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1,535 results on '"Wang Yanru"'

1. The Effect of the Concrete Structure Design Course Based on Formative Assessment

Author

Zhang Maoyu, Wang Yanru, Li Ruige, and Jiang Ruinian

Subjects
formative assessment, summative assessment, concrete structure design, 00-01, Mathematics, QA1-939
Abstract

The scientificity and rationality of the course assessment method, as a key factor determining whether the course objectives can be achieved, is closely related to the learning effectiveness and competence development of students. In the present study, an assessment method based on formative assessment and supplemented by summative assessment was implemented for the concrete structure design course, and a mechanism for tracking students’ learning status and providing timely feedback was constructed. We compared and analyzed students’ satisfaction, students’ overall assessment results, and students’ learning outcomes before and after the implementation of the proposed course assessment method. The result showed that there was a significant improvement in these three aspects after the implementation of the proposed course assessment method, which promoted student learning.

Published
2024
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2. Investigation on Wind-Induced Structural Damage and Preventive Measures of Low-Rise Buildings in Coastal Areas

Author

Zhang Maoyu, Tian Shengbao, Wang Yanru, Fu Bin, Zhang Chuanxiong, Zheng Shuqin, and Jiang Ruinian

Subjects
on-site investigation, wind-driven structural damage, wind countermeasures, low-rise houses, coastal areas, 00-02, Mathematics, QA1-939
Abstract

Strong winds, typhoons, and other extreme weather can cause significant damage to house structures, resulting in great harm to human life and property safety. It is imperative to prepare and strengthen infrastructure against these extreme weather conditions to minimize their impact. This paper conducts an on-site survey of low-rise houses in Cangnan County and Dongtou District, located on the south coast of Zhejiang, affected by typhoons. It summarizes the structural characteristics of houses and the damage caused by typhoons to house structures. The paper also performs a preliminary analysis of the damage mechanism of houses. Additionally, it examines wind-resistant measures used by the private sector, identifies potential issues with wind-resistant design, and proposes corresponding wind-resistant countermeasures and recommendations for low-rise houses. The research presented in this paper can be utilized for analyzing the wind damage mechanisms of low-rise houses in the future. Moreover, it offers a valuable reference for the analysis and simulation of wind damage in low-rise houses in typhoon-prone coastal areas. This research holds significant value in preventing wind damage to low-rise houses.

Published
2024
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3. MeshXL: Neural Coordinate Field for Generative 3D Foundation Models

Author

Chen, Sijin, Chen, Xin, Pang, Anqi, Zeng, Xianfang, Cheng, Wei, Fu, Yijun, Yin, Fukun, Wang, Yanru, Wang, Zhibin, Zhang, Chi, Yu, Jingyi, Yu, Gang, Fu, Bin, and Chen, Tao

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The polygon mesh representation of 3D data exhibits great flexibility, fast rendering speed, and storage efficiency, which is widely preferred in various applications. However, given its unstructured graph representation, the direct generation of high-fidelity 3D meshes is challenging. Fortunately, with a pre-defined ordering strategy, 3D meshes can be represented as sequences, and the generation process can be seamlessly treated as an auto-regressive problem. In this paper, we validate the Neural Coordinate Field (NeurCF), an explicit coordinate representation with implicit neural embeddings, is a simple-yet-effective representation for large-scale sequential mesh modeling. After that, we present MeshXL, a family of generative pre-trained auto-regressive models, which addresses the process of 3D mesh generation with modern large language model approaches. Extensive experiments show that MeshXL is able to generate high-quality 3D meshes, and can also serve as foundation models for various down-stream applications.

