73 citations · 186 across the 19 of their papers we have counts for
20 papers
RobustMAD: Evaluating Real-World Robustness of Multimodal Small Language Models for Deployable Anomaly Detection Assistants
Anushiya Arunan, Xin Li, Yan Qin +4
Multimodal industrial anomaly inspection assistants are a critical component of next-generation smart factories, enabling interactive vision-language-based querying. However, multi…
Learning More with Less: A Generalizable, Self-Supervised Framework for Privacy-Preserving Capacity Estimation with EV Charging Data
Anushiya Arunan, Yan Qin, Xiaoli Li +3
Accurate battery capacity estimation is key to alleviating consumer concerns about battery performance and reliability of electric vehicles (EVs). However, practical data limitatio…
Intelligently Augmented Contrastive Tensor Factorization: Empowering Multi-dimensional Time Series Classification in Low-Data Environments
Anushiya Arunan, Yan Qin, Xiaoli Li +1
Classification of multi-dimensional time series from real-world systems require fine-grained learning of complex features such as cross-dimensional dependencies and intra-class var…
Graph neural network-based lithium-ion battery state of health estimation using partial discharging curve
Kate Qi Zhou, Yan Qin, Chau Yuen
Data-driven methods have gained extensive attention in estimating the state of health (SOH) of lithium-ion batteries. Accurate SOH estimation requires degradation-relevant features…
A Change Point Detection Integrated Remaining Useful Life Estimation Model under Variable Operating Conditions
Anushiya Arunan, Yan Qin, Xiaoli Li +1
By informing the onset of the degradation process, health status evaluation serves as a significant preliminary step for reliable remaining useful life (RUL) estimation of complex…
LightGCNet: A Lightweight Geometric Constructive Neural Network for Data-Driven Soft sensors
Jing Nan, Yan Qin, Wei Dai +1
Data-driven soft sensors provide a potentially cost-effective and more accurate modeling approach to measure difficult-to-measure indices in industrial processes compared to mechan…
A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction
Anushiya Arunan, Yan Qin, Xiaoli Li +1
Data-driven industrial health prognostics require rich training data to develop accurate and reliable predictive models. However, stringent data privacy laws and the abundance of e…
Lithium-ion Battery Online Knee Onset Detection by Matrix Profile
Kate Qi Zhou, Yan Qin, Chau Yuen
Lithium-ion batteries (LiBs) degrade slightly until the knee onset, after which the deterioration accelerates to end of life (EOL). The knee onset, which marks the initiation of th…
A Slow-Shifting Concerned Machine Learning Method for Short-term Traffic Flow Forecasting
Zann Koh, Yan Qin, Yong Liang Guan +1
The ability to predict traffic flow over time for crowded areas during rush hours is increasingly important as it can help authorities make informed decisions for congestion mitiga…
Spatiotemporal Capsule Neural Network for Vehicle Trajectory Prediction
Yan Qin, Yong Liang Guan, Chau Yuen
Through advancement of the Vehicle-to-Everything (V2X) network, road safety, energy consumption, and traffic efficiency can be significantly improved. An accurate vehicle trajector…
Digital Twin for Real-time Li-ion Battery State of Health Estimation with Partially Discharged Cycling Data
Yan Qin, Anushiya Arunan, Chau Yuen
To meet the fairly high safety and reliability requirements in practice, the state of health (SOH) estimation of Lithium-ion batteries (LIBs), which has a close relationship with t…
A Hybrid Deep Learning Model-based Remaining Useful Life Estimation for Reed Relay with Degradation Pattern Clustering
Chinthaka Gamanayake, Yan Qin, Chau Yuen +3
Reed relay serves as the fundamental component of functional testing, which closely relates to the successful quality inspection of electronics. To provide accurate remaining usefu…
A Transferable Multi-stage Model with Cycling Discrepancy Learning for Lithium-ion Battery State of Health Estimation
Yan Qin, Chau Yuen, Xunyuan Yin +1
As a significant ingredient regarding health status, data-driven state-of-health (SOH) estimation has become dominant for lithium-ion batteries (LiBs). To handle data discrepancy a…
Transfer Learning-based State of Health Estimation for Lithium-ion Battery with Cycle Synchronization
Kate Qi Zhou, Yan Qin, Chau Yuen
Accurately estimating a battery's state of health (SOH) helps prevent battery-powered applications from failing unexpectedly. With the superiority of reducing the data requirement…
Slow-varying Dynamics Assisted Temporal Capsule Network for Machinery Remaining Useful Life Estimation
Yan Qin, Chau Yuen, Yimin Shao +2
Capsule network (CapsNet) acts as a promising alternative to the typical convolutional neural network, which is the dominant network to develop the remaining useful life (RUL) esti…
Lithium-ion Battery State of Health Estimation based on Cycle Synchronization using Dynamic Time Warping
Kate Qi Zhou, Yan Qin, Billy Pik Lik Lau +2
The state of health (SOH) estimation plays an essential role in battery-powered applications to avoid unexpected breakdowns due to battery capacity fading. However, few studies hav…
IIoT-Enabled Health Monitoring for Integrated Heat Pump System Using Mixture Slow Feature Analysis
Yan Qin, Wen-tai Li, Chau Yuen +2
The sustaining evolution of sensing and advancement in communications technologies have revolutionized prognostics and health management for various electrical equipment towards da…
A Transfer Learning-based State of Charge Estimation for Lithium-Ion Battery at Varying Ambient Temperatures
Yan Qin, Stefan Adams, Chau Yuen
Accurate and reliable state of charge (SoC) estimation becomes increasingly important to provide a stable and efficient environment for Lithium-ion batteries (LiBs) powered devices…
Time-Series Regeneration with Convolutional Recurrent Generative Adversarial Network for Remaining Useful Life Estimation
Xuewen Zhang, Yan Qin, Chau Yuen +2
For health prognostic task, ever-increasing efforts have been focused on machine learning-based methods, which are capable of yielding accurate remaining useful life (RUL) estimati…
Invariant learning based multi-stage identification for Lithium-ion battery performance degradation
Yan Qin, Chau Yuen, Stefan Adams
By informing accurate performance (e.g., capacity), health state management plays a significant role in safeguarding battery and its powered system. While most current approaches a…