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382 results on '"Liu, Changyong"'

1. Numerical analysis of the dynamic response of an open landslide slope under seismic loading

Author

Li, Xiangling, Liu, Changyong, Zheng, Zheng, Editor-in-Chief, Xi, Zhiyu, Associate Editor, Gong, Siqian, Series Editor, Hong, Wei-Chiang, Series Editor, Mellal, Mohamed Arezki, Series Editor, Narayanan, Ramadas, Series Editor, Nguyen, Quang Ngoc, Series Editor, Ong, Hwai Chyuan, Series Editor, Sun, Zaicheng, Series Editor, Ullah, Sharif, Series Editor, Wu, Junwei, Series Editor, Zhang, Baochang, Series Editor, Zhang, Wei, Series Editor, Zhu, Quanxin, Series Editor, Zheng, Wei, Series Editor, Liu, Peng, editor, Bilgin, Hüseyin, editor, Yang, Jialing, editor, and Hu, Bin, editor

Published
2024
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27. On bound states in Quantum Field Theory

Author

Liu, Changyong

Subjects
High Energy Physics - Theory
Abstract

In this paper, a new method to describe the energy spectrums of bound states in Quantum Field Theory is presented. We point out that the fundamental field and its dual soliton combine together to form bound states and the soliton corresponds to the ghost particle in our regularization scheme which takes advantage of dimensional regularization and Pauli-Villars regularization. Based on this point of view, we discuss the bound states of massive Thirring model, the positronium ($e^+e^-$) in QED and the vector meson in QCD. We also give a new way to obtain the mass of soliton (quantum soliton) from the stationary condition (gap equation). Our results agree with experimental data to high precision. We argue that the hypothetic $X_{17}$ particle in decay of $\rm{{}^8 Be}$ and $\rm{{}^4 He}$ is a soliton. For vector meson, we find the squared masses of $\rho$ resonances are $m^2(n)\sim (an^{1/3}-b)^2$ which coincide well with experiments., Comment: 18 pages, 11 figures

Published
2018

46. Monocular 3D Multi-Person Pose Estimation for On-Site Joint Flexion Assessment: A Case of Extreme Knee Flexion Detection.

Author

Yan, Guihai, Yan, Haofeng, Yao, Zhidong, Lin, Zhongliang, Wang, Gang, Liu, Changyong, and Yang, Xincong

Subjects
BUILDING sites, COMPUTER vision, SUPERVISORS, DEEP learning, LABOR productivity, POSE estimation (Computer vision)
Abstract

Work-related musculoskeletal disorders (WMSDs) represent a significant health challenge for workers in construction environments, often arising from prolonged exposure to ergonomic risks associated with manual labor, awkward postures, and repetitive motions. These conditions not only lead to diminished worker productivity but also incur substantial economic costs for employers and healthcare systems alike. Thus, there is an urgent need for effective tools to assess and mitigate these ergonomic risks. This study proposes a novel monocular 3D multi-person pose estimation method designed to enhance ergonomic risk assessments in construction environments. Leveraging advanced computer vision and deep learning techniques, this approach accurately captures and analyzes the spatial dynamics of workers' postures, with a focus on detecting extreme knee flexion, a critical indicator of work-related musculoskeletal disorders (WMSDs). A pilot study conducted on an actual construction site demonstrated the method's feasibility and effectiveness, achieving an accurate detection rate for extreme flexion incidents that closely aligned with supervisory observations and worker self-reports. The proposed monocular approach enables universal applicability and enhances ergonomic analysis through 3D pose estimation and group pose recognition for timely interventions. Future efforts will focus on improving robustness and integration with health monitoring to reduce WMSDs and promote worker health. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Automated Defect Detection on Dry-Hanging Stone Curtain Walls through Colored Point Clouds.

Author

Yao, Zhidong, Li, Xuelai, Yan, Guihai, Lin, Zhongliang, Wang, Gang, Liu, Changyong, and Yang, Xincong

Subjects
BUILDING envelopes, STONE, BUILDING performance, POINT cloud, ARTIFICIAL intelligence
Abstract

Stone curtain walls are widely used in contemporary architectures; however, their regular inspection is always labor-intensive, time-consuming, and hazardous due to the complex and enclosed spatial structure of these high-rise building enclosures. To address this issue, this study proposes an automated and novel inspection method, which is composed of the following three steps: First, we utilize 3D laser scanning technology to capture colored point cloud data of the stone curtain wall system; subsequently, by extracting and processing the integration of color and depth information, the stone panels and end sealants are precisely segmented; finally, various defects, such as cracks, unevenness, and irregularities, are automatically identified through artificial intelligence algorithms in a timely manner. To validate the proposed method, an on-site experiment was carried out to demonstrate the effectiveness in detecting multiple defects concurrently on stone curtain walls. The experimental results showed that our proposed method could provide a non-contact and automated inspection alternative for all the stone curtain walls with a high accuracy of anomaly detection, facilitating rational maintenance plans and strategies to ensure the safety and performance of these modern building enclosures. [ABSTRACT FROM AUTHOR]

Published
2024
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49. An HCI-Based Cognitive Architecture for Learning Process Observation

Author

Shi, Guimin, Yang, Sheng, Liu, Changyong, Meng, Shimin, Luo, Zhiming, and Li, Shaozi

Abstract

In this article, a cognitive framework for observing learning activities based on human-computer coupling is proposed. The observation is based on the vectorization of a learning situation along with human-computer interaction factors. An evolutionary high-dimensional topology of learning cognitive flow is introduced for human-computer interaction. In addition, the authors have selected a tree topology as the topological structure of a low-dimensional learning space to process the observations for online learning. Furthermore, the mechanism for the BSM (brain cognitive body-situation of coupling-manifold of information) the coupling morphism is presented. The principle for the coupled observation of objects in a cognitive or learning manifold is proposed. Finally, a special system for teaching and learning is programmed to observe and evaluate learning and mental arithmetic training processes. This system not only provides students with a new ergonomic learning model but also records the students' learning processes. Thus, the teachers can summarize the knowledge points automatically rather than manually.

Published
2020
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