Qingcheng Zeng

Gromov Hyperbolicity of Substitution graphs

Qingcheng Zeng, Cheng Zeng, Yumei Xue, Huixia He

In this paper, we construct a class of infinite graphs, called substitution graphs. The vertex set consists of all finite words over a finite alphabet. A directed graph is formed by adding vertical edges connecting each word to its children and horizontal …

Abelian maximal pattern complexity of two-dimensional words

Qingcheng Zeng, Yumei Xue, Cheng Zeng

In this paper, we study the maximal pattern complexity of two-dimensional words up to Abelian equivalence. We establish a lower bound for the Abelian maximal pattern complexity of two-dimensional words that are non-doubly periodic by projection under the existence of a transverse …

Research on local buckling behavior of girth-welded X80 buried pipeline under reverse fault

Qingcheng Zeng, Yanfang Hou, Jianjun Li, Shengwen Tu

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Toward Equitable Access: Leveraging Crowdsourced Reviews to Investigate Public Perceptions of Health Resource Accessibility

Zhaoqian Xue, Guanhong Liu, Chong Zhang, Kai Wei et autres

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Effect and mechanism of warm mix agent on the rheological properties of styrene–butadiene–styrene-modified asphalt

Qingcheng Zeng, Wei Qiu, Linjian Su, Jiaqi Gao et autres

Introduction The objective of this study was to investigate the effect and reaction mechanism of warm mix agent PN2217 on the rheological properties of styrene-butadiene-styrene (SBS) asphalt. Methods Fourier transform infrared (FT-IR) spectroscopy and atomic force microscope (AFM) were conducted to reveal …

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Local buckling responses of large-diameter pipelines with girth weld misalignment

Yanfang Hou, Qingcheng Zeng, Jianjun Li, Shengwen Tu

• Buckling behavior of girth-welded pipelines under combined loading is studied. • Buckling mode shifts from inward diamond to outward bulging as pressure increases. • Strain hardening affects the limit curvature more than the limit moment. • Misalignment significantly reduces both the …

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Influence of loading path on buckling behaviour of pressurized high-strength pipelines under axial compression and bending

Yanfang Hou, Qingcheng Zeng, Jianjun Li, Shengwen Tu

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SCORE: Saturated Consensus Relocalization in Semantic Line Maps

Haodong Jiang, Yanglin Zhang, Qingcheng Zeng, Y. G. Li et autres

We present SCORE, a visual relocalization system that achieves unprecedented map compactness through semantically labeled 3D line maps. SCORE requires only 0.01%-0.1% of the storage needed by structure-based or learning-based baselines, while maintaining practical accuracy and comparable runtime. The key innovation is …

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FRACTAL DIMENSION OF SUBSTITUTION TREE NETWORKS

Qingcheng Zeng, Daohua Wang, Ying Miao

Substitution networks can be constructed inductively based on multiple colored initial graphs. In this paper, we obtain a relationship between the row sums of power of a nonnegative matrix and its spectral radius. Furthermore, we investigate the substitution networks with colored initial …

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Study of Factors Influencing the Longitudinal Mechanical Performance of Shield Tunnels Traversing Soft–Hard Heterogeneous Soils

Xiaojie Xue, Qingcheng Zeng, Yi Xie, Bohan Wu et autres

To investigate the longitudinal mechanical behavior of shield tunnels traversing soft and hard heterogeneous strata, a refined three-dimensional numerical model was developed using ABAQUS. The model includes tunnel segments, longitudinal bolts, reinforcement, longitudinal thrust, and additional loading conditions to simulate realistic mechanical …

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Consistent and Optimal Solution to Camera Motion Estimation

Guangyang Zeng, Qingcheng Zeng, Xinghan Li, Biqiang Mu et autres

Given 2D point correspondences between an image pair, inferring the camera motion is a fundamental issue in the computer vision community. The existing works generally set out from the epipolar constraint and estimate the essential matrix, which is not optimal in the …

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Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models

Weihao Xuan, Qingcheng Zeng, Heli Qi, Junjue Wang et autres

Uncertainty quantification is essential for assessing the reliability and trustworthiness of modern AI systems. Among existing approaches, verbalized uncertainty, where models express their confidence through natural language, has emerged as a lightweight and interpretable solution in large language models (LLMs). However, its …