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1,967 results on '"Xie, Zhong"'

1. Analog Beamforming Enabled Multicasting: Finite-Alphabet Inputs and Statistical CSI

Author

Wu, Yanjun, Xie, Zhong, Xie, Zhuochen, Ouyang, Chongjun, and Liang, Xuwen

Subjects
Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing
Abstract

The average multicast rate (AMR) is analyzed in a multicast channel utilizing analog beamforming with finite-alphabet inputs, considering statistical channel state information (CSI). New expressions for the AMR are derived for non-cooperative and cooperative multicasting scenarios. Asymptotic analyses are conducted in the high signal-to-noise ratio regime to derive the array gain and diversity order. It is proved that the analog beamformer influences the AMR through its array gain, leading to the proposal of efficient beamforming algorithms aimed at maximizing the array gain to enhance the AMR., Comment: 5 pages

Published
2024

3. Small but Mighty: Enhancing 3D Point Clouds Semantic Segmentation with U-Next Framework

Author

Zeng, Ziyin, Hu, Qingyong, Xie, Zhong, Zhou, Jian, and Xu, Yongyang

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We study the problem of semantic segmentation of large-scale 3D point clouds. In recent years, significant research efforts have been directed toward local feature aggregation, improved loss functions and sampling strategies. While the fundamental framework of point cloud semantic segmentation has been largely overlooked, with most existing approaches rely on the U-Net architecture by default. In this paper, we propose U-Next, a small but mighty framework designed for point cloud semantic segmentation. The key to this framework is to learn multi-scale hierarchical representations from semantically similar feature maps. Specifically, we build our U-Next by stacking multiple U-Net $L^1$ codecs in a nested and densely arranged manner to minimize the semantic gap, while simultaneously fusing the feature maps across scales to effectively recover the fine-grained details. We also devised a multi-level deep supervision mechanism to further smooth gradient propagation and facilitate network optimization. Extensive experiments conducted on three large-scale benchmarks including S3DIS, Toronto3D, and SensatUrban demonstrate the superiority and the effectiveness of the proposed U-Next architecture. Our U-Next architecture shows consistent and visible performance improvements across different tasks and baseline models, indicating its great potential to serve as a general framework for future research.

Published
2023

4. LACV-Net: Semantic Segmentation of Large-Scale Point Cloud Scene via Local Adaptive and Comprehensive VLAD

Author

Zeng, Ziyin, Xu, Yongyang, Xie, Zhong, Tang, Wei, Wan, Jie, and Wu, Weichao

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Large-scale point cloud semantic segmentation is an important task in 3D computer vision, which is widely applied in autonomous driving, robotics, and virtual reality. Current large-scale point cloud semantic segmentation methods usually use down-sampling operations to improve computation efficiency and acquire point clouds with multi-resolution. However, this may cause the problem of missing local information. Meanwhile, it is difficult for networks to capture global information in large-scale distributed contexts. To capture local and global information effectively, we propose an end-to-end deep neural network called LACV-Net for large-scale point cloud semantic segmentation. The proposed network contains three main components: 1) a local adaptive feature augmentation module (LAFA) to adaptively learn the similarity of centroids and neighboring points to augment the local context; 2) a comprehensive VLAD module (C-VLAD) that fuses local features with multi-layer, multi-scale, and multi-resolution to represent a comprehensive global description vector; and 3) an aggregation loss function to effectively optimize the segmentation boundaries by constraining the adaptive weight from the LAFA module. Compared to state-of-the-art networks on several large-scale benchmark datasets, including S3DIS, Toronto3D, and SensatUrban, we demonstrated the effectiveness of the proposed network.

