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arXiv 2024年

作者： Zou, Wenwen Zhang, Juan Xu, Jie Jiang, Kai Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China LSEC NCMIS Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In this work, we investigate [110] symmetric tilt FCC grain boundaries (GBs) by a recently developed approach for quasiperiodic interfaces using the Landau-Brazovskii model. On special tilt angles associated with quadratic algebraic numbers, quasiperiodic GBs exhibit generalized Fibonacci substitution rules. The transition mechanism from quasiperiodic GBs to periodic GBs is explored through sphere offsets and spectral coalescence. We also propose an accurate method to calculate the GB energy for arbitrary tilt angle and analyze the factors affecting the GB energy. The revealing GB energy change is continue along with tilt angle except periodic GBs. © 2024, CC BY-NC-SA.

关键词： Grain boundaries

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Selecting Discriminative Features for Fine-Grained Visual Classification 5th

Selecting Discriminative Features for Fine-Grained Visual Cl...

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5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Xu, Qin Li, Linyang Chen, Qian Luo, Bin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China

ISBN: (纸本)9783030414030

Fine-grained visual classification is a challenging task because of intra-class variation and inter-class similarity. Most fine-grained models predominantly focus on discriminative region localization which can effectively solve the intra-class variation, but ignore global information and the problem of inter-class similarity which easily leads to overfitting on specific samples. To address these issues, we develop an end-to-end model based on selecting discriminative features for fine-grained visual classification without the help of part or bounding box annotations. In order to accurately select discriminative features, we integrate effective information from different receptive fields to enhance the quality of features, then the features of discriminative regions detected by anchors and the whole image’s feature are jointly processed for classification. Besides, we propose a new loss function to optimize the model to find discriminative regions and prevent overfitting in the particular sample, which can simultaneously solve the problems of intra-class variation and inter-class similarity. Comprehensive experiments show that the proposed approach is superior to the state-of-the-art methods on CUB-200-2011, Stanford Cars and FGVC-Aircraft datasets. © Springer Nature Switzerland AG 2020.

关键词： Classification (of information)

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A Design of Hign Gain Wideband Circular Polarization Antenna Based on All-Metal Vivaldi Antenna 2

A Design of Hign Gain Wideband Circular Polarization Antenna...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Li, Xuemei Huang, Zhixiang Liu, Dui Wang, Chao Cheng, Yi Key Lab of Intelligent Computing and Signal Processing Ministry of Education AnHui University Heifei AnHui230000 China

This paper designs a broadband circularly polarized antenna covering the 25 GHz to 31 GHz band. The Vivaldi antenna is used as the basic structure to generate broadband electromagnetic waves;circular polarization is achieved by feeding through a circularly polarized bridge;a metal choke ring is used at the bottom to ensure the low side lobes of the antenna. The antenna consists of four basic Vivaldi antennas, a metal choke ring, a grounded substrate, and a feed network. The results show that the antenna covers the entire frequency band when the axial ratio is lower than 3 dB, and the impedance matching is better. The use of a choke ring structure ensures that the antenna electromagnetic waves are radiated upward, resulting in higher gain and lower side lobes. The highest gain in the included frequency band is 11.4 dB, and the simulation result is good. The antenna has high gain and low sidelobe characteristics. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Circular polarization

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Insight on perovskite solar cells based on double electron transport layer

Insight on perovskite solar cells based on double electron t...

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Y. Zhou X.G. Ren S.P. He Z.X. Huang Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan China Department of Education of Anhui Province Key Laboratory of Electromagnetic Environmental Sensing Anhui University Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665482271

For the past few years, perovskite solar cells have become the most promising photovoltaic devices because of its excellent photoelectric conversion efficiency. Perovskite solar cells have defects in body, interface and energy level misalignment, which lead to the increase of non-radiative recombination loss and hinder the further improvement of efficiency and stability. Therefore, the reduced loss originated from the energy level misalignment and interface defects, which is essentially important to the realization of efficient perovskite solar cells. In the research of this paper, the influence of double electron transport layer and its stepwise conduction band structure on the device performance is studied. The results show that the double-layer electron transport layer structure can improve the loss of interface energy level misalignment and provide insight into high-performance solar cells.

