Ning Wang

Human-Centric Smart Manufacturing under Industry 5.0:IIoT-Enabled Machine Learning for Real-Time Fault Identification and Adaptive Workforce Scheduling<b></b>

Yaocong Yaocong Xie, Ning Wang

This study addresses Industry 5.0's demand for human-machine collaboration and manufacturing resilience by developing machine learning models for rapid fault identification and adaptive personnel scheduling. When a production-line fault occurs, the proposed approach uses IIoT dat…Read more

One Modality to Forget Them All: Enhancing Cross-Modal Unlearning in Vision-Language Models

Sudharshan Balaji, Yili Ren, Guangjing Wang, Yimin Chen, Ning Wang

Machine unlearning is widely used to remove hazardous knowledge from large language models. Modern Vision-Language Models (VLMs), however, process both text and visual inputs, raising a fundamental security question: does unlearning in one modality transfer to the other? We prese…Read more

DAPGNet: Dynamic Adaptive Physics-Guided Graph Diffusion Network for Hyperspectral Image Classification

Pengkun Wang, Weijia Cao, Ning Wang, Xiaofei Yang

Hyperspectral image (HSI) classification requires reliable pixel-relation modeling under spectral variability, mixed pixels, and heterogeneous boundaries. Existing graph-based HSI classifiers usually construct graph topology from spatial proximity, superpixel connectivity, or lea…Read more

Deep Reinforcement Learning-Based mmWave Beam Alignment for V2I Communications

Yuanyuan Qiao, Yong Niu, Lan Su, Shiwen Mao, Ning Wang, Zhangdui Zhong, et al.

Recent Advances in Machine Learning for Network Automation in the O-RAN

Mutasem Q. Hamdan, Haeyoung Lee, Dionysia Triantafyllopoulou, Rúben Borralho, Abdulkadir Kose, Esmaeil Amiri, et al.

The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces disaggregation and virtualization, enabling network operators to d…Read more

Landfill Waste Segregation Using Transfer and Ensemble Machine Learning: A Convolutional Neural Network Approach

Angelika Sita Ouedraogo, Ajay Kumar, Ning Wang

Waste disposal remains a challenge due to land availability, and environmental and health issues related to the main disposal method, landfilling. Combining computer vision (machine learning) and robotics to sort waste is a cost-effective solution for landfilling activities limit…Read more

Deep learning preconditioned methods for frequency-domain acoustic wave equation with their wavefield simulations

Chao Lang, Ning Wang, Shi-Li Pang, Can Wang, Zi-Xian Niu