8 papers
Seamless Outdoor-Indoor Pedestrian Positioning System with GNSS/UWB/IMU Fusion: A Comparison of EKF, FGO, and PF
Jiaqiang Zhang, Xianjia Yu, Sier Ha +5
Accurate and continuous pedestrian positioning across outdoor-indoor environments remains challenging because GNSS, UWB, and inertial PDR are complementary yet individually fragile…
A Sensor-Aware Phenomenological Framework for Lidar Degradation Simulation and SLAM Robustness Evaluation
Doumegna Mawuto Koudjo Felix, Xianjia Yu, Zhuo Zou +1
Lidar-based SLAM systems are highly sensitive to adverse conditions such as occlusion, noise, and field-of-view (FoV) degradation, yet existing robustness evaluation methods either…
Emotion Recognition with Minimal Wearable Sensing: Multi-domain Feature, Hybrid Feature Selection, and Personalized vs. Generalized Ensemble Model Analysis
Muhammad Irfan, Anum Nawaz, Ayse Kosal Bulbul +4
Negative emotions are linked to the onset of neurodegenerative diseases and dementia, yet they are often difficult to detect through observation. Physiological signals from wearabl…
Lidar Variability: A Novel Dataset and Comparative Study of Solid-State and Spinning Lidars
Doumegna Mawuto Koudjo Felix, Xianjia Yu, Jiaqiang Zhang +3
Lidar technology has been widely employed across various applications, such as robot localization in GNSS-denied environments and 3D reconstruction. Recent advancements have introd…
Blockchain-Enabled Privacy-Preserving Second-Order Federated Edge Learning in Personalized Healthcare
Anum Nawaz, Muhammad Irfan, Xianjia Yu +4
Federated learning (FL) is increasingly recognised for addressing security and privacy concerns in traditional cloud-centric machine learning (ML), particularly within personalised…
Blockchain Powered Edge Intelligence for U-Healthcare in Privacy Critical and Time Sensitive Environment
Anum Nawaz, Hafiz Humza Mahmood Ramzan, Xianjia Yu +2
Edge Intelligence (EI) serves as a critical enabler for privacy-preserving systems by providing AI-empowered computation and distributed caching services at the edge, thereby minim…