Published
2024

7. $L^p$ coarse Baum-Connes conjecture via $C_{0}$ coarse geometry

Author

Wang, Hang, Wang, Yanru, Zhang, Jianguo, and Zhou, Dapeng

Subjects
Mathematics - Functional Analysis, Mathematics - K-Theory and Homology, Mathematics - Operator Algebras, 46L80, 55U10, 58B34
Abstract

In this paper, we investigate the $L^{p}$ coarse Baum-Connes conjecture for $p\in [1,\infty)$ via $C_{0}$ coarse structure, which is a refinement of the bounded coarse structure on a metric space. We prove the $C_{0}$ version of the $L^{p}$ coarse Baum-Connes conjecture and thus construct an obstruction group for the conjecture. As an application, we show that the obstructions vanish under the assumption of finite asymptotic dimension, and hence give a new proof of the $L^{p}$ coarse Baum-Connes conjecture in this case., Comment: 29 pages

Published
2023

13. Persistence approximation property for $L^p$ operator algebras

Author

Wang, Hang, Wang, Yanru, Zhang, Jianguo, and Zhou, Dapeng

Subjects
Mathematics - Operator Algebras, Mathematics - K-Theory and Homology, 46L80, 58B34
Abstract

In this paper, we study the persistence approximation property for quantitative $K$-theory of filtered $L^p$ operator algebras. Moreover, we define quantitative assembly maps for $L^p$ operator algebras when $p\in [1,\infty)$. Finally, in the case of $L^{p}$ crossed products and $L^{p}$ Roe algebras, we find sufficient conditions for the persistence approximation property. This allows us to give some applications involving the $L^{p}$ (coarse) Baum-Connes conjecture., Comment: 33 pages, to appear in Chinese Ann. Math. Ser. B

Published
2022

14. Study on the Surface Charge Accumulation and Dispersion Process of Polyimide for New Cables

Author

Wang, Yanru, Tian, Yi, Huang, Xinbo, Shi, Haonan, Zhu, Guixin, Li, Zhiwei, Wang, Shuai, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, and Cai, Li Cai, editor

Published
2024
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15. Multicast Wireless Resource Optimization for High-Precision Clock Synchronization Timing Service in 5G-TSN

Author

Liu, Yue, Lu, Jizhao, Wang, Yanru, Liu, Hui, Cao, Yalin, Feng, Lei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Zhang, Yonghong, editor, Qi, Lianyong, editor, Liu, Qi, editor, Yin, Guangqiang, editor, and Liu, Xiaodong, editor

Published
2024
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16. Enhancement of IRS-Assisted Wireless Localization System in NLOS Conditions

Author

Liu, Boyu, Wang, Xudong, Gao, Feng, Wang, Yanru, Qiu, Yujie, Feng, Lei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Zhang, Yonghong, editor, Qi, Lianyong, editor, Liu, Qi, editor, Yin, Guangqiang, editor, and Liu, Xiaodong, editor

Published
2024
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30. FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction

Author

Zhu, Hao, Yang, Haotian, Guo, Longwei, Zhang, Yidi, Wang, Yanru, Huang, Mingkai, Wu, Menghua, Shen, Qiu, Yang, Ruigang, and Cao, Xun

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics
Abstract

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and the corresponding benchmark to evaluate single-view facial 3D reconstruction. By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input. FaceScape dataset releases $16,940$ textured 3D faces, captured from $847$ subjects and each with $20$ specific expressions. The 3D models contain the pore-level facial geometry that is also processed to be topologically uniform. These fine 3D facial models can be represented as a 3D morphable model for coarse shapes and displacement maps for detailed geometry. Taking advantage of the large-scale and high-accuracy dataset, a novel algorithm is further proposed to learn the expression-specific dynamic details using a deep neural network. The learned relationship serves as the foundation of our 3D face prediction system from a single image input. Different from most previous methods, our predicted 3D models are riggable with highly detailed geometry under different expressions. We also use FaceScape data to generate the in-the-wild and in-the-lab benchmark to evaluate recent methods of single-view face reconstruction. The accuracy is reported and analyzed on the dimensions of camera pose and focal length, which provides a faithful and comprehensive evaluation and reveals new challenges. The unprecedented dataset, benchmark, and code have been released at https://github.com/zhuhao-nju/facescape., Comment: Accepted to T-PAMI 2023; Extension of FaceScape(CVPR 2020); Code & data are available at https://github.com/zhuhao-nju/facescape

Published
2021

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