WorldWideScience

Sample records for single network archtecture

  1. A Tuning Process in a Tunable Archtecture Computer System

    OpenAIRE

    深沢, 良彰; 岸野, 覚; 門倉, 敏夫

    1986-01-01

    A tuning process in a tunable archtecture computer is described. We have designed a computer system with tunable archtecture. Main components of this computer are four AM2903 bit-slice chips. The control schema of micro instructions is horizontal-type, and the length of each instruction is 104 bits. Our tunable algorithm utilizes an execution history of machine level instructions, because the execution history can be regarded as a property of the user program. In execution histories of simila...

  2. Single Frequency Networks (SFN in Digital Terrestrial Broadcasting

    Directory of Open Access Journals (Sweden)

    V. Ricny

    2007-12-01

    Full Text Available The paper deals with principles and properties of single frequency networks of digital television and radio transmitters. Basic definitions and contextual relationships (guard interval, area of SFN, influence of used modulation parameters etc. are explained.

  3. Neuronal synchrony detection on single-electron neural networks

    International Nuclear Information System (INIS)

    Oya, Takahide; Asai, Tetsuya; Kagaya, Ryo; Hirose, Tetsuya; Amemiya, Yoshihito

    2006-01-01

    Synchrony detection between burst and non-burst spikes is known to be one functional example of depressing synapses. Kanazawa et al. demonstrated synchrony detection with MOS depressing synapse circuits. They found that the performance of a network with depressing synapses that discriminates between burst and random input spikes increases non-monotonically as the static device mismatch is increased. We designed a single-electron depressing synapse and constructed the same network as in Kanazawa's study to develop noise-tolerant single-electron circuits. We examined the temperature characteristics and explored possible architecture that enables single-electron circuits to operate at T > 0 K

  4. 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.

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

    Science.gov (United States)

    Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

    2017-01-01

    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.

  6. Localization of multilayer networks by optimized single-layer rewiring.

    Science.gov (United States)

    Jalan, Sarika; Pradhan, Priodyuti

    2018-04-01

    We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

  7. 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.

  8. Noise characteristics of single-walled carbon nanotube network transistors

    International Nuclear Information System (INIS)

    Kim, Un Jeong; Kim, Kang Hyun; Kim, Kyu Tae; Min, Yo-Sep; Park, Wanjun

    2008-01-01

    The noise characteristics of randomly networked single-walled carbon nanotubes grown directly by plasma enhanced chemical vapor deposition (PECVD) are studied with field effect transistors (FETs). Due to the geometrical complexity of nanotube networks in the channel area and the large number of tube-tube/tube-metal junctions, the inverse frequency, 1/f, dependence of the noise shows a similar level to that of a single single-walled carbon nanotube transistor. Detailed analysis is performed with the parameters of number of mobile carriers and mobility in the different environment. This shows that the change in the number of mobile carriers resulting in the mobility change due to adsorption and desorption of gas molecules (mostly oxygen molecules) to the tube surface is a key factor in the 1/f noise level for carbon nanotube network transistors

  9. Sonochemical optimization of the conductivity of single wall nanotube networks

    NARCIS (Netherlands)

    Kaempgen, M.; Lebert, M.; Haluska, M.; Nicoloso, N.; Roth, S.

    2008-01-01

    Networks of single-wall carbon nanotubes (SWCNTs) are covalently functionalized with oxygen-containing groups. In lower concentration, these functional groups act as stable dopands improving the conductivity of the SWCNT material. In higher concentration however, their role as defects with a certain

  10. 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/

  11. 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.

  12. Deterministic Single-Photon Source for Distributed Quantum Networking

    International Nuclear Information System (INIS)

    Kuhn, Axel; Hennrich, Markus; Rempe, Gerhard

    2002-01-01

    A sequence of single photons is emitted on demand from a single three-level atom strongly coupled to a high-finesse optical cavity. The photons are generated by an adiabatically driven stimulated Raman transition between two atomic ground states, with the vacuum field of the cavity stimulating one branch of the transition, and laser pulses deterministically driving the other branch. This process is unitary and therefore intrinsically reversible, which is essential for quantum communication and networking, and the photons should be appropriate for all-optical quantum information processing

  13. Charge transport in transparent single-wall carbon nanotube networks

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  14. Single image super-resolution based on convolutional neural networks

    Science.gov (United States)

    Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

    2018-03-01

    We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

  15. A molecular quantum spin network controlled by a single qubit.

    Science.gov (United States)

    Schlipf, Lukas; Oeckinghaus, Thomas; Xu, Kebiao; Dasari, Durga Bhaktavatsala Rao; Zappe, Andrea; de Oliveira, Felipe Fávaro; Kern, Bastian; Azarkh, Mykhailo; Drescher, Malte; Ternes, Markus; Kern, Klaus; Wrachtrup, Jörg; Finkler, Amit

    2017-08-01

    Scalable quantum technologies require an unprecedented combination of precision and complexity for designing stable structures of well-controllable quantum systems on the nanoscale. It is a challenging task to find a suitable elementary building block, of which a quantum network can be comprised in a scalable way. We present the working principle of such a basic unit, engineered using molecular chemistry, whose collective control and readout are executed using a nitrogen vacancy (NV) center in diamond. The basic unit we investigate is a synthetic polyproline with electron spins localized on attached molecular side groups separated by a few nanometers. We demonstrate the collective readout and coherent manipulation of very few (≤ 6) of these S = 1/2 electronic spin systems and access their direct dipolar coupling tensor. Our results show that it is feasible to use spin-labeled peptides as a resource for a molecular qubit-based network, while at the same time providing simple optical readout of single quantum states through NV magnetometry. This work lays the foundation for building arbitrary quantum networks using well-established chemistry methods, which has many applications ranging from mapping distances in single molecules to quantum information processing.

  16. 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.

  17. 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

  18. Electroluminescence from single-wall carbon nanotube network transistors.

    Science.gov (United States)

    Adam, E; Aguirre, C M; Marty, L; St-Antoine, B C; Meunier, F; Desjardins, P; Ménard, D; Martel, R

    2008-08-01

    The electroluminescence (EL) properties from single-wall carbon nanotube network field-effect transistors (NNFETs) and small bundle carbon nanotube field effect transistors (CNFETs) are studied using spectroscopy and imaging in the near-infrared (NIR). At room temperature, NNFETs produce broad (approximately 180 meV) and structured NIR spectra, while they are narrower (approximately 80 meV) for CNFETs. EL emission from NNFETs is located in the vicinity of the minority carrier injecting contact (drain) and the spectrum of the emission is red shifted with respect to the corresponding absorption spectrum. A phenomenological model based on a Fermi-Dirac distribution of carriers in the nanotube network reproduces the spectral features observed. This work supports bipolar (electron-hole) current recombination as the main mechanism of emission and highlights the drastic influence of carrier distribution on the optoelectronic properties of carbon nanotube films.

  19. Cluster-based single-sink wireless sensor networks and passive optical network converged network incorporating sideband modulation schemes

    Science.gov (United States)

    Kumar, Love; Sharma, Vishal; Singh, Amarpal

    2018-02-01

    Wireless sensor networks have tremendous applications, such as civil, military, and environmental monitoring. In most of the applications, sensor data are required to be propagated over the internet/core networks, which result in backhaul setback. Subsequently, there is a necessity to backhaul the sensed information of such networks together with prolonging of the transmission link. Passive optical network (PON) is next-generation access technology emerging as a potential candidate for convergence of the sensed data to the core system. Earlier, the work with single-optical line terminal-PON was demonstrated and investigated merely analytically. This work is an attempt to demonstrate a practical model of a bidirectional single-sink wireless sensor network-PON converged network in which the collected data from cluster heads are transmitted over PON networks. Further, modeled converged structure has been investigated under the influence of double, single, and tandem sideband modulation schemes incorporating a corresponding phase-delay to the sensor data entities that have been overlooked in the past. The outcome illustrates the successful fusion of the sensor data entities over PON with acceptable bit error rate and signal to noise ratio serving as a potential development in the sphere of such converged networks. It has also been revealed that the data entities treated with tandem side band modulation scheme help in improving the performance of the converged structure. Additionally, analysis for uplink transmission reported with queue theory in terms of time cycle, average time delay, data packet generation, and bandwidth utilization. An analytical analysis of proposed converged network shows that average time delay for data packet transmission is less as compared with time cycle delay.

  20. Application for Single Price Auction Model (SPA) in AC Network

    Science.gov (United States)

    Wachi, Tsunehisa; Fukutome, Suguru; Chen, Luonan; Makino, Yoshinori; Koshimizu, Gentarou

    This paper aims to develop a single price auction model with AC transmission network, based on the principle of maximizing social surplus of electricity market. Specifically, we first formulate the auction market as a nonlinear optimization problem, which has almost the same form as the conventional optimal power flow problem, and then propose an algorithm to derive both market clearing price and trade volume of each player even for the case of market-splitting. As indicated in the paper, the proposed approach can be used not only for the price evaluation of auction or bidding market but also for analysis of bidding strategy, congestion effect and other constraints or factors. Several numerical examples are used to demonstrate effectiveness of our method.

  1. 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.

  2. Concave switching in single-hop and multihop networks

    NARCIS (Netherlands)

    Walton, N.

    2015-01-01

    Switched queueing networks model wireless networks, input-queued switches, and numerous other networked communications systems. We consider an (\\(\\alpha ,g\\))-switch policy; these policies provide a generalization of the MaxWeight policies of Tassiulas and Ephremides (IEEE Trans Autom Control

  3. Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network

    Science.gov (United States)

    2013-05-26

    public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University

  4. Pulsed neural networks consisting of single-flux-quantum spiking neurons

    International Nuclear Information System (INIS)

    Hirose, T.; Asai, T.; Amemiya, Y.

    2007-01-01

    An inhibitory pulsed neural network was developed for brain-like information processing, by using single-flux-quantum (SFQ) circuits. It consists of spiking neuron devices that are coupled to each other through all-to-all inhibitory connections. The network selects neural activity. The operation of the neural network was confirmed by computer simulation. SFQ neuron devices can imitate the operation of the inhibition phenomenon of neural networks

  5. 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

  6. From Single Target to Multitarget/Network Therapeutics in Alzheimer’s Therapy

    Directory of Open Access Journals (Sweden)

    Hailin Zheng

    2014-01-01

    Full Text Available Brain network dysfunction in Alzheimer’s disease (AD involves many proteins (enzymes, processes and pathways, which overlap and influence one another in AD pathogenesis. This complexity challenges the dominant paradigm in drug discovery or a single-target drug for a single mechanism. Although this paradigm has achieved considerable success in some particular diseases, it has failed to provide effective approaches to AD therapy. Network medicines may offer alternative hope for effective treatment of AD and other complex diseases. In contrast to the single-target drug approach, network medicines employ a holistic approach to restore network dysfunction by simultaneously targeting key components in disease networks. In this paper, we explore several drugs either in the clinic or under development for AD therapy in term of their design strategies, diverse mechanisms of action and disease-modifying potential. These drugs act as multi-target ligands and may serve as leads for further development as network medicines.

  7. Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

    International Nuclear Information System (INIS)

    Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

    2003-01-01

    Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

  8. Convergent evolution of gene networks by single-gene duplications in higher eukaryotes.

    Science.gov (United States)

    Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

    2004-03-01

    By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix-loop-helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks emerging through single-gene duplications, the dominant importance of molecular modularity in the bottom-up construction of complex biological entities, and the convergent evolution of networks.

  9. 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.

  10. Convergent evolution of gene networks by single-gene duplications in higher eukaryotes

    OpenAIRE

    Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

    2004-01-01

    By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix–loop–helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks e...

  11. Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network

    NARCIS (Netherlands)

    Tran, Van Tung; Thobiani, Faisal Al; Tinga, Tiedo; Ball, Andrew David; Niu, Gang

    2017-01-01

    In this paper, a hybrid deep belief network is proposed to diagnose single and combined faults of suction and discharge valves in a reciprocating compressor. This hybrid integrates the deep belief network structured by multiple stacked restricted Boltzmann machines for pre-training and simplified

  12. Toeless pulse shaping with a single delay-line network

    International Nuclear Information System (INIS)

    Tauhata, L.; Binns, D.C.

    1976-04-01

    New unipolar delay-line clippers producing negligible cancellation remnant have been developed. Near perfect clipping is achieved using a combination of several types of coaxial cable tranformers working as a phase inverter, a new pulse adder, or an impedance transformer. Only passive elements are used in the bridge network. The construction is simple and the performance is extremely stable and wide in dynamic range and frequency band width. Completely symmetrical bipolar pulses are also easily obtained using this technique

  13. A Fully Integrated Global Strategic Supply Network - A Critical Enabler of DoD Transformation

    Science.gov (United States)

    2004-01-01

    Enterprise Applications: Even New Archtectures May Not Bring Market Back to Life.” Giga Research, 26 September 2003. Kreisher, Otto. “The Key...Enterprise Applications: Even New Archtectures May Not Bring Market Back to Life. Giga Research, September 26, 2003, p.5. 9 Miller, Byron (2002

  14. 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....

  15. Archtecture of distributed real-time systems

    OpenAIRE

    Wing Leung, Cheuk

    2013-01-01

    CRAFTERS (Constraint and Application Driven Framework for Tailoring Embedded Real-time System) project aims to address the problem of uncertainty and heterogeneity in a distributed system by providing seamless, portable connectivity and middleware. This thesis contributes to the project by investigating the techniques that can be used in a distributed real-time embedded system. The conclusion is that, there is a list of specifications to be meet in order to provide a transparent and real-time...

  16. GPS data processing of networks with mixed single- and dual-frequency receivers for deformation monitoring

    Science.gov (United States)

    Zou, X.; Deng, Z.; Ge, M.; Dick, G.; Jiang, W.; Liu, J.

    2010-07-01

    In order to obtain crustal deformations of higher spatial resolution, existing GPS networks must be densified. This densification can be carried out using single-frequency receivers at moderate costs. However, ionospheric delay handling is required in the data processing. We adapt the Satellite-specific Epoch-differenced Ionospheric Delay model (SEID) for GPS networks with mixed single- and dual-frequency receivers. The SEID model is modified to utilize the observations from the three nearest dual-frequency reference stations in order to avoid contaminations from more remote stations. As data of only three stations are used, an efficient missing data constructing approach with polynomial fitting is implemented to minimize data losses. Data from large scale reference networks extended with single-frequency receivers can now be processed, based on the adapted SEID model. A new data processing scheme is developed in order to make use of existing GPS data processing software packages without any modifications. This processing scheme is evaluated using a sub-network of the German SAPOS network. The results verify that the new scheme provides an efficient way to densify existing GPS networks with single-frequency receivers.

  17. PbO networks composed of single crystalline nanosheets synthesized by a facile chemical precipitation method

    Energy Technology Data Exchange (ETDEWEB)

    Samberg, Joshua P. [Department of Materials Science and Engineering, North Carolina State University, 911 Partners Way, Engineering Building I, Raleigh, NC 27695-7907 (United States); Kajbafvala, Amir, E-mail: amir.kajbafvala@gmail.com [Department of Materials Science and Engineering, North Carolina State University, 911 Partners Way, Engineering Building I, Raleigh, NC 27695-7907 (United States); Koolivand, Amir [Department of Chemistry, North Carolina State University, 2620 Yarbrough Drive, Raleigh, NC 27695 (United States)

    2014-03-01

    Graphical abstract: - Highlights: • Synthesis of PbO networks through a simple chemical precipitation route. • The synthesis method is rapid and low-cost. • Each network is composed of single crystalline PbO nanosheets. • A possible growth mechanism is proposed for synthesized PbO networks. - Abstract: For the field of energy storage, nanostructured lead oxide (PbO) shows immense potential for increased specific energy and deep discharge for lead acid battery technologies. In this work, PbO networks composed of single crystalline nanosheets were synthesized utilizing a simple, low cost and rapid chemical precipitation method. The PbO networks were prepared in a single reaction vessel from starting reagents of lead acetate dehydrate, ammonium hydroxide and deionized water. Lead acetate dehydrate was chosen as a reagent, as opposed to lead nitrate, to eliminate the possibility of nitrate contamination of the final product. X-ray diffraction (XRD) analysis, high resolution scanning electron microscopy (HRSEM) and high resolution transmission electron microscopy (HRTEM) analysis were used to characterize the synthesized PbO networks. The reproducible method described herein synthesized pure β-PbO (massicot) powders, with no byproducts. A possible formation mechanism for these PbO networks is proposed. The growth is found to proceed predominately in the 〈1 1 1〉 and 〈2 0 0〉 directions while being limited in the 〈0 1 1〉 direction.

