5,941 research outputs found

    Locating influential nodes via dynamics-sensitive centrality

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    With great theoretical and practical significance, locating influential nodes of complex networks is a promising issues. In this paper, we propose a dynamics-sensitive (DS) centrality that integrates topological features and dynamical properties. The DS centrality can be directly applied in locating influential spreaders. According to the empirical results on four real networks for both susceptible-infected-recovered (SIR) and susceptible-infected (SI) spreading models, the DS centrality is much more accurate than degree, kk-shell index and eigenvector centrality.Comment: 6 pages, 1 table and 2 figure

    ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

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    We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs). The new architecture utilizes two new operations, pointwise group convolution and channel shuffle, to greatly reduce computation cost while maintaining accuracy. Experiments on ImageNet classification and MS COCO object detection demonstrate the superior performance of ShuffleNet over other structures, e.g. lower top-1 error (absolute 7.8%) than recent MobileNet on ImageNet classification task, under the computation budget of 40 MFLOPs. On an ARM-based mobile device, ShuffleNet achieves ~13x actual speedup over AlexNet while maintaining comparable accuracy

    A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves

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    Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system - for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave

    From Dust To Planetesimal: The Snowball Phase ?

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    The standard model of planet formation considers an initial phase in which planetesimals form from a dust disk, followed by a phase of mutual planetesimal-planetesimal collisions, leading eventually to the formation of planetary embryos. However, there is a potential transition phase (which we call the "snowball phase"), between the formation of the first planetesimals and the onset of mutual collisions amongst them, which has often been either ignored or underestimated in previous studies. In this snowball phase, isolated planetesimals move on Keplerian orbits and grow solely via the direct accretion of sub-cm sized dust entrained with the gas in the protoplanetary disk. Using a simplified model in which planetesimals are progressively produced from the dust, we consider the expected sizes to which the planetesimals can grow before mutual collisions commence and derive the dependence of this size on a number of critical parameters, including the degree of disk turbulence, the planetesimal size at birth and the rate of planetesimal creation. For systems in which turbulence is weak and the planetesimals are created at a low rate and with relatively small birth size, we show that the snowball growth phase can be very important, allowing planetesimals to grow by a factor of 10^6 in mass before mutual collisions take over. In such cases, the snowball growth phase can be the dominant mode to transfer mass from the dust to planetesimals. Moreover, such growth can take place within the typical lifetime of a protoplanetary gas disk. A noteworthy result is that ... ...(see the paper). For the specific case of close binaries such as Alpha Centauri ... ... (see the paper). From a more general perspective, these preliminary results suggest that an efficient snowball growth phase provides a large amount of "room at the bottom" for theories of planet formation.Comment: Accepted for publication in the Astrophysical Journal. 15 pages, 4 figures, 1 tabl
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