Dapeng Li

Enhancing VIKOR for MAGDM with PUIL q-ROFSs: Addressing Ambiguity and Uncertainty in Decision-Making

Jing Guo, Haifeng Zhao, Hui Xu, Dapeng Li

Effectively evaluating educational curricula requires capturing experts’ nuanced linguistic judgments, which often exhibit probabilistic uncertainty and cognitive asymmetry that existing fuzzy models struggle to represent. This study addresses the critical challenge of processing such unbalanced and probabilistic linguistic information in multi-attribute group …

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Hybrid-Action MADRL-based Scheduling for Task Offloading and Trajectory Planning in Multi-UAV Systems with Latency Minimization

Wenxue Sun, Haitao Zhao, Miao Liu, Dapeng Li et autres

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Sustaining Connectivity From the Sky: A Feasibility-Driven MARL Strategy for Communication-Computing Coordination in Multi-UAV Emergency Networks

Bangning Xu, Haitao Zhao, Miao Liu, Baoming Li et autres

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LEHiD: LLM-Empowered Hierarchical DRL Framework for Path Planning in UAV Networks

Jie Zhang, Hao Huang, Dapeng Li, Haitao Zhao

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PRANet: Pathological relationship perception and dual attention guided network for diabetic retinopathy grading

Yanfei Guo, Hangli Du, Zhenhua Zhang, Yuncui Wang et autres

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AttMamba: Integrating Dual-Attention and Vision Mamba for Diabetic Retinopathy Grading

Yanfei Guo, Chenglong Yang, Zhenhua Zhang, Yuanke Zhang et autres

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Multi-Task Multi-Agent Reinforcement Learning for Collaborative Radio Mapping and Navigation in Cellular-Connected UAV Networks

Haitao Zhao, Hao Huang, Dapeng Li, Yiyang Ni et autres

In cellular-connected Unmanned Aerial Vehicle (UAV) communications, the advantages of UAVs as aerial mobile users are significant. UAVs can be supported by cellular networks and obtain more reliable connectivity during a flight. However, a cellular-connected multi-UAV system is prone to encounter the …

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Development and validation of an interpretable machine learning model using routine laboratory biomarkers to stratify severe pneumonia risk in young children

Wei Cui, Xinlv Zhang, Yang Chen, Guomiao Zhang et autres

• Interpretable ML framework: Stratifying pediatric severe pneumonia risk effectively. • Clinical utility: Achieving high performance for admission diagnosis and progression prediction. • Translational implication: Deploying clinical decision support with case-level interpretability. • Novelty biomarkers: Identifying chloride and glucose for high-risk pediatric …

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Robust Power Control for Dual-Polarized Holographic MIMO Enabled ISAC Systems

Ziling Shao, Xiao Zhao, Zhongyao Liu, Xi Zhu et autres

This paper explores the potential of dual-polarized (DP) technology with holographic multiple-input multi-output (HMIMO) surfaces. The primary goal is to mitigate the mutual interference between communication and sensing signals in integrated sensing and communication (ISAC) systems. By leveraging distinct polarization resources, DP …

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Plant-derived exosomes as bioactive compounds carriers for precision nutrition

Yannan Chen, Yuanyuan Liu, Hong Gao, Qian Qu et autres

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Model-based Multi-agent Mean-field Reinforcement Learning Based on Conditional Generation Adversarial Network Algorithm

Liubin Song, Daoxing Guo, Ao Wang, Dapeng Li et autres

In the model-based multi-agent mean-field upper-confidence reinforcement learning ($\mathbf{M}^{\mathbf{3}}$-UCRL) framework, the large agent population and the environment’s complexity and variability introduce significant inaccuracies into the dynamics model’s next-state predictions.We propose a model-based multi-agent mean-field reinforcement learning based on conditional generative adversarial network …

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SBA-Driven RAN Exposure Architecture for 6G and Ecosystem Integration

Yang Li, Yin Gao, Dapeng Li

To enable RAN capability exposure in 6G, this paper introduces RAN exposure function (REF) that facilitates secure and controlled access to radio access network (RAN) services and resources for external entities. Three novel service-based architecture (SBA)-driven RAN capability exposure architectures are proposed, …

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