  18. PbO networks composed of single crystalline nanosheets synthesized by a facile chemical precipitation method

    International Nuclear Information System (INIS)

    Samberg, Joshua P.; Kajbafvala, Amir; Koolivand, Amir

    2014-01-01

    Graphical abstract: - Highlights: • Synthesis of PbO networks through a simple chemical precipitation route. • The synthesis method is rapid and low-cost. • Each network is composed of single crystalline PbO nanosheets. • A possible growth mechanism is proposed for synthesized PbO networks. - Abstract: For the field of energy storage, nanostructured lead oxide (PbO) shows immense potential for increased specific energy and deep discharge for lead acid battery technologies. In this work, PbO networks composed of single crystalline nanosheets were synthesized utilizing a simple, low cost and rapid chemical precipitation method. The PbO networks were prepared in a single reaction vessel from starting reagents of lead acetate dehydrate, ammonium hydroxide and deionized water. Lead acetate dehydrate was chosen as a reagent, as opposed to lead nitrate, to eliminate the possibility of nitrate contamination of the final product. X-ray diffraction (XRD) analysis, high resolution scanning electron microscopy (HRSEM) and high resolution transmission electron microscopy (HRTEM) analysis were used to characterize the synthesized PbO networks. The reproducible method described herein synthesized pure β-PbO (massicot) powders, with no byproducts. A possible formation mechanism for these PbO networks is proposed. The growth is found to proceed predominately in the 〈1 1 1〉 and 〈2 0 0〉 directions while being limited in the 〈0 1 1〉 direction

  19. 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

  20. 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.

  1. Single-hidden-layer feed-forward quantum neural network based on Grover learning.

    Science.gov (United States)

    Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

    2013-09-01

    In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. 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...

  3. 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...

  4. Scaling of F-actin network rheology to probe single filament elasticity and dynamics.

    Science.gov (United States)

    Gardel, M L; Shin, J H; MacKintosh, F C; Mahadevan, L; Matsudaira, P A; Weitz, D A

    2004-10-29

    The linear and nonlinear viscoelastic response of networks of cross-linked and bundled cytoskeletal filaments demonstrates remarkable scaling with both frequency and applied prestress, which helps elucidate the origins of the viscoelasticity. The frequency dependence of the shear modulus reflects the underlying single-filament relaxation dynamics for 0.1-10 rad/sec. Moreover, the nonlinear strain stiffening of such networks exhibits a universal form as a function of prestress; this is quantitatively explained by the full force-extension relation of single semiflexible filaments.

  5. 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.

  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

    two LC impedance networks and two isolated dc sources, which can significantly increase the overall system cost and require a more complex modulator for balancing the network inductive voltage boosting. Offering a number of less costly alternatives, this letter presents the design and control of two...... 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...

  7. Enhanced photoluminescence from single nitrogen-vacancy defects in nanodiamonds coated with metal-phenolic networks

    OpenAIRE

    Bray, Kerem; Previdi, Rodolfo; Gibson, Brant C.; Shimoni, Olga; Aharonovich, Igor

    2015-01-01

    Fluorescent nanodiamonds are attracting major attention in the field of bio-sensing and biolabeling. In this work we demonstrate a robust approach to surface functionalize individual nanodiamonds with metal-phenolic networks that enhance the photoluminescence from single nitrogen vacancy (NV) centers. We show that single NV centres in the coated nanodiamonds also exhibit shorter lifetimes, opening another channel for high resolution sensing. We propose that the nanodiamond encapsulation suppr...

  8. 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.

  9. 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.

  10. 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

  11. Retrieving Single Scattering Albedos and Temperatures from CRISM Hyperspectral Data Using Neural Networks

    Science.gov (United States)

    He, L.; Arvidson, R. E.; O'Sullivan, J. A.

    2018-04-01

    We use a neural network (NN) approach to simultaneously retrieve surface single scattering albedos and temperature maps for CRISM data from 1.40 to 3.85 µm. It approximates the inverse of DISORT which simulates solar and emission radiative streams.

  12. 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.

  13. 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.

  14. Single server queueing networks with varying service times and renewal input

    Directory of Open Access Journals (Sweden)

    Pierre Le Gall

    2000-01-01

    Full Text Available Using recent results in tandem queues and queueing networks with renewal input, when successive service times of the same customer are varying (and when the busy periods are frequently not broken up in large networks, the local queueing delay of a single server queueing network is evaluated utilizing new concepts of virtual and actual delays (respectively. It appears that because of an important property, due to the underlying tandem queue effect, the usual queueing standards (related to long queues cannot protect against significant overloads in the buffers due to some possible “agglutination phenomenon” (related to short queues. Usual network management methods and traffic simulation methods should be revised, and should monitor the partial traffic streams loads (and not only the server load.

  15. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    International Nuclear Information System (INIS)

    Hao Yinghang; Gong, Yubing; Wang Li; Ma Xiaoguang; Yang Chuanlu

    2011-01-01

    Research highlights: → Single synchronization transition for gap-junctional coupling. → Multiple synchronization transitions for chemical synaptic coupling. → Gap junctions and chemical synapses have different impacts on synchronization transition. → Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  16. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    Energy Technology Data Exchange (ETDEWEB)

    Hao Yinghang [School of Physics, Ludong University, Yantai 264025 (China); Gong, Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Wang Li; Ma Xiaoguang; Yang Chuanlu [School of Physics, Ludong University, Yantai 264025 (China)

    2011-04-15

    Research highlights: Single synchronization transition for gap-junctional coupling. Multiple synchronization transitions for chemical synaptic coupling. Gap junctions and chemical synapses have different impacts on synchronization transition. Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  17. 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

  18. A Neural Network Approach to Fluid Level Measurement in Dynamic Environments Using a Single Capacitive Sensor

    Directory of Open Access Journals (Sweden)

    Edin TERZIC

    2010-03-01

    Full Text Available A measurement system has been developed using a single tube capacitive sensor to accurately determine the fluid level in vehicular fuel tanks. A novel approach based on artificial neural networks based signal pre-processing and classification has been described in this article. A broad investigation on the Backpropagation neural network and some selected signal pre-processing filters, namely, Moving Mean, Moving Median, and Wavelet Filter has also been presented. An on field drive trial was conducted under normal driving conditions at various fuel volumes ranging from 5 L to 50 L to acquire training samples from the capacitive sensor. A second field trial was conducted to obtain test samples to verify the performance of the neural network. The neural network was trained and verified with 50 % of the training and test samples. The results obtained using the neural network approach having different filtration methods are compared with the results obtained using simple Moving Mean and Moving Median functions. It is demonstrated that the Backpropagation neural network with Moving Median filter produced the most accurate outcome compared with the other signal filtration methods.

  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. SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

    Science.gov (United States)

    Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

    2018-05-25

    Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

  1. 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

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

    Science.gov (United States)

    Liu, Dan; Liu, Xuejun; Wu, Yiguang

    2018-04-24

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

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

    Directory of Open Access Journals (Sweden)

    Dan Liu

    2018-04-01

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

  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.

    2018-06-01

    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 moveout. 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 2 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 catalogue (including 95 per cent of the catalogue events), and less than 1 per cent of these candidate events are false detections.

  6. The Report of MAZDA's Common Archtecture Vision : The one of the Common Archtecture Vision Features

    OpenAIRE

    Shiomi, Kousuke

    2012-01-01

    高機能で多様な製品を製品開発し続けることで,企業に大きな負担がかかることは否定できない。そして,その負担を軽減する技術として,製品を構成する部品種類数を削減する方法が存在する。これまでにも,設計部品図管理に優れるModular Design,部品群を生産ライン群と絡めて捉えるVariety Reduction Program,設備投資費の検討も行なうTypen und Teile などがその例として挙げられよう。これらの従来の部品種類数削減方法には,製造原価低減に関する問題点が存在し,その問題点のひとつの解決方法をマツダのコモンアーキテクチャ構想が提供した。 よって,本論文では,従来の部品種類数削減方法の問題点を解決するコモンアーキテクチャ構想の特徴のひとつについて述べる。...

  7. Mapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons.

    Science.gov (United States)

    Xiao, Dongsheng; Vanni, Matthieu P; Mitelut, Catalin C; Chan, Allen W; LeDue, Jeffrey M; Xie, Yicheng; Chen, Andrew Cn; Swindale, Nicholas V; Murphy, Timothy H

    2017-02-04

    Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps.

  8. DeepQA: improving the estimation of single protein model quality with deep belief networks.

    Science.gov (United States)

    Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

    2016-12-05

    Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

  9. Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging.

    Science.gov (United States)

    Patel, Tapan P; Man, Karen; Firestein, Bonnie L; Meaney, David F

    2015-03-30

    Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. Copyright © 2015. Published by Elsevier B.V.

  10. 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.

  11. Geometry in Biomimetic Network: Double Gyroid to Pseudo-Single Gyroid in Nanohybrid Materials

    Science.gov (United States)

    Hsueh, Han-Yu; Ho, Rong-Ming; Hung, Yu-Chueh; Ling, Yi-Chun; Hasegawa, Hirokazu

    2013-03-01

    Biological systems have developed delicately arranged micro- and architectures to produce striking optical effects since millions of years ago. Inspired by the textures of butterfly wings with single gyroid (SG) structure, herein, we aim to fabricate biocompatible and robust materials with SG-like structure in nanometer size so as to give new materials with unprecedented optical properties for applications. Biommicking from the biological photonic structures of butterfly wings, a double gyroid (DG) structure in nanometer size is obtained from the self-assembly of polystyrene-b-poly(L-lactide) (PS-PLLA). To acquire robust backbone networks, inorganic networks in polymer matrix are fabricated by using the hydrolyzed PS-PLLA with DG structure as a template for sol-gel reaction. Owing to the soft polymer matrix, two co-continuous inorganic networks embedded in the polymer matrix can be rearranged by thermal annealing at temperature above the glass transition of the polymer. Consequently, the rearrangement of these inorganic networks leads the formation of SG-like structure possessing unique nanohybrids with ordered texture. This unique nanomaterials with SG-like structure is referred as a pseudo-SG (p-SG) nanohybrids.

  12. Single-Cell Network Analysis Identifies DDIT3 as a Nodal Lineage Regulator in Hematopoiesis

    Directory of Open Access Journals (Sweden)

    Cristina Pina

    2015-06-01

    Full Text Available We explore cell heterogeneity during spontaneous and transcription-factor-driven commitment for network inference in hematopoiesis. Since individual genes display discrete OFF states or a distribution of ON levels, we compute and combine pairwise gene associations from binary and continuous components of gene expression in single cells. Ddit3 emerges as a regulatory node with positive linkage to erythroid regulators and negative association with myeloid determinants. Ddit3 loss impairs erythroid colony output from multipotent cells, while forcing Ddit3 in granulo-monocytic progenitors (GMPs enhances self-renewal and impedes differentiation. Network analysis of Ddit3-transduced GMPs reveals uncoupling of myeloid networks and strengthening of erythroid linkages. RNA sequencing suggests that Ddit3 acts through development or stabilization of a precursor upstream of GMPs with inherent Meg-E potential. The enrichment of Gata2 target genes in Ddit3-dependent transcriptional responses suggests that Ddit3 functions in an erythroid transcriptional network nucleated by Gata2.

  13. Single-Iteration Learning Algorithm for Feed-Forward Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Barhen, J.; Cogswell, R.; Protopopescu, V.

    1999-07-31

    A new methodology for neural learning is presented, whereby only a single iteration is required to train a feed-forward network with near-optimal results. To this aim, a virtual input layer is added to the multi-layer architecture. The virtual input layer is connected to the nominal input layer by a specird nonlinear transfer function, and to the fwst hidden layer by regular (linear) synapses. A sequence of alternating direction singular vrdue decompositions is then used to determine precisely the inter-layer synaptic weights. This algorithm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information &ansfer within a neural network.

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

    KAUST Repository

    Lavieville, Romain; Zhang, Yang; Di Fabrizio, Enzo M.; Krahne, Roman

    2013-01-01

    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.

  15. How single node dynamics enhances synchronization in neural networks with electrical coupling

    International Nuclear Information System (INIS)

    Bonacini, E.; Burioni, R.; Di Volo, M.; Groppi, M.; Soresina, C.; Vezzani, A.

    2016-01-01

    The stability of the completely synchronous state in neural networks with electrical coupling is analytically investigated applying both the Master Stability Function approach (MSF), developed by Pecora and Carroll (1998), and the Connection Graph Stability method (CGS) proposed by Belykh et al. (2004). The local dynamics is described by Morris–Lecar model for spiking neurons and by Hindmarsh–Rose model in spike, burst, irregular spike and irregular burst regimes. The combined application of both CGS and MSF methods provides an efficient estimate of the synchronization thresholds, namely bounds for the coupling strength ranges in which the synchronous state is stable. In all the considered cases, we observe that high values of coupling strength tend to synchronize the system. Furthermore, we observe a correlation between the single node attractor and the local stability properties given by MSF. The analytical results are compared with numerical simulations on a sample network, with excellent agreement.

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

    International Nuclear Information System (INIS)

    Hu Pingan; Zhang Jia; Wen Zhenzhong; Zhang Can

    2011-01-01

    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 x 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.

  17. Single-walled carbon nanotube networks for flexible and printed electronics

    International Nuclear Information System (INIS)

    Zaumseil, Jana

    2015-01-01

    Networks of single-walled carbon nanotubes (SWNTs) can be processed from solution and have excellent mechanical properties. They are highly flexible and stretchable. Depending on the type of nanotubes (semiconducting or metallic) they can be used as replacements for metal or transparent conductive oxide electrodes or as semiconducting layers for field-effect transistors (FETs) with high carrier mobilities. They are thus competitive alternatives to other solution-processable materials for flexible and printed electronics. This review introduces the basic properties of SWNTs, current methods for dispersion and separation of metallic and semiconducting SWNTs and techniques to deposit and pattern dense networks from dispersion. Recent examples of applications of carbon nanotubes as conductors and semiconductors in (opto-)electronic devices and integrated circuits will be discussed. (paper)

  18. 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.

  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. VPE single core medium voltage cables in EVU supply networks. [Polyethylene (VPE)

    Energy Technology Data Exchange (ETDEWEB)

    Reuter, E [Elektromark Kommunales Elektrizitaetswerk Mark A.G., Hagen (Germany, F.R.). Elektrotechnische Abt.

    1977-02-01

    This paper gives a brief outline of the different cable constructions and constructional parts of medium voltage cables (10 - 20 kV) in power supply networks. At medium voltage (particularly at 20 kV), single core cables are being used to an increasing extent, preferably for station supplies and for pole mounted cables. Polymerized polyethylene (VPE) is used as insulating material for this cable; according to present knowledge it is suitable for the insulation of power cables for all voltages up to 110 kV.

  2. 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

  3. 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......The asymmetry of the inherent distributed capacitances causes the rise of neutral-to-ground voltage in ungrounded system or high resistance grounded system. Overvoltage may occur in resonant grounded system if Petersen coil is resonant with the distributed capacitances. Thus, the restraint...

  4. 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.

  5. Estimating Single and Multiple Target Locations Using K-Means Clustering with Radio Tomographic Imaging in Wireless Sensor Networks

    Science.gov (United States)

    2015-03-26

    clustering is an algorithm that has been used in data mining applications such as machine learning applications , pattern recognition, hyper-spectral imagery...42 3.7.2 Application of K-means Clustering . . . . . . . . . . . . . . . . . 42 3.8 Experiment Design...Tomographic Imaging WLAN Wireless Local Area Networks WSN Wireless Sensor Network xx ESTIMATING SINGLE AND MULTIPLE TARGET LOCATIONS USING K-MEANS CLUSTERING

  6. Fabrication of triangular nanobeam waveguide networks in bulk diamond using single-crystal silicon hard masks

    International Nuclear Information System (INIS)

    Bayn, I.; Mouradian, S.; Li, L.; Goldstein, J. A.; Schröder, T.; Zheng, J.; Chen, E. H.; Gaathon, O.; Englund, Dirk; Lu, M.; Stein, A.; Ruggiero, C. A.; Salzman, J.; Kalish, R.

    2014-01-01

    A scalable approach for integrated photonic networks in single-crystal diamond using triangular etching of bulk samples is presented. We describe designs of high quality factor (Q = 2.51 × 10 6 ) photonic crystal cavities with low mode volume (V m  = 1.062 × (λ/n) 3 ), which are connected via waveguides supported by suspension structures with predicted transmission loss of only 0.05 dB. We demonstrate the fabrication of these structures using transferred single-crystal silicon hard masks and angular dry etching, yielding photonic crystal cavities in the visible spectrum with measured quality factors in excess of Q = 3 × 10 3

  7. Path selection rules for droplet trains in single-lane microfluidic networks

    Science.gov (United States)

    Amon, A.; Schmit, A.; Salkin, L.; Courbin, L.; Panizza, P.