关键词： Band structures Photovoltaic systems Performance evaluation Microwave technology Microwave integrated circuits Spontaneous emission Photovoltaic cells

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Edge-fault-tolerance about the SM-λ property of hypercube-like networks

arXiv

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arXiv 2022年

作者： Liu, Dong Li, Pingshan Zhang, Bicheng Key Laboratory of Intelligent Computing & Information Processing Ministry of Education School of Mathematical and Computational Sicence Xiangtan University Hunan Xiangtan41105 China

The edge-fault-tolerance of networks is of great significance to the design and maintenance of networks. For any pair of vertices u and v of the connected graph G, if they are connected by min{degG(u), degG(v)} edge-disjoint paths, then G is strong Menger edge connected (SM-λ for short). The conditional edge-fault-tolerance about the SM-λ property of G, written smrλ(G), is the maximum value of m such that G − F is still SM-λ for any edge subset F with |F| ≤ m and δ(G−F) ≥ r, where δ(G−F) is the minimum degree of G−F. Previously, most of the exact value for smrλ(G) is aimed at some well-known networks when r ≤ 2, and a few of the lower bounds on some well-known networks for r ≥ 3. In this paper, we firstly determine the exact value of smrλ(G) on class of hypercube-like networks (HL-networks for short, including hypercubes, twisted cubes, crossed cubes etc.) for a general r, that is, smrλ(Gn) = 2r(n − r) − n for every Gn ∈ HLn, where n ≥ 3 and 1 ≤ r ≤ n − 2. Copyright © 2022, The Authors. All rights reserved.

关键词： Fault tolerance

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Accelerating evolutionary neural architecture search via multi-fidelity evaluation

arXiv

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arXiv 2021年

作者： Yang, Shangshang Tian, Ye Xiang, Xiaoshu Peng, Shichen Zhang, Xingyi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

Evolutionary neural architecture search (ENAS) has recently received increasing attention by effectively finding high-quality neural architectures, which however consumes high computational cost by training the architecture encoded by each individual for complete epochs in individual evaluation. Numerous ENAS approaches have been developed to reduce the evaluation cost, but it is often difficult for most of these approaches to achieve high evaluation accuracy. To address this issue, in this paper we propose an accelerated ENAS via multifidelity evaluation termed MFENAS, where the individual evaluation cost is significantly reduced by training the architecture encoded by each individual for only a small number of epochs. The balance between evaluation cost and evaluation accuracy is well maintained by suggesting a multi-fidelity evaluation, which identifies the potentially good individuals that cannot survive from previous generations by integrating multiple evaluations under different numbers of training epochs. For high diversity of neural architectures, a population initialization strategy is devised to produce different neural architectures varying from ResNetlike architectures to Inception-like ones. Experimental results on CIFAR-10 show that the architecture obtained by the proposed MFENAS achieves a 2.39% test error rate at the cost of only 0.6 GPU days on one NVIDIA 2080TI GPU, demonstrating the superiority of the proposed MFENAS over state-of-the-art NAS approaches in terms of both computational cost and architecture quality. The architecture obtained by the proposed MFENAS is then transferred to CIFAR-100 and ImageNet, which also exhibits competitive performance to the architectures obtained by existing NAS approaches. The source code of the proposed MFENAS is available at https://***/DevilYangS/MFENAS/.MSC Codes 68W50, 68T07 © 2021, CC BY.