Published
2022
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5. Photons generated by gravitional waves in the near-zone of a neutron star

Author

Feng, Chao-Jun, Guo, Ao, Xie, Zhong-Ming, and Li, Miao

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, High Energy Physics - Theory
Abstract

When a gravitational wave or a graviton travels through an electric or magnetic background, it could convert into a photon with some probability. In this paper, a dipole magnetic field is considered as this kind of background in both the Minkowski spacetime and the curved spacetime in the near-zone of a neutron star. In the former case, we find that the graviton traveling vertically rather than parallel to the background magnetic field could be more effectively converted into an electromagnetic radiation field. In the latter case, we focus on the situation, in which the graviton travels along the radial direction near a neutron star. The radius of a neutron star is about ten kilometers, so the gravitational wave with long wavelength or low frequency may bypass neutron stars by diffraction. For high frequency gravitational wave, the conversion probability is proportional to the distance square as that in the static electric or magnetic background case. The smaller the inclination angle between the dipole field and the neutron star north pole is, the larger magnetic amplitude will be. The term that described curved spacetime will slightly enhance this kind of probability. We estimate that this value is about the order of $\sim 10^{-14}- 10^{-10}$. Therefore, it is expectable that this kind of conversion process may have a potential to open a window for observing high frequency gravitational waves., Comment: 17pages,2figures

Published
2022
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31. Safety and efficacy of apatinib in patients with advanced gastric or gastroesophageal junction adenocarcinoma after the failure of two or more lines of chemotherapy (AHEAD): a prospective, single-arm, multicenter, phase IV study

Author

Li, Jin, Qin, Shukui, Wen, Lu, Wang, Junsheng, Deng, Wenying, Guo, Weijian, Jia, Tongfu, Jiang, Da, Zhang, Guifang, He, Yifu, Ba, Yi, Zhong, Haijun, Wang, Lin, Lin, Xiaoyan, Yang, Jianwei, Zhao, Jun, Bai, Yuxian, Wu, Xiangyuan, Gao, Feng, Sun, Guogui, Wu, Yongjuan, Ye, Feng, Wang, Qiong, Xie, Zhong, Yi, Tienan, Huang, Yong, Yu, Guohua, Lu, Lin, Yuan, Ying, Li, Wei, Liu, Likun, Sun, Yuping, Sun, Ying, Yin, Lifeng, and Hou, Zhiguo

Published
2023
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34. Update on the genetic diversity and population structure of Echinococcus granulosus in Gansu Province, Tibet Autonomous Region, and Xinjiang Uygur Autonomous Region, Western China, inferred from mitochondrial cox1, nad1, and nad5 sequences

Author

Shumuye, Nigus Abebe, Li, Li, Ohiolei, John Asekhaen, Qurishi, Sayed Ajmal, Li, Wen-Hui, Zhang, Nian-Zhang, Wu, Yan-Tao, Wu, Yao-Dong, Gao, Sheng-Zhi, Zhang, Fu-Heng, Tian, Xue-Qi, Tian, Wen-Jun, Fu, Yong, Wang, Xie-Zhong, Pan, Yong-Hong, Zhan, Fang, Zhang, Lin-Sheng, Guo, Ming-Kuan, Li, Wen-Dong, Fu, Bao-Quan, Yan, Hong-Bin, and Jia, Wan-Zhong

Published
2023
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44. Atomistic simulation of thermoelectric properties in cove-edged graphene nanoribbons.

Author

Xie, Zhong-Xiang, Chen, Xue-Kun, Yu, Xia, Deng, Yuan-Xiang, Zhang, Yong, Zhou, Wu-Xing, and Jia, Pin-Zhen

Subjects
*NANORIBBONS, *GREEN'S functions, *GRAPHENE, *SEEBECK coefficient, *PHONONS
Abstract

We present an atomistic simulation of thermoelectric properties in cove-edged graphene nanoribbons (CGNRs) via the nonequilibrium Green's function. Different from gapless zigzag graphene nanoribbons (ZGNRs), CGNRs exhibit a noticeable bandgap. Such a bandgap can be modulated by varying three structural parameters (namely, the width N, the distance between adjacent coves m, as well as the shortest offset n) of CGNRs, which can give rise to the transition from semiconducting to semi-metallic. Due to the less dispersive phonon bands and the decrease in the number of phonon channels of CGNRs, they are found to have the lower phonon thermal conductance than ZGNRs. Modulation of CGNRs can produce over tenfold improvement of the maximum of ZT compared to ZGNRs. This improvement is due to the promotion of the Seebeck coefficient together with the degradation of the phonon thermal conductance of CGNRs compared to ZGNRs. [ABSTRACT FROM AUTHOR]

Published
2024
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