    2013-07-01

    We investigate the transport of periodic trains of droplets through microfluidic networks having one inlet, one outlet, and nodes consisting of T junctions. Variations of the dilution of the trains, i.e., the distance between drops, reveal the existence of various hydrodynamic regimes characterized by the number of preferential paths taken by the drops. As the dilution increases, this number continuously decreases until only one path remains explored. Building on a continuous approach used to treat droplet traffic through a single asymmetric loop, we determine selection rules for the paths taken by the drops and we predict the variations of the fraction of droplets taking these paths with the parameters at play including the dilution. Our results show that as dilution decreases, the paths are selected according to the ascending order of their hydrodynamic resistance in the absence of droplets. The dynamics of these systems controlled by time-delayed feedback is complex: We observe a succession of periodic regimes separated by a wealth of bifurcations as the dilution is varied. In contrast to droplet traffic in single asymmetric loops, the dynamical behavior in networks of loops is sensitive to initial conditions because of extra degrees of freedom.

  8. 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.

  9. 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 S

    2016-07-01

    Single image super-resolution (SR) is an ill-posed problem, which tries to recover a high-resolution image from its low-resolution 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 SR 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 the existing state-of-the-art methods for various scaling factors both quantitatively and perceptually.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

    Science.gov (United States)

    Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

    2014-01-01

    Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

  15. 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.

  16. 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

  17. 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

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

    Directory of Open Access Journals (Sweden)

    Sadra Sadeh

    2015-01-01

    Full Text Available 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

  19. 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

  20. 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-

  1. Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

    Science.gov (United States)

    Tiwari, Shivendra N.; Padhi, Radhakant

    2018-01-01

    Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

  2. 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.

  3. 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.

  4. Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

    Science.gov (United States)

    Nilsaz-Dezfouli, Hamid; Abu-Bakar, Mohd Rizam; Arasan, Jayanthi; Adam, Mohd Bakri; Pourhoseingholi, Mohamad Amin

    2017-01-01

    In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve. PMID:28469384

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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......The multiple-input-multiple-output (MIMO) technique is the most attractive candidate to improve the spectrum efficiency in the next generation wireless communication systems. However, the efficiency of MIMO techniques reduces in the line of sight (LOS) environments. In this paper, we propose a new...

  11. SIP-Based Single Neuron Stochastic Predictive Control for Non-Gaussian Networked Control Systems with Uncertain Metrology Delays

    Directory of Open Access Journals (Sweden)

    Xinying Xu

    2018-06-01

    Full Text Available In this paper, a novel data-driven single neuron predictive control strategy is proposed for non-Gaussian networked control systems with metrology delays in the information theory framework. Firstly, survival information potential (SIP, instead of minimum entropy, is used to formulate the performance index to characterize the randomness of the considered systems, which is calculated by oversampling method. Then the minimum values can be computed by optimizing the SIP-based performance index. Finally, the proposed strategy, minimum entropy method and mean square error (MSE are applied to a networked motor control system, and results demonstrated the effectiveness of the proposed strategy.

  12. 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.

  13. A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

    Science.gov (United States)

    Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

    2006-12-01

    Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

  14. Optimization Study of Hydrogen Gas Adsorption on Zig-zag Single-walled Carbon Nanotubes: The Artificial Neural Network Analysis

    Science.gov (United States)

    Nasruddin; Lestari, M.; Supriyadi; Sholahudin

    2018-03-01

    The use of hydrogen gas in fuel cell technology has a huge opportunity to be applied in upcoming vehicle technology. One of the most important problems in fuel cell technology is the hydrogen storage. The adsorption of hydrogen in carbon-based materials attracts a lot of attention because of its reliability. This study investigated the adsorption of hydrogen gas in Single-walled Carbon Nano Tubes (SWCNT) with chilarity of (0, 12), (0, 15), and (0, 18) to find the optimum chilarity. Artificial Neural Networks (ANN) can be used to predict the hydrogen storage capacity at different pressure and temperature conditions appropriately, using simulated series of data. The Artificial Neural Network is modeled as a predictor of the hydrogen adsorption capacity which provides solutions to some deficiencies in molecular dynamics (MD) simulations. In a previous study, ANN configurations have been developed for 77k, 233k, and 298k temperatures in hydrogen gas storage. To prepare this prediction, ANN is modeled to find out the configurations that exist in the set of training and validation of specified data selection, the distance between data, and the number of neurons that produce the smallest error. This configuration is needed to make an accurate artificial neural network. The configuration of neural network was then applied to this research. The neural network analysis results show that the best configuration of artificial neural network in hydrogen storage is at 233K temperature i.e. on SWCNT with chilarity of (0.12).

  15. Growth of single walled carbon nanotubes networks using Al - Ni as catalyst

    International Nuclear Information System (INIS)

    Kotlar, M.; Vesely, M.; Redhammer, R.; Vretenar, V.

    2011-01-01

    The growth of SWCNTs networks on the SiO 2 chips was examined for different growth temperatures and annealing times. According to Raman spectroscopy the temperature is a significant parameter which affects quality of carbon nanotubes. For higher temperatures (850 - 900 deg C) the best quality was achieved. On the other hand, the different annealing times did not affect results of our experiments. SWCNTs network consists of large amount of intersecting carbon nanotubes. This network is electrically conductive over large distances. The SWCNTs networks can be used as transparent conductive layer or as sensitive layer of chemical sensors. (authors)

  16. 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...

  17. Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing.

    Science.gov (United States)

    Strus, Mark C; Chiaramonti, Ann N; Kim, Young Lae; Jung, Yung Joon; Keller, Robert R

    2011-07-01

    We investigate the electrical reliability of nanoscale lines of highly aligned, networked, metallic/semiconducting single-walled carbon nanotubes (SWCNTs) fabricated through a template-based fluidic assembly process. We find that these SWCNT networks can withstand DC current densities larger than 10 MA cm(-2) for several hours and, in some cases, several days. We develop test methods that show that the degradation rate, failure predictability and total device lifetime can be linked to the initial resistance. Scanning electron and transmission electron microscopy suggest that fabrication variability plays a critical role in the rate of degradation, and we offer an empirical method of quickly determining the long-term performance of a network. We find that well-fabricated lines subject to constant electrical stress show a linear accumulation of damage reminiscent of electromigration in metallic interconnects, and we explore the underlying physical mechanisms that could cause such behavior.

  18. Cu-O network dependence of optical charge-transfer gaps and spin-pair excitations in single-CuO2-layer compounds

    International Nuclear Information System (INIS)

    Tokura, Y.; Koshihara, S.; Arima, T.; Takagi, H.; Ishibashi, S.; Ido, T.; Uchida, S.

    1990-01-01

    Spectra of optical conductivity and magnon Raman scattering have been investigated in single crystals of a parent family of cuprate superconductors with various types of Cu-O single-layer networks. The analysis of the spectra shows the systematic dependence of the charge-transfer gaps and covalent character of Cu-O bonds on the pattern of the Cu-O network, while the spin-exchange energy is rather convergent for all the single-CuO 2 -sheet compounds

  19. 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.

  20. 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.

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

    Science.gov (United States)

    Rao, K. D. M.; Kulkarni, Giridhar U.

    2014-05-01

    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. 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. Electronic supplementary information (ESI) available: Optical micrographs, EDAX, XRD, SEM and TEM images of Au metal wires. See DOI: 10.1039/c4nr00869c

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

    DEFF Research Database (Denmark)

    Landex, Alex

    2009-01-01

    lines and single track lines are discussed in this article. The principles of the UIC 406 of double track lines can be applied to single track lines-at least when more than one train follows each other in the same direction. In a presentation of the UIC 406 for single track operations, it is important...

  3. Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

    Science.gov (United States)

    Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

    2018-04-24

    An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

  4. Mapping the q-voter model: From a single chain to complex networks

    Science.gov (United States)

    Jȩdrzejewski, Arkadiusz; Sznajd-Weron, Katarzyna; Szwabiński, Janusz

    2016-03-01

    We propose and compare six different ways of mapping the modified q-voter model to complex networks. Considering square lattices, Barabási-Albert, Watts-Strogatz and real Twitter networks, we ask the question if always a particular choice of the group of influence of a fixed size q leads to different behavior at the macroscopic level. Using Monte Carlo simulations we show that the answer depends on the relative average path length of the network and for real-life topologies the differences between the considered mappings may be negligible.

  5. 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.

  6. Stochastic resonance in an ensemble of single-electron neuromorphic devices and its application to competitive neural networks

    International Nuclear Information System (INIS)

    Oya, Takahide; Asai, Tetsuya; Amemiya, Yoshihito

    2007-01-01

    Neuromorphic computing based on single-electron circuit technology is gaining prominence because of its massively increased computational efficiency and the increasing relevance of computer technology and nanotechnology [Likharev K, Mayr A, Muckra I, Tuerel O. CrossNets: High-performance neuromorphic architectures for CMOL circuits. Molec Electron III: Ann NY Acad Sci 1006;2003:146-63; Oya T, Schmid A, Asai T, Leblebici Y, Amemiya Y. On the fault tolerance of a clustered single-electron neural network for differential enhancement. IEICE Electron Expr 2;2005:76-80]. The maximum impact of these technologies will be strongly felt when single-electron circuits based on fault- and noise-tolerant neural structures can operate at room temperature. In this paper, inspired by stochastic resonance (SR) in an ensemble of spiking neurons [Collins JJ, Chow CC, Imhoff TT. Stochastic resonance without tuning. Nature 1995;376:236-8], we propose our design of a basic single-electron neural component and report how we examined its statistical results on a network

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

    KAUST Repository

    Ayala Solares, Jose Roberto; Rezki, Zouheir; Alouini, Mohamed-Slim

    2012-01-01

    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

  8. A Hybrid Fuzzy Time Series Approach Based on Fuzzy Clustering and Artificial Neural Network with Single Multiplicative Neuron Model

    Directory of Open Access Journals (Sweden)

    Ozge Cagcag Yolcu

    2013-01-01

    Full Text Available Particularly in recent years, artificial intelligence optimization techniques have been used to make fuzzy time series approaches more systematic and improve forecasting performance. Besides, some fuzzy clustering methods and artificial neural networks with different structures are used in the fuzzification of observations and determination of fuzzy relationships, respectively. In approaches considering the membership values, the membership values are determined subjectively or fuzzy outputs of the system are obtained by considering that there is a relation between membership values in identification of relation. This necessitates defuzzification step and increases the model error. In this study, membership values were obtained more systematically by using Gustafson-Kessel fuzzy clustering technique. The use of artificial neural network with single multiplicative neuron model in identification of fuzzy relation eliminated the architecture selection problem as well as the necessity for defuzzification step by constituting target values from real observations of time series. The training of artificial neural network with single multiplicative neuron model which is used for identification of fuzzy relation step is carried out with particle swarm optimization. The proposed method is implemented using various time series and the results are compared with those of previous studies to demonstrate the performance of the proposed method.

  9. 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.......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 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...

  10. 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,

  11. 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

  12. 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.

  13. Identification of driving network of cellular differentiation from single sample time course gene expression data

    Science.gov (United States)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  14. 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

    2018-01-01

    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. PMID:29671822

  15. Near-optimality of special periodic protocols for fluid models of single server switched networks with switchover times

    Science.gov (United States)

    Matveev, A. S.; Ishchenko, R.

    2017-11-01

    We consider a generic deterministic time-invariant fluid model of a single server switched network, which consists of finitely many infinite size buffers (queues) and receives constant rate inflows of jobs from the outside. Any flow undergoes a multi-phase service, entering a specific buffer after every phase, and ultimately leaves the network; the route of the flow over the buffers is pre-specified, and flows may merge inside the network. They share a common source of service, which can serve at most one buffer at a time and has to switch among buffers from time to time; any switch consumes a nonzero switchover period. With respect to the long-run maximal scaled wip (work in progress) performance metric, near-optimality of periodic scheduling and service protocols is established: the deepest optimum (that is over all feasible processes in the network, irrespective of the initial state) is furnished by such a protocol up to as small error as desired. Moreover, this can be achieved with a special periodic protocol introduced in the paper. It is also shown that the exhaustive policy is optimal for any buffer whose service at the maximal rate does not cause growth of the scaled wip.

  16. A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamidreza Mousavi

    2017-01-01

    Full Text Available Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN. In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

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

    International Nuclear Information System (INIS)

    Kim, Un Jeong; Park, Wanjun

    2009-01-01

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

  18. A low noise single-transistor transimpedance preamplifier for Fourier-transform mass spectrometry using a T feedback network.

    Science.gov (United States)

    Lin, Tzu-Yung; Green, Roger J; O'Connor, Peter B

    2012-09-01

    A novel single-transistor transimpedance preamplifier has been introduced for improving performance in Fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry. A low noise junction field-effect transistor (JFET), BF862, is used as the main amplification stage of this trans-impedance preamplifier, and a T-shaped feedback network is introduced as both the feedback and the gate biasing solutions. The T feedback network has been studied using an operational amplifier (Op Amp), AD8099. Such a feedback system allows ~100-fold less feedback resistance at a given transimpedance, hence preserving bandwidth, which is beneficial to applications demanding high gain. The single-transistor preamplifier yields a tested transimpedance of ~10(4) Ω (80 dBΩ) in the frequency range between 1 kHz and 1 MHz (mass-to-charge ratio, m/z, of around 180-180k for a 12-T FT-ICR system), with a low power consumption of ~6 mW, which implies that this preamplifier is well suited to a 12-T FT-ICR mass spectrometer. In trading noise performance for higher trans-impedance, an alternative preamplifier design, an AD8099 preamplifier with the T feedback network, has also been studied with a capability of ~10(6) Ω (120 dBΩ) transimpedance in the same frequency range. The resistive components in the T feedback network reported here can be replaced by complex impedances, which allows adaptation of this feedback system to other frequency, transimpedance, and noise characteristics for applications not only in other mass spectrometers, such as Orbitrap, time-of-flight (TOF), and ion trap systems, but also in other charge/current detecting systems such as spectroscopy systems, microscopy systems, optical communication systems, or charge-coupled devices (CCDs).

  19. 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

  20. 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.

  1. 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

  2. DeepQA: Improving the estimation of single protein model quality with deep belief networks

    OpenAIRE

    Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

    2016-01-01

    Background Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. Results We introduce a novel single-model quality assessment method DeepQA based on deep belie...

  3. Capacity Bounds on the Downlink of Symmetric, Multi-Relay, Single-Receiver C-RAN Networks

    Directory of Open Access Journals (Sweden)

    Shirin Saeedi Bidokhti

    2017-11-01

    Full Text Available The downlink of symmetric Cloud Radio Access Networks (C-RANs with multiple relays and a single receiver is studied. Lower and upper bounds are derived on the capacity. The lower bound is achieved by Marton’s coding, which facilitates dependence among the multiple-access channel inputs. The upper bound uses Ozarow’s technique to augment the system with an auxiliary random variable. The bounds are studied over scalar Gaussian C-RANs and are shown to meet and characterize the capacity for interesting regimes of operation.

  4. 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.

  5. Quantum logic networks for controlled teleportation of a single particle via W state

    Institute of Scientific and Technical Information of China (English)

    Yuan Hong-Chun; Qi Kai-Guo

    2005-01-01

    We discuss the scheme for probabilistic and controlled teleportation of an unknown state of one particle using the general three-particle W state as the quantum channel. The feature of this scheme is that teleportation between two sides depends on the agreement of the third side (Charlie), who may participate the process of quantum teleportation as a supervisor. In addition, we also construct efficient quantum logic networks for implementing the new scheme by means of the primitive operations.

  6. 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.

  7. 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

  8. Pulse patterning effect in optical pulse division multiplexing for flexible single wavelength multiple access optical network

    Science.gov (United States)

    Jung, Sun-Young; Kim, Chang-Hun; Han, Sang-Kook

    2018-05-01

    A demand for high spectral efficiency requires multiple access within a single wavelength, but the uplink signals are significantly degraded because of optical beat interference (OBI) in intensity modulation/direct detection system. An optical pulse division multiplexing (OPDM) technique was proposed that could effectively reduce the OBI via a simple method as long as near-orthogonality is satisfied, but the condition was strict, and thus, the number of multiplexing units was very limited. We propose pulse pattern enhanced OPDM (e-OPDM) to reduce the OBI and improve the flexibility in multiple access within a single wavelength. The performance of the e-OPDM and patterning effect are experimentally verified after 23-km single mode fiber transmission. By employing pulse patterning in OPDM, the tight requirement was relaxed by extending the optical delay dynamic range. This could support more number of access with reduced OBI, which could eventually enhance a multiple access function.

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Dawson, M R.W. [Dept. of Psychology, Univ. of Alberta, Edmonton (Canada); Dobbs, A [Dept. of Psychology, Univ. of Alberta, Edmonton (Canada); Hooper, H R [Dept. of Nuclear Medicine, Cross Cancer Inst., Edmonton, AB (Canada); McEwan, A J.B. [Dept. of Radiology and Diagnostic Imaging, Univ. of Alberta, Edmonton (Canada); Triscott, J [Dept. of Family Medicine and Div. of Geriatric Medicine, Univ. of Alberta, Edmonton (Canada); Cooney, J [Dept. of Psychiatry, Univ. of Alberta, Edmonton (Canada)

    1994-12-01

    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.)

  11. 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.)

