143 research outputs found
Asynchronous Bidirectional Decoding for Neural Machine Translation
The dominant neural machine translation (NMT) models apply unified
attentional encoder-decoder neural networks for translation. Traditionally, the
NMT decoders adopt recurrent neural networks (RNNs) to perform translation in a
left-toright manner, leaving the target-side contexts generated from right to
left unexploited during translation. In this paper, we equip the conventional
attentional encoder-decoder NMT framework with a backward decoder, in order to
explore bidirectional decoding for NMT. Attending to the hidden state sequence
produced by the encoder, our backward decoder first learns to generate the
target-side hidden state sequence from right to left. Then, the forward decoder
performs translation in the forward direction, while in each translation
prediction timestep, it simultaneously applies two attention models to consider
the source-side and reverse target-side hidden states, respectively. With this
new architecture, our model is able to fully exploit source- and target-side
contexts to improve translation quality altogether. Experimental results on
NIST Chinese-English and WMT English-German translation tasks demonstrate that
our model achieves substantial improvements over the conventional NMT by 3.14
and 1.38 BLEU points, respectively. The source code of this work can be
obtained from https://github.com/DeepLearnXMU/ABDNMT.Comment: accepted by AAAI 1
Effect of matrix suction on the shear strength characteristics of reinforced granite residual soil
Introduction: The soil in geogrid-reinforced structures is typically unsaturated, with the shear strength provided by both the matrix suction and the reinforced body. Traditional structural designs for saturated soils only consider the shear strength provided by the reinforced body, neglecting the part provided by matrix suction. As a result, the design for reinforced structures is biased toward conservatism.Method: The study examined the matrix suction-provided shear strength in reinforced soils through strain-controlled triaxial and soil-water characteristic curve (SWCC) pressure plate instrumentation. The feasibility of the Schrefler and Khalili unsaturated soil shear strength formulas for predicting shear strength based on matrix suction forces was verified.Results: The study revealed that the cohesion of saturated reinforced soil exhibits a significant decrease in contrast with unsaturated reinforced soil, with matrix suction serving as a crucial consideration for reinforced structure design.Discussion: The experimental results confirm the suitability of applying the quasi-cohesion increment theory to reinforced clays. The Khalili formula can be utilized to predict the quasi cohesion of unsaturated reinforced soils with greater accuracy under diverse dry density conditions. The results obtained using post-shear moisture content were closer to the measured values than those using initial moisture content
Nitrogen-enriched hierarchically porous carbon materials fabricated by graphene aerogel templated Schiff-base chemistry for high performance electrochemical capacitors
This article presents a facile and effective approach for synthesizing three-dimensional (3D) graphenecoupled Schiff-base hierarchically porous polymers (GS-HPPs). The method involves the polymerization of melamine and 1,4-phthalaldehyde, yielding Schiff-base porous polymers on the interconnected macroporous frameworks of 3D graphene aerogels. The as-synthesized GS-HPPs possess hierarchically porous structures containing macro-/meso-/micropores, along with large specific surface areas up to 776 mĀ² gā»Ā¹ and high nitrogen contents up to 36.8 wt%. Consequently, 3D nitrogen-enriched hierarchically porous carbon (N-HPC) materials with macro-/meso-/micropores were obtained by the pyrolysis of the GS-HPPs at a high temperature of
800 Ā°C under a nitrogen atmosphere. With a hierarchically porous structure, good thermal stability and a high nitrogen-doping content up to 7.2 wt%, the N-HPC samples show a high specific capacitance of 335 F gā»Ā¹ at 0.1 A gā»Ā¹ in 6 M KOH, a good capacitance retention with increasing current density, and an outstanding cycling stability. The superior electrochemical performance means that the N-HPC materials have great potential as electrode materials for supercapacitors
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