关键词： Convolutional neural networks

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Design of Filtering Power Divider with Wide Stopband Based on QMSIW 2

Design of Filtering Power Divider with Wide Stopband Based o...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Cheng, Yi Huang, Zhixiang Wang, Zhongmiao Wang, Chao Li, Xuemei Key Lab of Ministry of Education of Intelligent Computing and Signal Processing Anhui University Hefei Anhui230601 China

A miniaturized filtering power divider with wide stopband based on quarter-mode substrate integrated waveguide (QMSIW) is proposed. The physical size of the QMSIW is reduced by 3/4 comparing with the traditional SIW structure, which can achieve miniaturization, and its electromagnetic field distribution has little effect. Using the metal interference column and the etched U-shaped groove to adjust the resonance frequency, so that the main mode and the first higher mode form a passband, meanwhile, suppressing the second higher mode. The simulation results show that the center frequency is 4.42 GHz with insertion loss of 0.45 dB, the 3-dB bandwidth is 4.12-4.63 GHz with a fractional bandwidths of 9.7%, and there is a great stopband up to 11 GHz with 15 dB rejection level. Besides, the return loss of passband is better than 17.5 dB. To verify the validity of this design, a prototype is fabricated and measured. The measured results demonstrate that it has a good agreement with the design simulations. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Substrate integrated waveguides

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A Circularly Polarized Antenna for GPS L1 band with U-Shaped-Like Strips

A Circularly Polarized Antenna for GPS L1 band with U-Shaped...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Lulu Meng Zhixiang Huang Yingsong Li School of Electronic and Information Engineering Anhui University Hefei China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

A U-shaped-like parasitic strip loading antenna is proposed and designed, which can work in L1 band of GPS with circular polarization (CP) characteristics. The antenna consists of ground plane, dielectric, radiation patch and U-shaped-like parasitic strips using a simple coaxial feed probe. The asymmetric U-shaped-like strips are to realize CP. The simulation and optimization results for the modeled directional CP antenna show that the axial ratio bandwidth is 10MHz and the impedance bandwidth is 30MHz, which can meet the requirements for GPS L1 band.

关键词： Polarization Loading Bandwidth Directive antennas Probes Loaded antennas Optimization

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Community-Aware Heterogeneous Graph Contrastive Learning 19th

Community-Aware Heterogeneous Graph Contrastive Learning

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19th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2024

作者： Li, Xinying Wu, Ling Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789819623723

Recently, heterogeneous graph contrastive learning, which can mine supervision signals from the data, has attracted widespread attention. However, most existing methods employ random data augmentation strategies to construct contrastive views, which may destroy the semantic information in heterogeneous graphs. Moreover, they often select positive and negative samples based solely on node-level proximity and overlook hard samples that are difficult to distinguish from anchors. To solve the above problems, we propose a Community-Aware Heterogeneous Graph Contrastive Learning model called CAHGCL. In particular, we design an adaptive data augmentation strategy to construct views, including feature augmentation and topology augmentation. To improve the quality of samples, we propose a dynamic sample weighting strategy based on node similarity and community information, capable of identifying both hard positive samples and hard negative samples. Finally, we introduce community-level contrast to improve community cohesion. Extensive experiments and analyses demonstrate that CAHGCL consistently outperforms state-of-the-art baselines on three datasets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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D-FGNAE: Decentralized Federated Graph Normalized AutoEncoder 19th

D-FGNAE: Decentralized Federated Graph Normalized AutoEncode...

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19th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2024

作者： Liang, Yuting Cai, Weixin Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789819623723

Graphs widely exist in real-world, and Graph Neural Networks (GNNs) have exhibited exceptional efficacy in graph learning in diverse fields. With the strengthening of data privacy protection worldwide in recent years, Federated graph neural networks (FedGNNs) have gained increasing attention in academia and industry owing to their ability to train the model in a collaborative manner while complying with the privacy protection regulations. However, in federated learning, the non-independent and identically distributed (non-IID) problem of local data possessed by multiple participants can significantly undermine model accuracy. We propose a new Decentralized Federated Graph Normalized AutoEncoder (D-FGNAE). First, the model is designed as a decentralized federated learning framework with dynamically assigned tripartite roles. This design eliminates the fixed server role found in traditional federated learning, enhances system fault tolerance, avoids single points of failure, and protects model privacy. Second, the splitting and correcting of calculation by layer in the model, along with the special design of the normalization layer, effectively tackle the non-IID problem in both the structural and attribute aspects. Experimental results on real-world networks demonstrate the effectiveness of D-FGNAE, which can achieve nearly the same accuracy as the centralized model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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