  12. 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

  13. Potential pitfalls of single phasing operation in a three phase distribution network

    Energy Technology Data Exchange (ETDEWEB)

    Narayanan, V S

    1986-07-01

    Finding it difficult to cope with the increased demand for electric power, some electricity boards have resorted to single phasing techniques in distribution system. This practice is harmful to the equipment in the power system. Some of the potential dangers associated with this undesirable practice are briefly discussed.

  14. On the effectiveness of single and multiple base station sleep modes in cellular networks

    OpenAIRE

    Marsan, Marco Ajmone; Chiaraviglio, Luca; Ciullo, Delia; Meo, Michela

    2013-01-01

    In this paper we study base station sleep modes that, by reducing power consumption in periods of low traffic, improve the energy efficiency of cellular access networks. We assume that when some base stations enter sleep mode, radio coverage and service provisioning are provided by the base stations that remain active, so as to guarantee that service is available over the whole area at all times. This may be an optimistic assumption in the case of the sparse base station layouts typical of ru...

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

    Energy Technology Data Exchange (ETDEWEB)

    Opatkiewicz, Justin P; LeMieux, Melburne C; Bao Zhenan [Department of Chemical Engineering, Stanford University, Stanford, CA 94305 (United States); Patil, Nishant P; Wei Hai; Mitra, Subhasish, E-mail: zbao@stanford.edu [Department of Electrical Engineering, Stanford University, Stanford, CA 94305 (United States)

    2011-03-25

    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, {mu}-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.

  16. 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.

  17. Dentist Material Selection for Single-Unit Crowns: Findings from The National Dental Practice-Based Research Network

    Science.gov (United States)

    Makhija, Sonia K.; Lawson, Nathaniel C.; Gilbert, Gregg H.; Litaker, Mark S.; McClelland, Jocelyn A.; Louis, David R.; Gordan, Valeria V.; Pihlstrom, Daniel J.; Meyerowitz, Cyril; Mungia, Rahma; McCracken, Michael S.

    2016-01-01

    Objectives Dentists enrolled in the National Dental Practice-Based Research Network completed a study questionnaire about techniques and materials used for single-unit crowns and an enrollment questionnaire about dentist/practice characteristics. The objectives were to quantify dentists’ material recommendations and test the hypothesis that dentist’s and practice’s characteristics are significantly associated with these recommendations. Methods Surveyed dentists responded to a contextual scenario asking what material they would use for a single-unit crown on an anterior and posterior tooth. Material choices included: full metal, porcelain-fused-to-metal (PFM), all-zirconia, layered zirconia, lithium disilicate, leucite-reinforced ceramic, or other. Results 1,777 of 2,132 eligible dentists responded (83%). The top 3 choices for anterior crowns were lithium disilicate (54%), layered zirconia (17%), and leucite-reinforced glass ceramic (13%). There were significant differences (p<0.05) by dentist’s gender, race, years since graduation, practice type, region, practice busyness, hours worked/week, and location type. The top 3 choices for posterior crowns were all-zirconia (32%), PFM (31%), and lithium disilicate (21%). There were significant differences (p<0.05) by dentist’s gender, practice type, region, practice busyness, insurance coverage, hours worked/week, and location type. Conclusions Network dentists use a broad range of materials for single-unit crowns for anterior and posterior teeth, adopting newer materials into their practices as they become available. Material choices are significantly associated with dentist’s and practice’s characteristics. Clinical Significance Decisions for crown material may be influenced by factors unrelated to tooth and patient variables. Dentists should be cognizant of this when developing an evidence-based approach to selecting crown material. PMID:27693778

  18. Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.

    Science.gov (United States)

    Urtnasan, Erdenebayar; Park, Jong-Uk; Joo, Eun-Yeon; Lee, Kyoung-Joung

    2018-04-23

    In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers including activation, pooling, and dropout layers. One-dimensional (1D) convolution, rectified linear units (ReLU), and max pooling were applied to the convolution, activation, and pooling layers, respectively. For training and evaluation of the CNN model, a single-lead ECG dataset was collected from 82 subjects with OSA and was divided into training (including data from 63 patients with 34,281 events) and testing (including data from 19 patients with 8571 events) datasets. Using this CNN model, a precision of 0.99%, a recall of 0.99%, and an F 1 -score of 0.99% were attained with the training dataset; these values were all 0.96% when the CNN was applied to the testing dataset. These results show that the proposed CNN model can be used to detect OSA accurately on the basis of a single-lead ECG. Ultimately, this CNN model may be used as a screening tool for those suspected to suffer from OSA.

  19. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Alfinito, Eleonora; Pennetta, Cecilia; Reggiani, Lino [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via Arnesano, Lecce (Italy); Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia (CNISM) (Italy)

    2008-02-13

    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.

  1. Not single brain areas but a network is involved in language: Applications in presurgical planning.

    Science.gov (United States)

    Alemi, Razieh; Batouli, Seyed Amir Hossein; Behzad, Ebrahim; Ebrahimpoor, Mitra; Oghabian, Mohammad Ali

    2018-02-01

    Language is an important human function, and is a determinant of the quality of life. In conditions such as brain lesions, disruption of the language function may occur, and lesion resection is a solution for that. Presurgical planning to determine the language-related brain areas would enhance the chances of language preservation after the operation; however, availability of a normative language template is essential. In this study, using data from 60 young individuals who were meticulously checked for mental and physical health, and using fMRI and robust imaging and data analysis methods, functional brain maps for the language production, perception and semantic were produced. The obtained templates showed that the language function should be considered as the product of the collaboration of a network of brain regions, instead of considering only few brain areas to be involved in that. This study has important clinical applications, and extends our knowledge on the neuroanatomy of the language function. Copyright © 2018 Elsevier B.V. All rights reserved.

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

    DEFF Research Database (Denmark)

    Szwagrzak, Karol

    2016-01-01

    disequilibrium prices, etc. In these contexts suppliers and demanders naturally have single-peaked preferences. We evaluate transfer rules on the basis of the “replacement principle” (Thomson, J Econ Theory 76(1):145–168 1997; Moulin, Q J Econ 102:769–783 1987), the requirement that a change in an agent......’s preferences affects all other agents in the same direction in terms of welfare. We find that the only Pareto-efficient, participation-compatible, replication-invariant, and envy-free rule satisfying an appropriate formulation of the replacement principle is the “egalitarian rule” introduced by Bochet et al....... (Theor Econ 7:395–423 2012)....

  3. Online Adaptive Optimal Control of Vehicle Active Suspension Systems Using Single-Network Approximate Dynamic Programming

    Directory of Open Access Journals (Sweden)

    Zhi-Jun Fu

    2017-01-01

    Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. Multiclass classification of obstructive sleep apnea/hypopnea based on a convolutional neural network from a single-lead electrocardiogram.

    Science.gov (United States)

    Urtnasan, Erdenebayar; Park, Jong-Uk; Lee, Kyoung-Joung

    2018-05-24

    In this paper, we propose a convolutional neural network (CNN)-based deep learning architecture for multiclass classification of obstructive sleep apnea and hypopnea (OSAH) using single-lead electrocardiogram (ECG) recordings. OSAH is the most common sleep-related breathing disorder. Many subjects who suffer from OSAH remain undiagnosed; thus, early detection of OSAH is important. In this study, automatic classification of three classes-normal, hypopnea, and apnea-based on a CNN is performed. An optimal six-layer CNN model is trained on a training dataset (45,096 events) and evaluated on a test dataset (11,274 events). The training set (69 subjects) and test set (17 subjects) were collected from 86 subjects with length of approximately 6 h and segmented into 10 s durations. The proposed CNN model reaches a mean -score of 93.0 for the training dataset and 87.0 for the test dataset. Thus, proposed deep learning architecture achieved a high performance for multiclass classification of OSAH using single-lead ECG recordings. The proposed method can be employed in screening of patients suspected of having OSAH. © 2018 Institute of Physics and Engineering in Medicine.

  12. 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.

  13. 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.

  14. Forming a three-dimensional porous organic network via solid-state explosion of organic single crystals.

    Science.gov (United States)

    Bae, Seo-Yoon; Kim, Dongwook; Shin, Dongbin; Mahmood, Javeed; Jeon, In-Yup; Jung, Sun-Min; Shin, Sun-Hee; Kim, Seok-Jin; Park, Noejung; Lah, Myoung Soo; Baek, Jong-Beom

    2017-11-17

    Solid-state reaction of organic molecules holds a considerable advantage over liquid-phase processes in the manufacturing industry. However, the research progress in exploring this benefit is largely staggering, which leaves few liquid-phase systems to work with. Here, we show a synthetic protocol for the formation of a three-dimensional porous organic network via solid-state explosion of organic single crystals. The explosive reaction is realized by the Bergman reaction (cycloaromatization) of three enediyne groups on 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene. The origin of the explosion is systematically studied using single-crystal X-ray diffraction and differential scanning calorimetry, along with high-speed camera and density functional theory calculations. The results suggest that the solid-state explosion is triggered by an abrupt change in lattice energy induced by release of primer molecules in the 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene crystal lattice.

  15. 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.

  16. Separation of a single photon and products of the π0, η and K0s meson neutral decay channels using neural network

    International Nuclear Information System (INIS)

    Bandurin, D.V.; Skachkov, N.B.

    2004-01-01

    The artificial neural network approach is used for separation of signals from a single photon and products of the π 0 , η and K s 0 meson neutral decay channels on the basis of the data from the CMS electromagnetic calorimeter alone. Rejection values for the three types of mesons as a function of single photon selection efficiencies are obtained for two pseudorapidity regions and initial Et of 20, 40, 60 and 100 GeV. (author)

  17. Separation of a single photon and products of the π0-, η-, Ks0-meson neutral decay channels in the CMS electromagnetic calorimeter using neural network

    International Nuclear Information System (INIS)

    Bandurin, D.V.; Skachkov, N.B.

    2001-01-01

    The artificial neural network approach is used for separation of signals from a single photon γ and products of the π 0 -, η-, K s 0 -meson neutral decay channels on the basis of the data from the CMS electromagnetic calorimeter alone. Rejection values for the three types of mesons as a function of single photon selection efficiencies are obtained for two Barrel and one Endcap pseudorapidity regions and initial E t of 20, 40, 60 and 100 GeV

  18. 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

  19. 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...

  20. 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

  1. 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

  2. Outcomes of single organism peritonitis in peritoneal dialysis: gram negatives versus gram positives in the Network 9 Peritonitis Study.

    Science.gov (United States)

    Bunke, C M; Brier, M E; Golper, T A

    1997-08-01

    The use of the "peritonitis rate" in the management of patients undergoing peritoneal dialysis is assuming importance in comparing the prowess of facilities, care givers and new innovations. For this to be a meaningful outcome measure, the type of infection (causative pathogen) must have less clinical significance than the number of infections during a time interval. The natural history of Staphylococcus aureus, pseudomonas, and fungal peritonitis would not support that the outcome of an episode of peritonitis is independent of the causative pathogen. Could this concern be extended to other more frequently occurring pathogens? To address this, the Network 9 Peritonitis Study identified 530 episodes of single organism peritonitis caused by a gram positive organism and 136 episodes caused by a single non-pseudomonal gram negative (NPGN) pathogen. Coincidental soft tissue infections (exit site or tunnel) occurred equally in both groups. Outcomes of peritonitis were analyzed by organism classification and by presence or absence of a soft tissue infection. NPGN peritonitis was associated with significantly more frequent catheter loss, hospitalization, and technique failure and was less likely to resolve regardless of the presence or absence of a soft tissue infection. Hospitalization and death tended to occur more frequently with enterococcal peritonitis than with other gram positive peritonitis. The outcomes in the NPGN peritonitis group were significantly worse (resolution, catheter loss, hospitalization, technique failure) compared to coagulase negative staphylococcal or S. aureus peritonitis, regardless of the presence or absence of a coincidental soft tissue infection. Furthermore, for the first time, the poor outcomes of gram negative peritonitis are shown to be independent of pseudomonas or polymicrobial involvement or soft tissue infections. The gram negative organism appears to be the important factor. In addition, the outcome of peritonitis caused by S. aureus

  3. 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.

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

    KAUST Repository

    Hadjtaieb, Amir

    2014-01-01

    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

  6. 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

  7. Multi-port network and 3D finite-element models for accurate transformer calculations: Single-phase load-loss test

    Energy Technology Data Exchange (ETDEWEB)

    Escarela-Perez, R. [Departamento de Energia, Universidad Autonoma Metropolitana, Av. San Pablo 180, Col. Reynosa, C.P. 02200, Mexico D.F. (Mexico); Kulkarni, S.V. [Electrical Engineering Department, Indian Institute of Technology, Bombay (India); Melgoza, E. [Instituto Tecnologico de Morelia, Av. Tecnologico 1500, Morelia, Mich., C.P. 58120 (Mexico)

    2008-11-15

    A six-port impedance network for a three-phase transformer is obtained from a 3D time-harmonic finite-element (FE) model. The network model properly captures the eddy current effects of the transformer tank and frame. All theorems and tools of passive linear networks can be used with the multi-port model to simulate several important operating conditions without resorting anymore to computationally expensive 3D FE simulations. The results of the network model are of the same quality as those produced by the FE program. Although the passive network may seem limited by the assumption of linearity, many important transformer operating conditions imply unsaturated states. Single-phase load-loss measurements are employed to demonstrate the effectiveness of the network model and to understand phenomena that could not be explained with conventional equivalent circuits. In addition, formal deduction of novel closed-form formulae is presented for the calculation of the leakage impedance measured at the high and low voltage sides of the transformer. (author)

  8. 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.

  9. A single charge in the actin binding domain of fascin can independently tune the linear and non-linear response of an actin bundle network.

    Science.gov (United States)

    Maier, M; Müller, K W; Heussinger, C; Köhler, S; Wall, W A; Bausch, A R; Lieleg, O

    2015-05-01

    Actin binding proteins (ABPs) not only set the structure of actin filament assemblies but also mediate the frequency-dependent viscoelastic moduli of cross-linked and bundled actin networks. Point mutations in the actin binding domain of those ABPs can tune the association and dissociation dynamics of the actin/ABP bond and thus modulate the network mechanics both in the linear and non-linear response regime. We here demonstrate how the exchange of a single charged amino acid in the actin binding domain of the ABP fascin triggers such a modulation of the network rheology. Whereas the overall structure of the bundle networks is conserved, the transition point from strain-hardening to strain-weakening sensitively depends on the cross-linker off-rate and the applied shear rate. Our experimental results are consistent both with numerical simulations of a cross-linked bundle network and a theoretical description of the bundle network mechanics which is based on non-affine bending deformations and force-dependent cross-link dynamics.

  10. 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....

  11. 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.

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

    Science.gov (United States)

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

    2018-06-01

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

  13. 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

  14. 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....

  15. 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

    A novel 3D network single-phase Ni0.9Zn0.1O has been designed and synthesized by calcining a special metal-organic precursor (MOP) (MeO2C3H6, Me=Ni and Zn, the molar ratio of Ni: Zn=9:1) as the self-sacrificing template for the first time. Comparing with NiO or the mixture of NiO and ZnO, the new...

  16. A NOVEL PIPELINE FOR DRUG DISCOVERY IN NEUROPSYCHIATRIC DISORDERS USING HIGH-CONTENT SINGLE-CELL SCREENING OF SIGNALLING NETWORK RESPONSES EX VIVO

    OpenAIRE

    Lago Cooke, Santiago Guillermo

    2016-01-01

    The current work entails the development of a novel high content platform for the measurement of kinetic ligand responses across cell signalling networks at the single-cell level in distinct PBMC subtypes ex vivo. Using automated sample preparation, fluorescent cellular barcoding and flow cytometry the platform is capable of detecting 21, 840 parallel cell signalling responses in each PBMC sample. We apply this platform to characterize the effects of neuropsychiatric treatments and CNS ligand...

  17. An absorptive single-pole four-throw switch using multiple-contact MEMS switches and its application to a monolithic millimeter-wave beam-forming network

    International Nuclear Information System (INIS)

    Lee, Sanghyo; Kim, Jong-Man; Kim, Yong-Kweon; Kwon, Youngwoo

    2009-01-01

    In this paper, a new absorptive single-pole four-throw (SP4T) switch based on multiple-contact switching is proposed and integrated with a Butler matrix to demonstrate a monolithic beam-forming network at millimeter waves (mm waves). In order to simplify the switching driving circuit and reduce the number of unit switches in an absorptive SP4T switch, the individual switches were replaced with long-span multiple-contact switches using stress-free single-crystalline-silicon MEMS technology. This approach improves the mechanical stability as well as the manufacturing yield, thereby allowing successful integration into a monolithic beam former. The fabricated absorptive SP4T MEMS switch shows insertion loss less than 1.3 dB, return losses better than 11 dB at 30 GHz and wideband isolation performance higher than 39 dB from 20 to 40 GHz. The absorptive SP4T MEMS switch is integrated with a 4 × 4 Butler matrix on a single chip to implement a monolithic beam-forming network, directing beam into four distinct angles. Array factors from the measured data show that the proposed absorptive SPnT MEMS switch can be effectively used for high-performance mm-wave beam-switching systems. This work corresponds to the first demonstration of a monolithic beam-forming network using switched beams

  18. 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.

