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1.
针对目标估计过程需要大量人工参与、自动化程度低的问题,提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法,对不同传感器得到的目标数据质量进行科学、有效的测度和评价,并根据质量得分动态调整各数据源在目标估计过程中所占的权重,从而减少人工干预,提高目标估计效能。仿真试验结果证明了该方法的有效性。 相似文献
2.
Effects of injection parameters on propagation patterns of hydrogen-fueled rotating detonation waves
《International Journal of Hydrogen Energy》2022,47(91):38811-38822
Two-dimensional rotating detonation waves (RDWs) with separate injections of hydrogen and air are simulated using the Navier–Stokes equations together with a detailed chemical mechanism. The effects of injection stagnation temperature and slot width on the detonation propagation patterns are investigated. Results find that extremely high temperatures can lead to a chaotic mode in which detonation waves are generated and extinguished randomly. Increasing the slot width can reduce the number of detonation waves and finally trigger detonation quenching at a low injection stagnation temperature. But increasing the slot width can change the RDW propagation pattern from a chaotic to a stable mode under high injection temperature. Furthermore, the kinetic parameter τ (representing the chemical reactivity of the mixture) and the kinematic parameter α (representing the mixing efficiency of hydrogen and oxygen) are introduced to distinguish the RDW propagation patterns. 相似文献
3.
《Ceramics International》2022,48(22):33177-33184
The rare earth (Yb3+) substituted W-type hexagonal ferrites with composition CaPb2-xYbxFe16O27 (x = 0.0, 0.5, 1.0, 1.5, 2.0) were synthesized by a facile and cost-effective sol-gel auto combustion method with post heat treatment. The synthesized hexagonal ferrites were characterized by a variety of analytical techniques, and an impedance analyzer was used to investigate the effects of Ytterbium on structural, magnetic, spectral and dielectric properties. The relationship between their impedance, structure and dielectric properties was investigated. The X-ray diffraction patterns verify the presence of single-phase W-type hexagonal ferrites. Physical properties such as Dbulk (bulk density), Dxrd (X-ray density), and P (porosity) of the CaPb2-xYbxFe16O27 W-type hexagonal ferrites were calculated. The bulk density of all the samples was decreased, and X-ray intensity was increased with the Ytterbium replacement in the W-type hexaferrite. By adding Yb3+ ions, the lattice parameters, cell volume and X-ray density were reduced due to the substitution of ytterbium with smaller ionic radii compared to the lead ion with large ionic radii. The AC-conductivity was increased from (1.523 × 10?5 to 6.699 × 10?5) Ωcm?1. The dielectric constant and tangent loss was found to decrease substantially. The magnetic properties were found to enhance by the substitution of Yb3+. The low coercivity value of Yb3+ substituted W-type hexagonal ferrites are suitable for magnetic recording media operated at a high-frequency regime. The enhancement of electrical, dielectric and magnetic characteristics suggests these materials as promising for multi-layer chip inductors (MLCIs) circuit applications. 相似文献
4.
机器翻译译文质量估计(Quality Estimation,QE)是指在不需要人工参考译文的条件下,估计机器翻译系统产生的译文的质量,对机器翻译研究和应用具有很重要的价值。机器翻译译文质量估计经过最近几年的发展,取得了丰富的研究成果。该文首先介绍了机器翻译译文质量估计的背景与意义;然后详细介绍了句子级QE、单词级QE、文档级QE的具体任务目标、评价指标等内容,进一步概括了QE方法发展的三个阶段: 基于特征工程和机器学习的QE方法阶段,基于深度学习的QE方法阶段,融入预训练模型的QE方法阶段,并介绍了每一阶段中的代表性研究工作;最后分析了目前的研究现状及不足,并对未来QE方法的研究及发展方向进行了展望。 相似文献
5.
Knowledge distillation has become a key technique for making smart and light-weight networks through model compression and transfer learning. Unlike previous methods that applied knowledge distillation to the classification task, we propose to exploit the decomposition-and-replacement based distillation scheme for depth estimation from a single RGB color image. To do this, Laplacian pyramid-based knowledge distillation is firstly presented in this paper. The key idea of the proposed method is to transfer the rich knowledge of the scene depth, which is well encoded through the teacher network, to the student network in a structured way by decomposing it into the global context and local details. This is fairly desirable for the student network to restore the depth layout more accurately with limited resources. Moreover, we also propose a new guidance concept for knowledge distillation, so-called ReplaceBlock, which replaces blocks randomly selected in the decoded feature of the student network with those of the teacher network. Our ReplaceBlock gives a smoothing effect in learning the feature distribution of the teacher network by considering the spatial contiguity in the feature space. This process is also helpful to clearly restore the depth layout without the significant computational cost. Based on various experimental results on benchmark datasets, the effectiveness of our distillation scheme for monocular depth estimation is demonstrated in details. The code and model are publicly available at : https://github.com/tjqansthd/Lap_Rep_KD_Depth. 相似文献
6.
《Ceramics International》2022,48(14):19513-19526
Comprehensive control of processing techniques is primordial when fine-tuning the morphological features of titanium dioxide nanotube arrays (TNTs). This systematic review and meta-analysis compiled articles published from 2007 to date on the synthesis and growth mechanism of nanotubes fabricated via electrochemical anodization and evaluated the potential relationships between anodizing conditions and the resulting structures. Studies were gathered from the Science Direct online database, screened according to predefined criteria, and evaluated for their eligibility. Ninety-nine studies were assessed in the meta-analysis, 87 of them on tube length, 80 on tube diameter, and 33 on wall thickness. Multiple linear regression was performed to test if anodization parameters significantly predicted the resulting morphology of TiO2 nanotubular structures. Overall regression for the three responses was statistically significant (length: R2 = 0.487, p < 0.001; diameter: R2 = 0.899, p < 0.001; wall thickness: R2 = 0.792, p < 0.001). Applied potential was one of the main effects predicting all three responses (p < 0.001 in every model). Other important main predictors were anodizing time for tube length (p < 0.001), water percentage for tube diameter (p < 0.001) and ammonium fluoride (NH4F) concentration for wall thickness (p < 0.001). 相似文献
7.
8.
《Geotextiles and Geomembranes》2022,50(6):1230-1243
There are several methods for estimating bed shear stress in the literature, but comprehensive comparisons among them are limited and under specific conditions. This study compared these methods first on a bare smooth bed, and then for a single geobag on a rough bed in the interest of determining the stability of geobags used in riverbank protection structures. The geobag was filled with cement or sand and tested under different open channel flow conditions. The turbulent kinetic energy method appeared to best represent the local bed shear stress on the geobag when using the newly calibrated proportionality constants. The Reynolds stress method via extrapolation was relatively unaffected by changes to the geobags shape and measurement locations, suggesting this method inadequately represents the local bed shear stress. The Patel method and the universal law of the wall method failed to represent local bed shear stress in the rough bed cases due to instrument limitations and the breakdown of the law of the wall. This study highlights the impact of different methods on the bed shear stress estimation. 相似文献
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10.
Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE). 相似文献