2,167 research outputs found
Research on the Permeability and Earthquake Damage of an Earth Dam Foundation
The experiences on geological investigation, permeability test, prediction of seepage failure patterns and the earthquake damage of an earth dam foundation are presented in this paper. Basing on the monitoring data and seismic records observed from the seismic station on the dam, the prediction of reservoir induced earthquake and possibility of liquefaction are analysed
JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution
Recent years have witnessed a rapid growth of deep-network based services and
applications. A practical and critical problem thus has emerged: how to
effectively deploy the deep neural network models such that they can be
executed efficiently. Conventional cloud-based approaches usually run the deep
models in data center servers, causing large latency because a significant
amount of data has to be transferred from the edge of network to the data
center. In this paper, we propose JALAD, a joint accuracy- and latency-aware
execution framework, which decouples a deep neural network so that a part of it
will run at edge devices and the other part inside the conventional cloud,
while only a minimum amount of data has to be transferred between them. Though
the idea seems straightforward, we are facing challenges including i) how to
find the best partition of a deep structure; ii) how to deploy the component at
an edge device that only has limited computation power; and iii) how to
minimize the overall execution latency. Our answers to these questions are a
set of strategies in JALAD, including 1) A normalization based in-layer data
compression strategy by jointly considering compression rate and model
accuracy; 2) A latency-aware deep decoupling strategy to minimize the overall
execution latency; and 3) An edge-cloud structure adaptation strategy that
dynamically changes the decoupling for different network conditions.
Experiments demonstrate that our solution can significantly reduce the
execution latency: it speeds up the overall inference execution with a
guaranteed model accuracy loss.Comment: conference, copyright transfered to IEE
The long-lasting optical afterglow plateau of short burst GRB 130912A
The short burst GRB 130912A was detected by Swift, Fermi satellites and
several ground-based optical telescopes. Its X-ray light curve decayed with
time normally. The optical emission, however, displayed a long term plateau,
which is the longest one in current short GRB observations. In this work we
examine the physical origin of the X-ray and optical emission of this peculiar
event. We find that the canonical forward shock afterglow emission model can
account for the X-ray and optical data self-consistently and the energy
injection model that has been widely adopted to interpret the
shallowly-decaying afterglow emission is not needed. We also find that the
burst was born in a very-low density interstellar medium, consistent with the
compact object merger model. Significant fractions of the energy of the forward
shock have been given to accelerate the non-thermal electrons and amplify the
magnetic fields (i.e., and , respectively), which are much larger than those inferred in most short
burst afterglow modeling and can explain why the long-lasting optical afterglow
plateau is rare in short GRBs.Comment: 5 pages, 2 figure
Embedded Applications of MS-PSO-BP on Wind/Storage Power Forecasting
Higher proportion wind power penetration has great impact on grid operation and dispatching, intelligent hybrid algorithm is proposed to cope with inaccurate schedule forecast. Firstly, hybrid algorithm of MS-PSO-BP (Mathematical Statistics, Particle Swarm Optimization, Back Propagation neural network) is proposed to improve the wind power system prediction accuracy. MS is used to optimize artificial neural network training sample, PSO-BP (particle swarm combined with back propagation neural network) is employed on prediction error dynamic revision. From the angle of root mean square error (RMSE), the mean absolute error (MAE) and convergence rate, analysis and comparison of several intelligent algorithms (BP, RBP, PSO-BP, MS-BP, MS-RBP, MS-PSO-BP) are done to verify the availability of the proposed prediction method. Further, due to the physical function of energy storage in improving accuracy of schedule pre-fabrication, a mathematical statistical method is proposed to determine the optimal capacity of the storage batteries in power forecasting based on the historical statistical data of wind farm. Algorithm feasibility is validated by application of experiment simulation and comparative analysis
Dynamics Model of Carrier-based Aircraft Landing Gears Landed on Dynamic Deck
AbstractIn order to study the carrier-based aircraft landing laws landed on the carrier, the dynamics model of carrier-based aircraft landing gears landed on dynamic deck is built. In this model, the interactions of the carrier-based aircraft landing attitude and the damping force acting on landing gears are considered, and the influence of dynamic deck is introduced into the model through the deck normal vectors. The wheel-deck coordinate system is put forward to solve the complex simulation problem of force-on-wheel which comes from the dynamic deck. At last, by simulation, it is demonstrated that the model can be applied to landing attitude when the carrier-based aircraft is landing on the dynamic deck, it is also proved that the model is comprehensive and suitable for any abnormal landing situation
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