  19. 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.

  20. 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......-capacity transmission, because inter-core crosstalk (XT) could be the main limiting factor for MCF transmission. In a real MCF network, the inter-core XT in a particular core is likely to change continuously as the optical paths in the adjacent cores are dynamically assigned to match the dynamic nature of the data...

  1. 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

  2. Capacity upgrade in short-reach optical fibre networks: simultaneous 4-PAM 20 Gbps data and polarization-modulated PPS clock signal using a single VCSEL carrier

    Science.gov (United States)

    Isoe, G. M.; Wassin, S.; Gamatham, R. R. G.; Leitch, A. W. R.; Gibbon, T. B.

    2017-11-01

    In this work, a four-level pulse amplitude modulation (4-PAM) format with a polarization-modulated pulse per second (PPS) clock signal using a single vertical cavity surface emitting laser (VCSEL) carrier is for the first time experimentally demonstrated. We propose uncomplex alternative technique for increasing capacity and flexibility in short-reach optical communication links through multi-signal modulation onto a single VCSEL carrier. A 20 Gbps 4-PAM data signal is directly modulated onto a single mode 10 GHz bandwidth VCSEL carrier at 1310 nm, therefore, doubling the network bit rate. Carrier spectral efficiency is further maximized by exploiting the inherent orthogonal polarization switching of the VCSEL carrier with changing bias in transmission of a PPS clock signal. We, therefore, simultaneously transmit a 20 Gbps 4-PAM data signal and a polarization-based PPS clock signal using a single VCSEL carrier. It is the first time a signal VCSEL carrier is reported to simultaneously transmit a directly modulated 20 Gbps 4-PAM data signal and a polarization-based PPS clock signal. We further demonstrate on the design of a software-defined digital signal processing (DSP)-assisted receiver as an alternative to costly receiver hardware. Experimental results show that a 3.21 km fibre transmission with simultaneous 20 Gbps 4-PAM data signal and polarization-based PPS clock signal introduced a penalty of 3.76 dB. The contribution of polarization-based PPS clock signal to this penalty was found out to be 0.41 dB. Simultaneous distribution of data and timing clock signals over shared network infrastructure significantly increases the aggregated data rate at different optical network units (ONUs), without costly investment.

  3. 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

  4. 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.

  5. Well-Constructed Single-Layer Molybdenum Disulfide Nanorose Cross-Linked by Three Dimensional-Reduced Graphene Oxide Network for Superior Water Splitting and Lithium Storage Property

    Science.gov (United States)

    Zhao, Yanyan; Kuai, Long; Liu, Yanguo; Wang, Pengpeng; Arandiyan, Hamidreza; Cao, Sufeng; Zhang, Jie; Li, Fengyun; Wang, Qing; Geng, Baoyou; Sun, Hongyu

    2015-01-01

    A facile one-step solution reaction route for growth of novel MoS2 nanorose cross-linked by 3D rGO network, in which the MoS2 nanorose is constructed by single-layered or few-layered MoS2 nanosheets, is presented. Due to the 3D assembled hierarchical architecture of the ultrathin MoS2 nanosheets and the interconnection of 3D rGO network, as well as the synergetic effects of MoS2 and rGO, the as-prepared MoS2-NR/rGO nanohybrids delivered high specific capacity, excellent cycling and good rate performance when evaluated as an anode material for lithium-ion batteries. Moreover, the nanohybrids also show excellent hydrogen-evolution catalytic activity and durability in an acidic medium, which is superior to MoS2 nanorose and their nanoparticles counterparts. PMID:25735416

  6. 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.

  7. 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

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

    International Nuclear Information System (INIS)

    Sun, Xiao-Guang; Kerr, John B.

    2004-01-01

    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 6 O 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 -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 6 O 13 full cell constructed using a single ion conductor gel (propylene carbonate (PC)/EMC, 1/1 in

  9. 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...

  10. Mobilities in ambipolar field effect transistors based on single-walled carbon nanotube network and formed on a gold nanoparticle template

    Energy Technology Data Exchange (ETDEWEB)

    Wongsaeng, Chalao [Department of Science, Faculty of Sciences and Agricultural Technology, Rajamangala University of Technology Lanna Tak, Tak 63000 (Thailand); Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Singjai, Pisith, E-mail: pisith.s@cmu.ac.th [Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand)

    2014-04-07

    Ambipolar field effect transistors based on a single-walled carbon nanotube (SWNT) network formed on a gold nanoparticle (AuNP) template with polyvinyl alcohol as a gate insulator were studied by measuring the current–gate voltage characteristics. It was found that the mobilities of holes and electrons increased with increasing AuNP number density. The disturbances in the flow pattern of the carbon feedstock in the chemical vapor deposition growth that were produced by the AuNP geometry, resulted in the differences in the crystallinity and the diameter, as well as the changes in the degree of the semiconductor behavior of the SWNTs.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. Percolation of interdependent network of networks

    International Nuclear Information System (INIS)

    Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

    2015-01-01

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

  17. 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

  18. 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.

  19. Automatic sleep stage classification of single-channel EEG by using complex-valued convolutional neural network.

    Science.gov (United States)

    Zhang, Junming; Wu, Yan

    2018-03-28

    Many systems are developed for automatic sleep stage classification. However, nearly all models are based on handcrafted features. Because of the large feature space, there are so many features that feature selection should be used. Meanwhile, designing handcrafted features is a difficult and time-consuming task because the feature designing needs domain knowledge of experienced experts. Results vary when different sets of features are chosen to identify sleep stages. Additionally, many features that we may be unaware of exist. However, these features may be important for sleep stage classification. Therefore, a new sleep stage classification system, which is based on the complex-valued convolutional neural network (CCNN), is proposed in this study. Unlike the existing sleep stage methods, our method can automatically extract features from raw electroencephalography data and then classify sleep stage based on the learned features. Additionally, we also prove that the decision boundaries for the real and imaginary parts of a complex-valued convolutional neuron intersect orthogonally. The classification performances of handcrafted features are compared with those of learned features via CCNN. Experimental results show that the proposed method is comparable to the existing methods. CCNN obtains a better classification performance and considerably faster convergence speed than convolutional neural network. Experimental results also show that the proposed method is a useful decision-support tool for automatic sleep stage classification.

  20. 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.

  1. 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.

  2. 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

  3. Multiple network interface core apparatus and method

    Science.gov (United States)

    Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

    2011-04-26

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

  4. 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. PMID:27174582

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

    Energy Technology Data Exchange (ETDEWEB)

    Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it [Scientific Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan (Italy); Center for Mind/Brain Sciences, University of Trento, Trento (Italy); Chiesa, Pietro; Tabarelli, Davide; Jovicich, Jorge [Center for Mind/Brain Sciences, University of Trento, Trento (Italy); D' Incerti, Ludovico [Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan (Italy)

    2015-03-15

    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{sub 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Implementation of a Single-Phase SST for the Interface between a 13.2 kV MVAC Network and a 750 V Bipolar DC Distribution

    Directory of Open Access Journals (Sweden)

    Hyeok-Jin Yun

    2018-05-01

    Full Text Available This paper presents the implementation of a single-phase solid-state transformer (SST for the interface between a 13.2 kV medium voltage alternative current (MVAC network and a 750 V bipolar DC distribution. The SST has ten cascaded subunits in consideration of the device rating and modulation index (MI. Each subunit consists of an AC/DC stage and a DC/DC stage with a high frequency isolated transformer (HFIT. The AC/DC stage consists of cascaded H-bridges (CHBs to cope with the MVAC. The DC/DC stage employs a triple active bridge (TAB converter for bipolar DC distribution. Topology analysis and controller design for this specific structure are discussed. In addition, the insulation of HFIT used in DC/DC converters is also discussed. A simple balancing controller at the AC/DC stage and a current sharing controller at the DC/DC stage are used to prevent DC-link voltage unbalance caused by the cascaded structure. The discussions are validated using a 150 kW single-phase 21-level SST prototype at the laboratory level.

  11. Simultaneous 10 Gbps data and polarization-based pulse-per-second clock transmission using a single VCSEL for high-speed optical fibre access networks

    Science.gov (United States)

    Isoe, G. M.; Wassin, S.; Gamatham, R. R. G.; Leitch, A. W. R.; Gibbon, T. B.

    2017-01-01

    Access networks based on vertical cavity surface emitting laser (VCSEL) transmitters offer alternative solution in delivering different high bandwidth, cost effective services to the customer premises. Clock and reference frequency distribution is critical for applications such as Coordinated Universal Time (UTC), GPS, banking and big data science projects. Simultaneous distribution of both data and timing signals over shared infrastructure is thus desirable. In this paper, we propose and experimentally demonstrate a novel, cost-effective technique for multi-signal modulation on a single VCSEL transmitter. Two signal types, an intensity modulated 10 Gbps data signal and a polarization-based pulse per second (PPS) clock signal are directly modulated onto a single VCSEL carrier at 1310 nm. Spectral efficiency is maximized by exploiting inherent orthogonal polarization switching of the VCSEL with changing bias in transmission of the PPS signal. A 10 Gbps VCSEL transmission with PPS over 11 km of G.652 fibre introduced a transmission penalty of 0.52 dB. The contribution of PPS to this penalty was found to be 0.08 dB.

  12. 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.

  13. 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.

  14. 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.

  15. The Optimal Timing of Stage 2 Palliation for Hypoplastic Left Heart Syndrome: An Analysis of the Pediatric Heart Network Single Ventricle Reconstruction Trial Public Data Set.

    Science.gov (United States)

    Meza, James M; Hickey, Edward J; Blackstone, Eugene H; Jaquiss, Robert D B; Anderson, Brett R; Williams, William G; Cai, Sally; Van Arsdell, Glen S; Karamlou, Tara; McCrindle, Brian W

    2017-10-31

    In infants requiring 3-stage single-ventricle palliation for hypoplastic left heart syndrome, attrition after the Norwood procedure remains significant. The effect of the timing of stage 2 palliation (S2P), a physician-modifiable factor, on long-term survival is not well understood. We hypothesized that an optimal interval between the Norwood and S2P that both minimizes pre-S2P attrition and maximizes post-S2P survival exists and is associated with individual patient characteristics. The National Institutes of Health/National Heart, Lung, and Blood Institute Pediatric Heart Network Single Ventricle Reconstruction Trial public data set was used. Transplant-free survival (TFS) was modeled from (1) Norwood to S2P and (2) S2P to 3 years by using parametric hazard analysis. Factors associated with death or heart transplantation were determined for each interval. To account for staged procedures, risk-adjusted, 3-year, post-Norwood TFS (the probability of TFS at 3 years given survival to S2P) was calculated using parametric conditional survival analysis. TFS from the Norwood to S2P was first predicted. TFS after S2P to 3 years was then predicted and adjusted for attrition before S2P by multiplying by the estimate of TFS to S2P. The optimal timing of S2P was determined by generating nomograms of risk-adjusted, 3-year, post-Norwood, TFS versus the interval from the Norwood to S2P. Of 547 included patients, 399 survived to S2P (73%). Of the survivors to S2P, 349 (87%) survived to 3-year follow-up. The median interval from the Norwood to S2P was 5.1 (interquartile range, 4.1-6.0) months. The risk-adjusted, 3-year, TFS was 68±7%. A Norwood-S2P interval of 3 to 6 months was associated with greatest 3-year TFS overall and in patients with few risk factors. In patients with multiple risk factors, TFS was severely compromised, regardless of the timing of S2P and most severely when S2P was performed early. No difference in the optimal timing of S2P existed when stratified by

  16. A New Anode for Lithium-Ion Batteries Based on Single-Walled Carbon Nanotubes and Graphene: Improved Performance through a Binary Network Design.

    Science.gov (United States)

    Ren, Jing; Ren, Rui-Peng; Lv, Yong-Kang

    2018-05-04

    Carbon nanomaterials, especially graphene and carbon nanotubes, are considered to be favorable alternatives to graphite-based anodes in lithium-ion batteries, owing to their high specific surface area, electrical conductivity, and excellent mechanical flexibility. However, the limited number of storage sites for lithium ions within the sp 2 -carbon hexahedrons leads to the low storage capacity. Thus, rational structure design is essential for the preparation of high-performance carbon-based anode materials. Herein, we employed flexible single-walled carbon nanotubes (SWCNTs) with ultrahigh electrical conductivity as a wrapper for 3D graphene foam (GF) by using a facile dip-coating process to form a binary network structure. This structure, which offered high electrical conductivity, enlarged the electrode/electrolyte contact area, shortened the electron-/ion-transport pathways, and allowed for efficient utilization of the active material, which led to improved electrochemical performance. When used as an anode in lithium-ion batteries, the SWCNT-GF electrode delivered a specific capacity of 953 mA h g -1 at a current density of 0.1 A g -1 and a high reversible capacity of 606 mA h g -1 after 1000 cycles, with a capacity retention of 90 % over 1000 cycles at 1 A g -1 and 189 mA h g -1 after 2200 cycles at 5 A g -1 . © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Comparison of echocardiographic and cardiac magnetic resonance imaging measurements of functional single ventricular volumes, mass, and ejection fraction (from the Pediatric Heart Network Fontan Cross-Sectional Study).

    Science.gov (United States)

    Margossian, Renee; Schwartz, Marcy L; Prakash, Ashwin; Wruck, Lisa; Colan, Steven D; Atz, Andrew M; Bradley, Timothy J; Fogel, Mark A; Hurwitz, Lynne M; Marcus, Edward; Powell, Andrew J; Printz, Beth F; Puchalski, Michael D; Rychik, Jack; Shirali, Girish; Williams, Richard; Yoo, Shi-Joon; Geva, Tal

    2009-08-01

    Assessment of the size and function of a functional single ventricle (FSV) is a key element in the management of patients after the Fontan procedure. Measurement variability of ventricular mass, volume, and ejection fraction (EF) among observers by echocardiography and cardiac magnetic resonance imaging (CMR) and their reproducibility among readers in these patients have not been described. From the 546 patients enrolled in the Pediatric Heart Network Fontan Cross-Sectional Study (mean age 11.9 +/- 3.4 years), 100 echocardiograms and 50 CMR studies were assessed for measurement reproducibility; 124 subjects with paired studies were selected for comparison between modalities. Interobserver agreement for qualitative grading of ventricular function by echocardiography was modest for left ventricular (LV) morphology (kappa = 0.42) and weak for right ventricular (RV) morphology (kappa = 0.12). For quantitative assessment, high intraclass correlation coefficients were found for echocardiographic interobserver agreement (LV 0.87 to 0.92, RV 0.82 to 0.85) of systolic and diastolic volumes, respectively. In contrast, intraclass correlation coefficients for LV and RV mass were moderate (LV 0.78, RV 0.72). The corresponding intraclass correlation coefficients by CMR were high (LV 0.96, RV 0.85). Volumes by echocardiography averaged 70% of CMR values. Interobserver reproducibility for the EF was similar for the 2 modalities. Although the absolute mean difference between modalities for the EF was small (<2%), 95% limits of agreement were wide. In conclusion, agreement between observers of qualitative FSV function by echocardiography is modest. Measurements of FSV volume by 2-dimensional echocardiography underestimate CMR measurements, but their reproducibility is high. Echocardiographic and CMR measurements of FSV EF demonstrate similar interobserver reproducibility, whereas measurements of FSV mass and LV diastolic volume are more reproducible by CMR.

  18. On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.

    Science.gov (United States)

    Pläschke, Rachel N; Cieslik, Edna C; Müller, Veronika I; Hoffstaedter, Felix; Plachti, Anna; Varikuti, Deepthi P; Goosses, Mareike; Latz, Anne; Caspers, Svenja; Jockwitz, Christiane; Moebus, Susanne; Gruber, Oliver; Eickhoff, Claudia R; Reetz, Kathrin; Heller, Julia; Südmeyer, Martin; Mathys, Christian; Caspers, Julian; Grefkes, Christian; Kalenscher, Tobias; Langner, Robert; Eickhoff, Simon B

    2017-12-01

    Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc. © 2017

  19. 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 ...

  20. 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.

  1. Network University of the CIS as a tool for development of academic mobility within a single (unified educational space of the CIS member states

    Directory of Open Access Journals (Sweden)

    Гульнара Амангельдиновна Краснова

    2010-03-01

    Full Text Available The article presents the results of the project «Establishment of a network University of the CIS (2008-2010 years» realization, aimed to establish a joint master's programs in the commonwealth, to strengthen international cooperation in the training of highly qualified specialists, specified tasks to further its implementation in 2010.

  2. 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

  3. 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

  4. 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

  5. A π-π 3D network of tetranuclear μ2/μ3-carbonato Dy(III) bis-pyrazolylpyridine clusters showing single molecule magnetism features.

