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    Vision-Based Body Pose Estimation of Excavator Using a Transformer-Based Deep-Learning Model 

    Source: Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 002:;page 04024064-1
    Author(s): Ankang Ji; Hongqin Fan; Xiaolong Xue
    Publisher: American Society of Civil Engineers
    Abstract: Devoted to safety, efficiency, and productivity management on construction sites, a deep-learning method termed transformer-based mechanical equipment pose network (TransMPNet) is proposed in this research to work on images ...
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    Project-Based As-Needed Information Retrieval from Unstructured AEC Documents 

    Source: Journal of Management in Engineering:;2015:;Volume ( 031 ):;issue: 001
    Author(s): Hongqin Fan; Fan Xue; Heng Li
    Publisher: American Society of Civil Engineers
    Abstract: With the increasing complexity of architecture, engineering, and construction (AEC) projects and fast track execution of project works, written documents are becoming more and more important for project coordination, ...
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    Forecasting Construction and Demolition Waste Using Gene Expression Programming 

    Source: Journal of Computing in Civil Engineering:;2015:;Volume ( 029 ):;issue: 005
    Author(s): Zezhou Wu; Hongqin Fan; Guiwen Liu
    Publisher: American Society of Civil Engineers
    Abstract: Accurate forecasting of construction and demolition waste (CDW) generation could provide valuable information for the planning, design, and management of CDW at municipal levels. However, the lack of reliable forecasting ...
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    A Novel Quantitative Model for Determining Subsidy Levels to Accelerate the Replacement of In-Use Construction Equipment for Emissions Reduction 

    Source: Journal of Management in Engineering:;2021:;Volume ( 038 ):;issue: 002:;page 04021100
    Author(s): Zhenhua Huang; Hongqin Fan
    Publisher: ASCE
    Abstract: Subsidy incentive programs for accelerating the replacement of construction equipment are widely considered effective for reducing emissions from construction equipment. However, there are no known effective models for ...
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    Assessing Residual Value of Heavy Construction Equipment Using Predictive Data Mining Model 

    Source: Journal of Computing in Civil Engineering:;2008:;Volume ( 022 ):;issue: 003
    Author(s): Hongqin Fan; Simaan AbouRizk; Hyoungkwan Kim; Osmar Zaïane
    Publisher: American Society of Civil Engineers
    Abstract: Construction equipment constitutes a significant portion of investment in fixed assets by large contractors. To make the right decisions on equipment repair, rebuilding, disposal, or equipment fleet optimization to maximize ...
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