In this paper, we present a parity space-based fault diagnosability analysis scheme for unmanned aerial vehicles (UAVs) with linear discrete time-varying (LDTV) dynamics. Robust residual generato ... Read More

In virtual reality, virtual weight perception allows users to perform tasks more precisely and enhances immersion. In this paper, we propose a variable offset (VO) method based on a five-finger p ... Read More

A deep neural network (DNN) is a machine learning tool that mimics the functioning of the neurons in the human brain. DNN can detect smoke and thus provide early warnings regarding wildfires befo ... Read More

As buildings become increasingly complex and aging infrastructures persist in modern cities, the risk of diverse disaster scenarios has grown significantly. To address the safety challenges assoc ... Read More

Wind turbine blades endure persistent operational stresses, including aerodynamic loads, cyclic fatigue, and environmental corrosion, leading to structural defects such as cracks, perforations, a ... Read More

Various efforts have been made to automate irrigation systems, however, there still exists a problem of an impending water crisis that was reported by the World Bank wherein the Philippines was o ... Read More

In this study, we address key limitations in RGB–depth (D) sensing systems, including depth noise, sensor misalignment, missing depth values, and performance degradation under low illumination. ... Read More

The surge in multiperson sports videos has increased the demand for automated behavior recognition systems capable of understanding group-level activities. Recognizing collective behaviors such a ... Read More

In intelligent healthcare monitoring, vision-based sensing offers a practical route for non-contact medical diagnostics, yet tongue-coating assessment in traditional Chinese medicine (TCM)-relate ... Read More

Reliable emotion recognition from acoustic sensor signals is a pivotal yet challenging component for achieving natural and empathetic human–robot interaction. We propose a dedicated, deployable ... Read More

Sensor noise significantly degrades the trajectory tracking accuracy of robotic manipulators. In this paper, we propose a closed-loop control strategy based on multisensor fusion and an extended ... Read More

As machine learning (ML) models are increasingly used in high-stakes domains, improving both predictive performance and fairness has become an important research problem. Existing explanation-bas ... Read More