    Science.gov (United States)

    Gass, Ian A; Moubaraki, Boujemaa; Langley, Stuart K; Batten, Stuart R; Murray, Keith S

    2012-02-18

    2,6-Di(pyrazole-3-yl)pyridine, 3-bpp, forms a porous (4(9)·6(6)) π-π mediated 3D network of trigonal pyramidal [Dy(III)(4)] carbonato-bridged complexes, with hexagonal channels comprising 54% of the unit cell volume, the material displaying slow magnetisation reversal. This journal is © The Royal Society of Chemistry 2012

  6. A method of increasing the sensitivity of protection from single-phase short-circuits to ground in the 6 – 10 kV network

    International Nuclear Information System (INIS)

    Manilov, A. M.; Mel’nik, D. A.

    2012-01-01

    A method of increasing the sensitivity of protection from single-phase short-circuits to ground by acting on the signal with brief dummy grounding of the neutral is described. After determining the damage, the neutral is again grounded through a high resistance and an arc-quenching reactor. An increase in the protection sensitivity is thereby obtained, the damage detection time is shortened, and the probability of the single-phase short-circuit to ground converting into double and multipoint earth faults is reduced.

  7. 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...... cooperating with the plurality of user equipment to decode the received data....

  8. 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

  9. 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.

  10. 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.

  11. Recent advances on failure and recovery in networks of networks

    International Nuclear Information System (INIS)

    Shekhtman, Louis M.; Danziger, Michael M.; Havlin, Shlomo

    2016-01-01

    Until recently, network science has focused on the properties of single isolated networks that do not interact or depend on other networks. However it has now been recognized that many real-networks, such as power grids, transportation systems, and communication infrastructures interact and depend on other networks. Here, we will present a review of the framework developed in recent years for studying the vulnerability and recovery of networks composed of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes, like for example certain people, play a role in two networks, i.e. in a multiplex. Dependency relations may act recursively and can lead to cascades of failures concluding in sudden fragmentation of the system. We review the analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. The general theory and behavior of interdependent networks has many novel features that are not present in classical network theory. Interdependent networks embedded in space are significantly more vulnerable compared to non-embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences. Finally, when recovery of components is possible, global spontaneous recovery of the networks and hysteresis phenomena occur. The theory developed for this process points to an optimal repairing strategy for a network of networks. Understanding realistic effects present in networks of networks is required in order to move towards determining system vulnerability.

  12. 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...

  13. 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

  14. 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

    Directory of Open Access Journals (Sweden)

    Chenzhong Shao

    2018-01-01

    Full Text Available 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.

  15. Monitoring Churn in Wireless Networks

    Science.gov (United States)

    Holzer, Stephan; Pignolet, Yvonne Anne; Smula, Jasmin; Wattenhofer, Roger

    Wireless networks often experience a significant amount of churn, the arrival and departure of nodes. In this paper we propose a distributed algorithm for single-hop networks that detects churn and is resilient to a worst-case adversary. The nodes of the network are notified about changes quickly, in asymptotically optimal time up to an additive logarithmic overhead. We establish a trade-off between saving energy and minimizing the delay until notification for single- and multi-channel networks.

  16. 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.

  17. Vulnerability and controllability of networks of networks

    International Nuclear Information System (INIS)

    Liu, Xueming; Peng, Hao; Gao, Jianxi

    2015-01-01

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

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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)

  3. Multilayer Social Networks

    DEFF Research Database (Denmark)

    Dickison, Mark; Magnani, Matteo; Rossi, Luca

    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...

  4. Competing Transport Networks

    NARCIS (Netherlands)

    M.J. van der Leij (Marco)

    2003-01-01

    textabstractIn a circular city model, I consider network design and pricing decisions for a single fast transport connection that faces competition from a slower but better accessible transport mode. To access the fast transport network individuals have to make complementary trips by slow mode. This

  5. Cascading Failures and Recovery in Networks of Networks

    Science.gov (United States)

    Havlin, Shlomo

    Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.

  6. Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players

    Science.gov (United States)

    Murugesan, Gowtham; Saghafi, Behrouz; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alex; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

    2018-02-01

    The effect of repetitive sub-concussive head impact exposure in contact sports like American football on brain health is poorly understood, especially in the understudied populations of youth and high school players. These players, aged 9-18 years old may be particularly susceptible to impact exposure as their brains are undergoing rapid maturation. This study helps fill the void by quantifying the association between head impact exposure and functional connectivity, an important aspect of brain health measurable via resting-state fMRI (rs-fMRI). The contributions of this paper are three fold. First, the data from two separate studies (youth and high school) are combined to form a high-powered analysis with 60 players. These players experience head acceleration within overlapping impact exposure making their combination particularly appropriate. Second, multiple features are extracted from rs-fMRI and tested for their association with impact exposure. One type of feature is the power spectral density decomposition of intrinsic, spatially distributed networks extracted via independent components analysis (ICA). Another feature type is the functional connectivity between brain regions known often associated with mild traumatic brain injury (mTBI). Third, multiple supervised machine learning algorithms are evaluated for their stability and predictive accuracy in a low bias, nested cross-validation modeling framework. Each classifier predicts whether a player sustained low or high levels of head impact exposure. The nested cross validation reveals similarly high classification performance across the feature types, and the Support Vector, Extremely randomized trees, and Gradboost classifiers achieve F1-score up to 75%.

  7. Networks in the news media

    DEFF Research Database (Denmark)

    Bro, Peter

    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......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...

  8. Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks

    Science.gov (United States)

    Saghafi, Behrouz; Murugesan, Gowtham; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alexander; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

    2018-02-01

    The effect of subconcussive head impact exposure during contact sports, including American football, on brain health is poorly understood particularly in young and adolescent players, who may be more vulnerable to brain injury during periods of rapid brain maturation. This study aims to quantify the association between cumulative effects of head impact exposure from a single season of football on white matter (WM) integrity as measured with diffusion MRI. The study targets football players aged 9-18 years old. All players were imaged pre- and post-season with structural MRI and diffusion tensor MRI (DTI). Fractional Anisotropy (FA) maps, shown to be closely correlated with WM integrity, were computed for each subject, co-registered and subtracted to compute the change in FA per subject. Biomechanical metrics were collected at every practice and game using helmet mounted accelerometers. Each head impact was converted into a risk of concussion, and the risk of concussion-weighted cumulative exposure (RWE) was computed for each player for the season. Athletes with high and low RWE were selected for a two-category classification task. This task was addressed by developing a 3D Convolutional Neural Network (CNN) to automatically classify players into high and low impact exposure groups from the change in FA maps. Using the proposed model, high classification performance, including ROC Area Under Curve score of 85.71% and F1 score of 83.33% was achieved. This work adds to the growing body of evidence for the presence of detectable neuroimaging brain changes in white matter integrity from a single season of contact sports play, even in the absence of a clinically diagnosed concussion.

  9. 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...

  10. NASA Integrated Network COOP

    Science.gov (United States)

    Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

    2012-01-01

    Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

  11. マルチユース可能な教育用計算機システムの構築と運用

    OpenAIRE

    堀内, 泰輔; 堀内, 征治; 岡田, 学

    1994-01-01

    In the area of information processing education, there are so many problems when we select new compter system. Because there are many operating system, computer system including network archtecture, program language to educate, etc. We selected new computer system in this March by condsideration with part of computer center in the new age. As a result, we chose complex system includes 2 work-stations, 48 personal computers and computer network. In this paper, we introduce construction and app...

  12. 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

  13. Centrality in earthquake multiplex networks

    Science.gov (United States)

    Lotfi, Nastaran; Darooneh, Amir Hossein; Rodrigues, Francisco A.

    2018-06-01

    Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a temporal network, described by a multiplex network, and characterize the evolution of the network structure in terms of the eigenvector centrality measure. We generalize previous works that considered the single layer representation of earthquake networks. Our results suggest that the multiplex representation captures better earthquake activity than methods based on single layer networks. We also verify that the regions with highest seismological activities in Iran and California can be identified from the network centrality analysis. The temporal modeling of seismic data provided here may open new possibilities for a better comprehension of the physics of earthquakes.

  14. single crystals

    Indian Academy of Sciences (India)

    2018-05-18

    May 18, 2018 ... Abstract. 4-Nitrobenzoic acid (4-NBA) single crystals were studied for their linear and nonlinear optical ... studies on the proper growth, linear and nonlinear optical ..... between the optic axes and optic sign of the biaxial crystal.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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......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 this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  20. 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...

  1. 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.

  2. 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...

  3. [Network structures in biological systems].

    Science.gov (United States)

    Oleskin, A V

    2013-01-01

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

  4. 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

  5. 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

    International Nuclear Information System (INIS)

    Su, K; Kuo, J; Hu, L; Traughber, M; Pereira, G; Traughber, B; Herrmann, K; Muzic, R

    2015-01-01

    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

  6. 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.

  7. 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

  8. 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.

  9. Singled out?

    Science.gov (United States)

    Waller, Frank

    2004-03-01

    The increasing use of single use medical devices is being driven by a growing awareness of iatrogenic (from the Greek; caused by the doctor) and nosocomial infections. Public health perceptions relating to transmissible spongiform encephalopathies, specifically variant Creutzfeldt-Jakob disease (vCJD), the Human Immunodeficiency Virus (HIV) and Hepatitis B are high on the political agenda and a matter of concern to healthcare professionals.

  10. 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

  11. 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...

  12. 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.

  13. Temporal networks

    CERN Document Server

    Saramäki, Jari

    2013-01-01

    The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach  the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and concept...

  14. 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.

  15. 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.

  16. Epidemics in interconnected small-world networks

    NARCIS (Netherlands)

    Liu, M.; Li, D.; Qin, P.; Liu, C.; Wang, H.; Wang, F.

    2015-01-01

    Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks

  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 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....... These include student relations and interactions and epistemic and linguistic networks of words, concepts and actions. Network methodology has already found use in science education research. However, while networks hold the potential for new insights, they have not yet found wide use in the science education...... 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...

  2. Network Convergence

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Network Convergence. User is interested in application and content - not technical means of distribution. Boundaries between distribution channels fade out. Network convergence leads to seamless application and content solutions.

  3. Industrial Networks

    DEFF Research Database (Denmark)

    Karlsson, Christer

    2015-01-01

    Companies organize in a way that involves many activities that are external to the traditional organizational boundaries. This presents challenges to operations management and managing operations involves many issues and actions dealing with external networks. Taking a network perspective changes...

  4. 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...

  5. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

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

    2015-01-01

    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....... This paper advocates for the use of SDN to bring about future Internet and 5G network services by incorporating network coding (NC) functionalities. The inherent flexibility of both SDN and NC provides a fertile ground to envision more efficient, robust, and secure networking designs, that may also...

  6. 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

  7. 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.

  8. The DARPA quantum network

    International Nuclear Information System (INIS)

    Elliot, B.

    2005-01-01

    Full text: The DARPA quantum network is now in initial operational, with six nodes performing quantum cryptography 24x7 across the Boston metro area between our campuses at Harvard University, Boston University, and BBN Technologies. In this talk, we present our recent activities, including the deployment of this network, building our Mark 1 Entangled QKD system, porting BBN QKD protocol software to NIST and Qinetiq freespace systems, performing initial design of a superconducting single photon detector with U. Rochester and NIST Boulder, and implementing a novel Low-Density Parity Check (LDPC) protocol for QKD. (author)

  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. Spatial networks

    Science.gov (United States)

    Barthélemy, Marc

    2011-02-01

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

  11. 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...

  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. 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...

  14. 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...

  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. 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,...

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

    Science.gov (United States)

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

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

  18. 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...

  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. Stages of neuronal network formation

    International Nuclear Information System (INIS)

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

    2013-01-01

    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. (paper)

  2. Measurement methods on the complexity of network

    Institute of Scientific and Technical Information of China (English)

    LIN Lin; DING Gang; CHEN Guo-song

    2010-01-01

    Based on the size of network and the number of paths in the network,we proposed a model of topology complexity of a network to measure the topology complexity of the network.Based on the analyses of the effects of the number of the equipment,the types of equipment and the processing time of the node on the complexity of the network with the equipment-constrained,a complexity model of equipment-constrained network was constructed to measure the integrated complexity of the equipment-constrained network.The algorithms for the two models were also developed.An automatic generator of the random single label network was developed to test the models.The results show that the models can correctly evaluate the topology complexity and the integrated complexity of the networks.

  3. Networked Identities

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Larsen, Malene Charlotte

    2008-01-01

    of CoPs we shall argue that the metaphor or theory of networked learning is itself confronted with some central tensions and challenges that need to be addressed. We then explore these theoretical and analytic challenges to the network metaphor, through an analysis of a Danish social networking site. We......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...... argue that understanding meaning-making and ‘networked identities’ may be relevant analytic entry points in navigating the challenges....

  4. A perspective from Europe on in-home networking

    NARCIS (Netherlands)

    Koonen, A.M.J.; Shi, Y.; Tran, N.C.; Okonkwo, C.M.; Boom, van den H.P.A.; Tangdiongga, E.

    2012-01-01

    Delivery of wirebound and wireless services can be integrated in a single cost-efficient in-home POF network, when using advanced signal modulation techniques. In larger buildings, dynamic capacity allocation by wavelength routing improves the network performance.

  5. 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

  6. Deep hierarchical attention network for video description

    Science.gov (United States)

    Li, Shuohao; Tang, Min; Zhang, Jun

    2018-03-01

    Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

  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. 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

  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. Wireless Sensor Network Localization Research

    OpenAIRE

    Liang Xin

    2014-01-01

    DV-Hop algorithm is one of the important range-free localization algorithms. It performs better in isotropic density senor networks, however, it brings larger location errors in random distributed networks. According to the localization principle of the DV-Hop algorithm, this paper improves the estimation of average single hop distance by using the Least Equal Square Error, and revises the estimated distance between the unknown node and the anchor node with compensation coefficient considerin...

  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. Analysis of interference performance of tactical radio network

    Science.gov (United States)

    Nie, Hao; Cai, Xiaoxia; Chen, Hong

    2017-08-01

    Mobile Ad hoc network has a strong military background for its development as the core technology of the backbone network of US tactical Internet. And which tactical radio network, is the war in today's tactical use of the Internet more mature form of networking, mainly used in brigade and brigade following forces. This paper analyzes the typical protocol AODV in the tactical radio network, and then carries on the networking. By adding the interference device to the whole network, the battlefield environment is simulated, and then the throughput, delay and packet loss rate are analyzed, and the performance of the whole network and the single node before and after the interference is obtained.

  14. 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

  15. 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....

  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. Temporal networks

    Science.gov (United States)

    Holme, Petter; Saramäki, Jari

    2012-10-01

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

  18. Resilience of networks formed of interdependent modular networks

    Science.gov (United States)

    Shekhtman, Louis M.; Shai, Saray; Havlin, Shlomo

    2015-12-01

    Many infrastructure networks have a modular structure and are also interdependent with other infrastructures. While significant research has explored the resilience of interdependent networks, there has been no analysis of the effects of modularity. Here we develop a theoretical framework for attacks on interdependent modular networks and support our results through simulations. We focus, for simplicity, on the case where each network has the same number of communities and the dependency links are restricted to be between pairs of communities of different networks. This is particularly realistic for modeling infrastructure across cities. Each city has its own infrastructures and different infrastructures are dependent only within the city. However, each infrastructure is connected within and between cities. For example, a power grid will connect many cities as will a communication network, yet a power station and communication tower that are interdependent will likely be in the same city. It has previously been shown that single networks are very susceptible to the failure of the interconnected nodes (between communities) (Shai et al 2014 arXiv:1404.4748) and that attacks on these nodes are even more crippling than attacks based on betweenness (da Cunha et al 2015 arXiv:1502.00353). In our example of cities these nodes have long range links which are more likely to fail. For both treelike and looplike interdependent modular networks we find distinct regimes depending on the number of modules, m. (i) In the case where there are fewer modules with strong intraconnections, the system first separates into modules in an abrupt first-order transition and then each module undergoes a second percolation transition. (ii) When there are more modules with many interconnections between them, the system undergoes a single transition. Overall, we find that modular structure can significantly influence the type of transitions observed in interdependent networks and should be

  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. Network chemistry, network toxicology, network informatics, and network behavioristics: A scientific outline

    OpenAIRE

    WenJun Zhang

    2016-01-01

    In present study, I proposed some new sciences: network chemistry, network toxicology, network informatics, and network behavioristics. The aims, scope and scientific foundation of these sciences are outlined.

  1. 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 ...

  2. 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.

  3. 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.

  4. The future of network governance research

    DEFF Research Database (Denmark)

    Lewis, Jenny

    2011-01-01

    that comprises it. The main theoretical and empirical approaches that have been used to guide it to date are then briefly described, emphasizing recent debates about interpretivism and decentring. Next, it suggests that a robust and interesting future for network governance requires diversity, rather than...... adherence to a single approach. It is argued that more sophisticated approaches for examining network governance are fashioned through a synthesis of ideas and methods to create an analysis of networks as networks. This is especially the case where some formal analysis of network structure is used...

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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...

