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Li Lei Limin Li Shasha Wang Gaoyang Zhao Yoshifumi Oshima Yang Ren Lei Zhao Lihua Jin Yao Wang Chengshan Li Pingxiang Zhang 《Journal of the European Ceramic Society》2018,38(14):4694-4700
Highly (100)-oriented Ce1-x(Y0.2Zr0.8)xOδ (CYZO) films were prepared on biaxially textured NiW substrates by a chemical solution deposition approach using metal inorganic salts as starting materials. It has been found that both the preferential orientation and surface roughness of CYZO films decrease gradually with increasing of the doping percentage of Y3+ and Zr4+ ions. The epitaxial growth relationship of (220)CYZO//(200)NiW and [00?l]CYZO//[001]NiW was demonstrated by XRD texture measurement as well as atomic resolution STEM observation. XRD, Raman and XPS spectra results indicate that Y3+ and Zr4+ ions were indeed introduced into CeO2 lattice to substitute Ce4+ ions and form cubic fluorite CYZO solid solution. Moreover, CeO2 buffer layer can be endowed a strong enough capability to prevent element diffusion through co-doping of yttrium and zirconium, provided that an optimal doping ratio of them is adopted. This will provide a new approach to fabricating strong-barrier single buffer layer for coated conductor. 相似文献
84.
Yao Dajie Liu Xiaofei Wu Jian 《International Journal of Control, Automation and Systems》2020,18(9):2251-2258
International Journal of Control, Automation and Systems - In this paper, the tracking problem for a class of uncertain nonlinearly parameterized systems with input delay based the adaptive... 相似文献
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To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction,
optimization model decoupling and optimization was presented. In feasible region
reduction, the dimensions of the feasible design region were reduced by selecting dominant
design variables from numerous multilevel parameters by sensitivity analyses, and the
feasible regions of variables were reduced by influence mechanism analyses. In model
decoupling, the optimization model with a large number of variables was divided into
various sub-models with fewer variables by variance analysis. In the third step, the
optimization sub-models were solved one by one using a genetic algorithm, and the
modified characteristic curve method was adopted as the failure prediction method. Based
on the proposed optimization method, optimization of a double-lap single-bolt joint was
performed using the ANSYS® code. The results show that the bearing failure load increased
by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of
the joint, which validated the effectiveness of the three-step optimization strategy. 相似文献
87.
The application of deep learning in the field of object detection has
experienced much progress. However, due to the domain shift problem, applying an
off-the-shelf detector to another domain leads to a significant performance drop. A
large number of ground truth labels are required when using another domain to train
models, demanding a large amount of human and financial resources. In order to avoid
excessive resource requirements and performance drop caused by domain shift, this
paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our
approach improves the cross-domain vehicle detection model from image space and
feature space. We employ objectives of the generative adversarial network and cycle
consistency loss for image style transfer in image space. For feature space, we align
feature distributions between the source domain and the target domain to improve the
detection accuracy. Experiments are carried out using the method with two different
datasets, proving that this technique effectively improves the accuracy of vehicle
detection in the target domain. 相似文献
89.
Neural Machine Translation (NMT) is an end-to-end learning approach for
automated translation, overcoming the weaknesses of conventional phrase-based translation
systems. Although NMT based systems have gained their popularity in commercial
translation applications, there is still plenty of room for improvement. Being the most
popular search algorithm in NMT, beam search is vital to the translation result. However,
traditional beam search can produce duplicate or missing translation due to its target
sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural
machine translation improvements based on a novel beam search evaluation function. And
we use reinforcement learning to train a translation evaluation system to select better
candidate words for generating translations. In the experiments, we conducted extensive
experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual
corpora of NiuTrans are used in our experiments. The experiment results prove that the
proposed methods can effectively improve the English to Chinese translation quality. 相似文献
90.