  11. Heterodox networks

    DEFF Research Database (Denmark)

    Lala, Purnima; Kumar, Ambuj

    2016-01-01

    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......)’ have not been considered much in the literature. In this article we present Heterodox networks as an innovative and alternate approach to handle the PTC congestion. We describe two different approaches to combat the PTC congestion where the traditional terrestrial infrastructure fails to provide......-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...

  12. Networking Japan

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    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...... HIDA). Many of these alumni have and will in the future exchange ideas and keep contact not only to Japan, but also to fellow alumni around the globe and, thereby, practice south-south exchanges, which are made possible and traceable by their established alumni network and the World Network of Friends...

  13. Sentinel Network

    Science.gov (United States)

    The Sentinel Network is an integrated, electronic, national medical product safety initiative that compiles information about the safe and effective use of medical products accessible to patients and healthcare practitioners.

  14. Exchange Network

    Science.gov (United States)

    The Environmental Information Exchange Network (EN) is an Internet-based system used by state, tribal and territorial partners to securely share environmental and health information with one another and EPA.

  15. Diversity Networks

    Science.gov (United States)

    and professional growth of women through networking, mentoring and training. We strive to ensure that will be used. National Processing Center Seniors Leader: Jo Anne Hankins Champion: Eric Milliner NO

  16. Nepal Networking

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    , as a Danida fellow. Today, the older sister works in Nepal and the younger in Seattle, where they still make use of their personal networks including connections to their fellow alumni of technical assistance courses. Inspired by work on social remittances in combination with network theory , I argue......Technical Assistance courses have many functions apart from disseminating knowledge and information, one such function is to engender networks. During the course period, participants meet and establish contact and some of these contacts remain connections between alumni for many years after...... the courses are finished. The alumni networks depend on the uses they are put to by the individual alumni and the support they get from alumni and host countries. The United Nations initiated technical assistance courses in the late 1940s in order to train nationals from developing countries as a means...

  17. 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.

  18. 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

  19. 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...

  20. 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....

  1. 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...

  2. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Lipshtat, A.; Biham, O.

    2004-01-01

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  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. ExScal Backbone Network Architecture

    Science.gov (United States)

    2005-01-01

    802.11 battery powered nodes was laid over the sensor network. We adopted the Stargate platform for the backbone tier to serve as the basis for...its head. XSS Hardware and Network: XSS stands for eXtreme Scaling Stargate . A stargate is a linux-based single board computer. It has a 400 MHz

  5. 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

  6. 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...

  7. Mobility management in the future mobile network

    NARCIS (Netherlands)

    Karimzadeh Motallebi Azar, Morteza

    2018-01-01

    The current mobile network architectures are heavily hierarchical, which implies that all traffic must be traversed through a centralized core entity. This makes the network prone to several limitations, e.g., suboptimal communication paths, low scalability, signaling overhead, and single point of

  8. 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).

  9. Basketball Teams as Strategic Networks

    Science.gov (United States)

    Fewell, Jennifer H.; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S.

    2012-01-01

    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. PMID:23139744

  10. Basketball teams as strategic networks.

    Science.gov (United States)

    Fewell, Jennifer H; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S

    2012-01-01

    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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Identifying influential spreaders in interconnected networks

    International Nuclear Information System (INIS)

    Zhao, Dawei; Li, Lixiang; Huo, Yujia; Yang, Yixian; Li, Shudong

    2014-01-01

    Identifying the most influential spreaders in spreading dynamics is of the utmost importance for various purposes for understanding or controlling these processes. The existing relevant works are limited to a single network. Most real networks are actually not isolated, but typically coupled and affected by others. The properties of epidemic spreading have recently been found to have some significant differences in interconnected networks from those in a single network. In this paper, we focus on identifying the influential spreaders in interconnected networks. We find that the well-known k-shell index loses effectiveness; some insignificant spreaders in a single network become the influential spreaders in the whole interconnected networks while some influential spreaders become no longer important. The simulation results show that the spreading capabilities of the nodes not only depend on their influence for the network topology, but also are dramatically influenced by the spreading rate. Based on this perception, a novel index is proposed for measuring the influential spreaders in interconnected networks. We then support the efficiency of this index with numerical simulations. (paper)

  17. Vulnerability of complex networks

    Science.gov (United States)

    Mishkovski, Igor; Biey, Mario; Kocarev, Ljupco

    2011-01-01

    We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős-Rényi (ER) random networks, Barabási-Albert (BA) model of scale-free networks, Watts-Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.

  18. 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.

  19. Epidemics in interconnected small-world networks.

    Science.gov (United States)

    Liu, Meng; Li, Daqing; Qin, Pengju; Liu, Chaoran; Wang, Huijuan; Wang, Feilong

    2015-01-01

    Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

  20. Epidemics in interconnected small-world networks.

    Directory of Open Access Journals (Sweden)

    Meng Liu

    Full Text Available Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

  1. Pinning impulsive control algorithms for complex network

    International Nuclear Information System (INIS)

    Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo

    2014-01-01

    In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms

  2. 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

  3. 4G Mobile Networks

    DEFF Research Database (Denmark)

    Lanzani, Christian Fabio Alessandro

    This thesis has investigated 4G radio access networks covering spectrum allocation methodologies, eNB software radios and architectures including interfacing performance aspects relevant for IMT-Advanced requirements. Dynamic spectrum allocation is an alternative to xed allocation methodologies. Al.......7-2.6 GHz bands. Likewise, SingleRAN low-power congurations will operate in the 2.6-3.8 GHz bands allowing equipment manu- factures to focus on a limited number of systems and congurations. An SCR architecture is proposed based on SoC integration of both digital and analog functions allowing mod- ularity...

  4. Future High Capacity Backbone Networks

    DEFF Research Database (Denmark)

    Wang, Jiayuan

    are proposed. The work focuses on energy efficient routing algorithms in a dynamic optical core network environment, with Generalized MultiProtocol Label Switching (GMPLS) as the control plane. Energy ef- ficient routing algorithms for energy savings and CO2 savings are proposed, and their performance...... aiming for reducing the dynamic part of the energy consumption of the network may increase the fixed part of the energy consumption meanwhile. In the second half of the thesis, the conflict between energy efficiency and Quality of Service (QoS) is addressed by introducing a novel software defined......This thesis - Future High Capacity Backbone Networks - deals with the energy efficiency problems associated with the development of future optical networks. In the first half of the thesis, novel approaches for using multiple/single alternative energy sources for improving energy efficiency...

  5. 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.

  6. 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...

  7. Network Survivability

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  8. 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.

  9. Telecommunication Networks

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  10. Network interruptions

    CERN Multimedia

    2005-01-01

    On Sunday 12 June 2005, a site-wide security software upgrade will be performed on all CERN network equipment. This maintenance operation will cause at least 2 short network interruptions of 2 minutes on each equipment item. There are hundreds of such items across the CERN site (Meyrin, Prévessin and all SPS and LHC pits), and it will thus take the whole day to treat them all. All network users and services will be affected. Central batch computing services will be interrupted during this period, expected to last from 8 a.m. until late evening. Job submission will still be possible but no jobs will actually be run. It is hoped to complete the computer centre upgrades in the morning so that stable access can be restored to lxplus, afs and nice services as soon as possible; this cannot be guaranteed, however. The opportunity will be used to interrupt and perform upgrades on the CERN Document Servers.

  11. Managing Networks

    DEFF Research Database (Denmark)

    Jørgensen, Heidi; Vintergaard, Christian

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

  12. A theory of intelligence: networked problem solving in animal societies

    OpenAIRE

    Shour, Robert

    2009-01-01

    A society's single emergent, increasing intelligence arises partly from the thermodynamic advantages of networking the innate intelligence of different individuals, and partly from the accumulation of solved problems. Economic growth is proportional to the square of the network entropy of a society's population times the network entropy of the number of the society's solved problems.

  13. Towards effective visual analytics on multiplex and multilayer networks

    DEFF Research Database (Denmark)

    Rossi, Luca; Magnani, Matteo

    2015-01-01

    In this article we discuss visualisation strategies for multiplex networks. Since Moreno’s early works on network analysis, visualisation has been one of the main ways to understand networks thanks to its ability to summarise a complex structure into a single representation highlighting multiple...

  14. 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...

  15. 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....

  16. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2018-01-01

    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....

  17. Network Views

    Science.gov (United States)

    Alexander, Louis

    2010-01-01

    The world changed in 2008. The financial crisis brought with it a deepening sense of insecurity, and the desire to be connected to a network increased. Throughout the summer and fall of 2008, events were unfolding with alarming rapidity. The Massachusetts Institute of Technology (MIT) Alumni Association wanted to respond to this change in the…

  18. 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 ...

  19. Global Networking.

    Science.gov (United States)

    Lynch, Clifford

    1997-01-01

    Discusses the state of the Internet. Highlights include the magnitude of the infrastructure, costs, its increasing pace, constraints in international links, provision of network capacity to homes and small businesses, cable television modems, political and cultural problems, the digital library concept, search engines, the failure of personal…

  20. 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.

  1. 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.

  2. Transition Towards An Integrated Network Organisation

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona; Wæhrens, Brian Vejrum

    2016-01-01

    , 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......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...... the organization, and its reconfiguration decisions. Implications are also discussed regarding process drivers and the role of HB in the network organization....

  3. 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

  4. 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-...

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

    OpenAIRE

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

    2016-01-01

    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...

  6. An overview of 5G network slicing architecture

    Science.gov (United States)

    Chen, Qiang; Wang, Xiaolei; Lv, Yingying

    2018-05-01

    With the development of mobile communication technology, the traditional single network model has been unable to meet the needs of users, and the demand for differentiated services is increasing. In order to solve this problem, the fifth generation of mobile communication technology came into being, and as one of the key technologies of 5G, network slice is the core technology of network virtualization and software defined network, enabling network slices to flexibly provide one or more network services according to users' needs[1]. Each slice can independently tailor the network functions according to the requirements of the business scene and the traffic model and manage the layout of the corresponding network resources, to improve the flexibility of network services and the utilization of resources, and enhance the robustness and reliability of the whole network [2].

  7. 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

  8. 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.

  9. Ecological network analysis: network construction

    NARCIS (Netherlands)

    Fath, B.D.; Scharler, U.M.; Ulanowicz, R.E.; Hannon, B.

    2007-01-01

    Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but

  10. 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.

  11. Application of artificial neural network for NHR fault diagnosis

    International Nuclear Information System (INIS)

    Yu Haitao; Zhang Liangju; Xu Xiangdong

    1999-01-01

    The author makes researches on 200 MW nuclear heating reactor (NHR) fault diagnosis system using artificial neural network, and use the tendency value and real value of the data under the accidents to train and test two BP networks respectively. The final diagnostic result is the combination of the results of the two networks. The compound system can enhance the accuracy and adaptability of the diagnosis comparing to the single network system

  12. Feedback Networks

    OpenAIRE

    Zamir, Amir R.; Wu, Te-Lin; Sun, Lin; Shen, William; Malik, Jitendra; Savarese, Silvio

    2016-01-01

    Currently, the most successful learning models in computer vision are based on learning successive representations followed by a decision layer. This is usually actualized through feedforward multilayer neural networks, e.g. ConvNets, where each layer forms one of such successive representations. However, an alternative that can achieve the same goal is a feedback based approach in which the representation is formed in an iterative manner based on a feedback received from previous iteration's...

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Cascade-based attacks on complex networks

    Science.gov (United States)

    Motter, Adilson E.; Lai, Ying-Cheng

    2002-12-01

    We live in a modern world supported by large, complex networks. Examples range from financial markets to communication and transportation systems. In many realistic situations the flow of physical quantities in the network, as characterized by the loads on nodes, is important. We show that for such networks where loads can redistribute among the nodes, intentional attacks can lead to a cascade of overload failures, which can in turn cause the entire or a substantial part of the network to collapse. This is relevant for real-world networks that possess a highly heterogeneous distribution of loads, such as the Internet and power grids. We demonstrate that the heterogeneity of these networks makes them particularly vulnerable to attacks in that a large-scale cascade may be triggered by disabling a single key node. This brings obvious concerns on the security of such systems.

  18. Camera network video summarization

    Science.gov (United States)

    Panda, Rameswar; Roy-Chowdhury, Amit K.

    2017-05-01

    Networks of vision sensors are deployed in many settings, ranging from security needs to disaster response to environmental monitoring. Many of these setups have hundreds of cameras and tens of thousands of hours of video. The difficulty of analyzing such a massive volume of video data is apparent whenever there is an incident that requires foraging through vast video archives to identify events of interest. As a result, video summarization, that automatically extract a brief yet informative summary of these videos, has attracted intense attention in the recent years. Much progress has been made in developing a variety of ways to summarize a single video in form of a key sequence or video skim. However, generating a summary from a set of videos captured in a multi-camera network still remains as a novel and largely under-addressed problem. In this paper, with the aim of summarizing videos in a camera network, we introduce a novel representative selection approach via joint embedding and capped l21-norm minimization. The objective function is two-fold. The first is to capture the structural relationships of data points in a camera network via an embedding, which helps in characterizing the outliers and also in extracting a diverse set of representatives. The second is to use a capped l21-norm to model the sparsity and to suppress the influence of data outliers in representative selection. We propose to jointly optimize both of the objectives, such that embedding can not only characterize the structure, but also indicate the requirements of sparse representative selection. Extensive experiments on standard multi-camera datasets well demonstrate the efficacy of our method over state-of-the-art methods.

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. Maximization Network Throughput Based on Improved Genetic Algorithm and Network Coding for Optical Multicast Networks

    Science.gov (United States)

    Wei, Chengying; Xiong, Cuilian; Liu, Huanlin

    2017-12-01

    Maximal multicast stream algorithm based on network coding (NC) can improve the network's throughput for wavelength-division multiplexing (WDM) networks, which however is far less than the network's maximal throughput in terms of theory. And the existing multicast stream algorithms do not give the information distribution pattern and routing in the meantime. In the paper, an improved genetic algorithm is brought forward to maximize the optical multicast throughput by NC and to determine the multicast stream distribution by hybrid chromosomes construction for multicast with single source and multiple destinations. The proposed hybrid chromosomes are constructed by the binary chromosomes and integer chromosomes, while the binary chromosomes represent optical multicast routing and the integer chromosomes indicate the multicast stream distribution. A fitness function is designed to guarantee that each destination can receive the maximum number of decoding multicast streams. The simulation results showed that the proposed method is far superior over the typical maximal multicast stream algorithms based on NC in terms of network throughput in WDM networks.

  4. 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

  5. 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.

  6. 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.

  7. Single-Sex Classrooms

    Science.gov (United States)

    Protheroe, Nancy

    2009-01-01

    Although single-sex education was once the norm in the U.S., the practice has largely been confined to private schools for more than a century. However, with the introduction of the final version of the U.S. Department of Education's so-called single-sex regulations in 2006, public schools were allowed greater flexibility to offer single-sex…

  8. Superconducting Single Photon Detectors

    NARCIS (Netherlands)

    Dorenbos, S.N.

    2011-01-01

    This thesis is about the development of a detector for single photons, particles of light. New techniques are being developed that require high performance single photon detection, such as quantum cryptography, single molecule detection, optical radar, ballistic imaging, circuit testing and

  9. 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...

  10. 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

  11. 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

  12. Organization of growing random networks

    International Nuclear Information System (INIS)

    Krapivsky, P. L.; Redner, S.

    2001-01-01

    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 k . When A k grows more slowly than linearly with k, the number of nodes with k links, N k (t), decays faster than a power law in k, while for A k growing faster than linearly in k, a single node emerges which connects to nearly all other nodes. When A k is asymptotically linear, N k (t)∼tk -ν , with ν dependent on details of the attachment probability, but in the range 2 -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

  13. Stability of Boolean multilevel networks.

    Science.gov (United States)

    Cozzo, Emanuele; Arenas, Alex; Moreno, Yamir

    2012-09-01

    The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semiannealed approximation to study the stability properties of random Boolean networks in multiplex (multilayered) graphs. Our main finding is that the multilevel structure provides a mechanism for the stabilization of the dynamics of the whole system even when individual layers work on the chaotic regime, therefore identifying new ways of feedback between the structure and the dynamics of these systems. Our results point out the need for a conceptual transition from the physics of single-layered networks to the physics of multiplex networks. Finally, the fact that the coupling modifies the phase diagram and the critical conditions of the isolated layers suggests that interdependency can be used as a control mechanism.

  14. 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.

  15. 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.

  16. Improving network management with Software Defined Networking

    International Nuclear Information System (INIS)

    Dzhunev, Pavel

    2013-01-01

    Software-defined networking (SDN) is developed as an alternative to closed networks in centers for data processing by providing a means to separate the control layer data layer switches, and routers. SDN introduces new possibilities for network management and configuration methods. In this article, we identify problems with the current state-of-the-art network configuration and management mechanisms and introduce mechanisms to improve various aspects of network management

  17. Single atom oscillations

    International Nuclear Information System (INIS)

    Wiorkowski, P.; Walther, H.

    1990-01-01

    Modern methods of laser spectroscopy allow the study of single atoms or ions in an unperturbed environment. This has opened up interesting new experiments, among them the detailed study of radiation-atom coupling. In this paper, the following two experiments dealing with this problem are reviewed: the single-atom maser and the study of the resonance fluorescence of a single stored ion. The simplest and most fundamental system for studying radiation-matter coupling is a single two-level atom interacting with a single mode of an electromagnetic field in a cavity. This problem received a great deal of attention shortly after the maser was invented

  18. Distributed Robust Power Minimization for the Downlink of Multi-Cloud Radio Access Networks

    KAUST Repository

    Dhifallah, Oussama Najeeb; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2017-01-01

    Conventional cloud radio access networks assume single cloud processing and treat inter-cloud interference as background noise. This paper considers the downlink of a multi-cloud radio access network (CRAN) where each cloud is connected to several

  19. 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.

  20. Single quadrature duplication and transparent taps

    International Nuclear Information System (INIS)

    Kim, Ajung

    2004-01-01

    The concept of single quadrature duplication, which is the process of producing two outputs with the same homodyne detecting statistics as an input, is addressed. This device has important potential application to optical communications as a transparent optical tap in a local area network environment. The characteristics of the device are examined, and a realization scheme employing a coupler and phase-sensitive amplifiers is proposed

  1. 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.

  2. Concurrent bandits and cognitive radio networks

    OpenAIRE

    Avner, Orly; Mannor, Shie

    2014-01-01

    We consider the problem of multiple users targeting the arms of a single multi-armed stochastic bandit. The motivation for this problem comes from cognitive radio networks, where selfish users need to coexist without any side communication between them, implicit cooperation or common control. Even the number of users may be unknown and can vary as users join or leave the network. We propose an algorithm that combines an $\\epsilon$-greedy learning rule with a collision avoidance mechanism. We ...

  3. Advanced Communication for Wireless Sensor Networks

    Science.gov (United States)

    2016-08-22

    strategies that could be used to increase the single-hop transmission range of a wireless sensor network, increase energy efficiency (improve battery...substance placed within the reach of the network. Sensor measurements were quantized to save energy and bandwidth during transmission of the...the problem of assigning transmission powers to every node in order to maintain connectivity while minimizing the energy consumption of the whole

  4. Dynamic simulations of single-molecule enzyme networks

    NARCIS (Netherlands)

    Armbruster, H.D.; Nagy, J.D.; Rijt, van de E.A.F.; Rooda, J.E.

    2009-01-01

    Along with the growth of technologies allowing accurate visualization of biochemical reactions to the scale of individual molecules has arisen an appreciation of the role of statistical fluctuations in intracellular biochemistry. The stochastic nature of metabolism can no longer be ignored. It can

  5. QUANTUM NETWORKS WITH SINGLE ATOMS, PHOTONS AND PHONONS

    Science.gov (United States)

    2016-10-04

    there is interference between two different transport channels. For instance, in a cavity far from resonance, there is interference arising from all...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...Elements of Quantum Optics. Springer-Verlag, Berlin, 2007. [39] J.-T. Shen and S. Fan. Coherent photon transport from spontaneous emission in one

  6. 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.

  7. Quantum logic networks for probabilistic teleportation

    Institute of Scientific and Technical Information of China (English)

    刘金明; 张永生; 等

    2003-01-01

    By eans of the primitive operations consisting of single-qubit gates.two-qubit controlled-not gates,Von Neuman measurement and classically controlled operations.,we construct efficient quantum logic networks for implementing probabilistic teleportation of a single qubit,a two-particle entangled state,and an N-particle entanglement.Based on the quantum networks,we show that after the partially entangled states are concentrated into maximal entanglement,the above three kinds of probabilistic teleportation are the same as the standard teleportation using the corresponding maximally entangled states as the quantum channels.

  8. Inferring Phylogenetic Networks Using PhyloNet.

    Science.gov (United States)

    Wen, Dingqiao; Yu, Yun; Zhu, Jiafan; Nakhleh, Luay

    2018-07-01

    PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.

  9. 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 stru......-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....

  10. 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)

  11. Single photon emission tomography

    International Nuclear Information System (INIS)

    Buvat, Irene

    2011-09-01

    The objective of this lecture is to present the single photon emission computed tomography (SPECT) imaging technique. Content: 1 - Introduction: anatomic, functional and molecular imaging; Principle and role of functional or molecular imaging; 2 - Radiotracers: chemical and physical constraints, main emitters, radioisotopes production, emitters type and imaging techniques; 3 - Single photon emission computed tomography: gamma cameras and their components, gamma camera specifications, planar single photon imaging characteristics, gamma camera and tomography; 4 - Quantification in single photon emission tomography: attenuation, scattering, un-stationary spatial resolution, partial volume effect, movements, others; 5 - Synthesis and conclusion

  12. Pain: a distributed brain information network?

    Directory of Open Access Journals (Sweden)

    Hiroaki Mano

    2015-01-01

    Full Text Available Understanding how pain is processed in the brain has been an enduring puzzle, because there doesn't appear to be a single "pain cortex" that directly codes the subjective perception of pain. An emerging concept is that, instead, pain might emerge from the coordinated activity of an integrated brain network. In support of this view, Woo and colleagues present evidence that distinct brain networks support the subjective changes in pain that result from nociceptive input and self-directed cognitive modulation. This evidence for the sensitivity of distinct neural subsystems to different aspects of pain opens up the way to more formal computational network theories of pain.

  13. 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.

  14. 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...

  15. Immunization of Epidemics in Multiplex Networks

    Science.gov (United States)

    Zhao, Dawei; Wang, Lianhai; Li, Shudong; Wang, Zhen; Wang, Lin; Gao, Bo

    2014-01-01

    Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks. PMID:25401755

  16. 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.

  17. Immunization of epidemics in multiplex networks.

    Science.gov (United States)

    Zhao, Dawei; Wang, Lianhai; Li, Shudong; Wang, Zhen; Wang, Lin; Gao, Bo

    2014-01-01

    Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks.

  18. Immunization of epidemics in multiplex networks.

    Directory of Open Access Journals (Sweden)

    Dawei Zhao

    Full Text Available Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted immunization and layer node-based random (targeted immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF networks.

  19. Pinning synchronization of a mobile agent network

    International Nuclear Information System (INIS)

    Wang, Lei; Sun, You-xian

    2009-01-01

    We investigate the problem of controlling a group of mobile agents in a plane in order to move them towards a desired orbit via pinning control, in which each agent is associated with a chaotic oscillator coupled with those of neighboring agents, and the pinning strategy is to have the common linear feedback acting on a small fraction of agents by random selection. We explore the effects of the pinning probability, feedback gains and agent density in the pinning synchronization of a mobile agent network under a fast-switching constraint, and perform numerical simulations for validation. In particular, we show that there exists a critical pinning density for network synchronization with an unbounded region: above the threshold, the dynamical network can be controlled by pinning; below it, anarchy prevails. And for the network with a single bounded synchronization region, pinning control has little effect as regards enhancing network synchronizability

  20. 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...

  1. Synchronization of networks

    Indian Academy of Sciences (India)

    We study the synchronization of coupled dynamical systems on networks. The dynamics is .... Such a time-varying topology can occur in social networks, computer networks, WWW ... This has the effect of reducing the spread of the transverse ...

  2. Reconfigurable network processing platforms

    NARCIS (Netherlands)

    Kachris, C.

    2007-01-01

    This dissertation presents our investigation on how to efficiently exploit reconfigurable hardware to design flexible, high performance, and power efficient network devices capable to adapt to varying processing requirements of network applications and traffic. The proposed reconfigurable network

  3. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  4. 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.

  5. 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.

  6. 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

  7. Network development plan 1995

    International Nuclear Information System (INIS)

    Anon.

    1995-11-01

    Network plan 1995 concerns several strategic problems, among others environmental policy of power transmission lines. Possibilities of restructuring aerial cable network are described. The state of the existing systems and plans for new network systems are presented. (EG)

  8. Using turbidity for designing water networks.

    Science.gov (United States)

    Castaño, J A; Higuita, J C

    2016-05-01

    Some methods to design water networks with minimum fresh water consumption are based on the selection of a key contaminant. In most of these "single contaminant methods", a maximum allowable concentration of contaminants must be established in water demands and water sources. Turbidity is not a contaminant concentration but is a property that represents the "sum" of other contaminants, with the advantage that it can be cheaper and easily measured than biological oxygen demand, chemical oxygen demand, suspended solids, dissolved solids, among others. The objective of this paper is to demonstrate that turbidity can be used directly in the design of water networks just like any other contaminant concentration. A mathematical demonstration is presented and in order to validate the mathematical results, the design of a water network for a guava fudge production process is performed. The material recovery pinch diagram and nearest neighbors algorithm were used for the design of the water network. Nevertheless, this water network could be designed using other single contaminant methodologies. The maximum error between the expected and the real turbidity values in the water network was 3.3%. These results corroborate the usefulness of turbidity in the design of water networks. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. 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

  10. 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.

  11. 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.

  12. 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....

  13. Sensing single electrons with single molecules

    International Nuclear Information System (INIS)

    Plakhotnik, Taras

    2007-01-01

    We propose a new methodology for probing transport of just one electron, a process of great importance both in nature and in artificial devices. Our idea for locating a single electron is analogues to the conventional GPS where signals from several satellites are used to locate a macro object. Using fluorescent molecules as tiny sensors, it is possible to determine 3D displacement vector of an electron

  14. Pareto distance for multi-layer network analysis

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2013-01-01

    services, e.g., Facebook, Twitter, LinkedIn and Foursquare. As a result, the analysis of on-line social networks requires a wider scope and, more technically speaking, models for the representation of this fragmented scenario. The recent introduction of more realistic layered models has however determined......Social Network Analysis has been historically applied to single networks, e.g., interaction networks between co-workers. However, the advent of on-line social network sites has emphasized the stratified structure of our social experience. Individuals usually spread their identities over multiple...

  15. 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.

  16. The Homogeneity Research of Urban Rail Transit Network Performance

    Directory of Open Access Journals (Sweden)

    Wang Fu-jian

    2016-01-01

    Full Text Available Urban Rail Transit is an important part of the public transit, it is necessary to carry out the corresponding network function analysis. Previous studies mainly about network performance analysis of a single city rail transit, lacking of horizontal comparison between the multi-city, it is difficult to find inner unity of different Urban Rail Transit network functions. Taking into account the Urban Rail Transit network is a typical complex networks, so this paper proposes the application of complex network theory to research the homogeneity of Urban Rail Transit network performance. This paper selects rail networks of Beijing, Shanghai, Guangzhou as calculation case, gave them a complex network mapping through the L, P Space method and had a static topological analysis using complex network theory, Network characteristics in three cities were calculated and analyzed form node degree distribution and node connection preference. Finally, this paper studied the network efficiency changes of Urban Rail Transit system under different attack mode. The results showed that, although rail transport network size, model construction and construction planning of the three cities are different, but their network performance in many aspects showed high homogeneity.

  17. 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.

  18. Experiments with arbitrary networks in time-multiplexed delay systems

    Science.gov (United States)

    Hart, Joseph D.; Schmadel, Don C.; Murphy, Thomas E.; Roy, Rajarshi

    2017-12-01

    We report a new experimental approach using an optoelectronic feedback loop to investigate the dynamics of oscillators coupled on large complex networks with arbitrary topology. Our implementation is based on a single optoelectronic feedback loop with time delays. We use the space-time interpretation of systems with time delay to create large networks of coupled maps. Others have performed similar experiments using high-pass filters to implement the coupling; this restricts the network topology to the coupling of only a few nearest neighbors. In our experiment, the time delays and coupling are implemented on a field-programmable gate array, allowing the creation of networks with arbitrary coupling topology. This system has many advantages: the network nodes are truly identical, the network is easily reconfigurable, and the network dynamics occur at high speeds. We use this system to study cluster synchronization and chimera states in both small and large networks of different topologies.

  19. Survivability Strategies for Epidemic Failures in Heterogeneous Networks

    DEFF Research Database (Denmark)

    Katsikas, Dimitrios; Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2013-01-01

    Nowadays, transport networks, carry extremely large amounts of network traffic, and are widely spread across multiple geographical locations. As a result, any possible connectivity failure could directly impact the service delivery of a vast amount of users. Therefore, the network should be able...... protection, path restoration) X[1]X. Hence, assuming sufficient resources, network resilience can be achieved when a single failure occur (e.g. fiber cut). However, when it comes to simultaneous failures such as cascading and epidemic failures, the available solutions are expensive X[2]X. For Generalized...... the network X[6]X[7]X. This paper evaluates the reliability of a GMPLS transport network under epidemic failure scenarios. Thus, the aim is to increase the fault tolerance of the GMPLS technology when simultaneous failures occur impacting a large number of network nodes across an optical transport network...

  20. 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...

  1. 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...

  2. Integrating Networking into ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2018-01-01

    Networking is foundational to the ATLAS distributed infrastructure and there are many ongoing activities related to networking both within and outside of ATLAS. We will report on the progress in a number of areas exploring ATLAS's use of networking and our ability to monitor the network, analyze metrics from the network, and tune and optimize application and end-host parameters to make the most effective use of the network. Specific topics will include work on Open vSwitch for production systems, network analytics, FTS testing and tuning, and network problem alerting and alarming.

  3. 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.

  4. 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…

  5. 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...

  6. Composition and structure of a large online social network in The Netherlands.

    Directory of Open Access Journals (Sweden)

    Rense Corten

    Full Text Available 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. 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 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...... 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....

  14. Network Plus

    Science.gov (United States)

    Bender, Walter; Chesnais, Pascal

    1988-05-01

    Over the past several years, the Electronic Publishing Group at the MIT Media Laboratory has been conducting a family of media experiments which explore a new kind of broadcast: the distribution of data and computer programs rather than pre-packaged material. This broadcast is not directed to a human recipient, but to a local computational agent acting on his behalf. In response to instructions from both the broadcaster and the reader, this agent selects from the incoming data and presents it in a manner suggestive of traditional media. The embodiment of these media experiments is a news retrieval system where the news editor has been replaced by the personal computer. A variety of both local and remote databases which operate passively as well as interac-tively are accessed by "reporters." These "reporters" are actually software interfaces, which are programmed to gather news. Ideally, they are "broadcatching" that is to say, watching all broadcast television channels, listening to all radio transmissions, and reading all newspapers, magazines, and journals. 1 A possible consequence of the synthesis of media through active processing is the merger of newspapers and television (figure 1). The result is either a newspaper with illustrations which move 2 or, conversely, print as television output. The latter is the theme of Network Plus.

  15. Single-Photon Routing for a L-Shaped Channel

    Science.gov (United States)

    Yang, Xiong; Hou, Jiao-Jiao; Wu, Chun

    2018-02-01

    We have investigated the transport properties of a single photon scattered by a two-level atom embedded in a L-shaped waveguide, which is made of two one-dimensional (1D) semi-infinite coupled-resonator waveguides (CRWs). Single photons can be directed from one CRW to the other due to spontaneous emission of the atom. The result shows that the spontaneous emission of the TLS still routes single photon from one CRW to the other; the boundary existing makes the probability of finding single photon in a CRW could reach one. Our the scheme is helpful to construct a ring quantum networks.

  16. Modeling of steam generator in nuclear power plant using neural network ensemble

    International Nuclear Information System (INIS)

    Lee, S. K.; Lee, E. C.; Jang, J. W.

    2003-01-01

    Neural network is now being used in modeling the steam generator is known to be difficult due to the reverse dynamics. However, Neural network is prone to the problem of overfitting. This paper investigates the use of neural network combining methods to model steam generator water level and compares with single neural network. The results show that neural network ensemble is effective tool which can offer improved generalization, lower dependence of the training set and reduced training time

  17. Adaptive Suspicious Prevention for Defending DoS Attacks in SDN-Based Convergent Networks

    OpenAIRE

    Dao, Nhu-Ngoc; Kim, Joongheon; Park, Minho; Cho, Sungrae

    2016-01-01

    The convergent communication network will play an important role as a single platform to unify heterogeneous networks and integrate emerging technologies and existing legacy networks. Although there have been proposed many feasible solutions, they could not become convergent frameworks since they mainly focused on converting functions between various protocols and interfaces in edge networks, and handling functions for multiple services in core networks, e.g., the Multi-protocol Label Switchi...

  18. 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...

  19. 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.

  20. Data center networks and network architecture

    Science.gov (United States)

    Esaki, Hiroshi

    2014-02-01

    This paper discusses and proposes the architectural framework, which is for data center networks. The data center networks require new technical challenges, and it would be good opportunity to change the functions, which are not need in current and future networks. Based on the observation and consideration on data center networks, this paper proposes; (i) Broadcast-free layer 2 network (i.e., emulation of broadcast at the end-node), (ii) Full-mesh point-to-point pipes, and (iii) IRIDES (Invitation Routing aDvertisement for path Engineering System).