[HTML][HTML] TCACNet: Temporal and channel attention convolutional network for motor imagery classification of EEG-based BCI

X Liu, R Shi, Q Hui, S Xu, S Wang, R Na, Y Sun… - Information Processing …, 2022 - Elsevier
Brain–computer interface (BCI) is a promising intelligent healthcare technology to improve
human living quality across the lifespan, which enables assistance of movement and …

Deliversense: Efficient delivery drone scheduling for crowdsensing with deep reinforcement learning

X Chen, H Wang, Z Li, W Ding, F Dang, C Wu… - Adjunct proceedings of …, 2022 - dl.acm.org
Delivery drones provide a promising sensing platform for Mobile Crowdsensing (MCS) due
to their high mobility and large-scale deployment. However, due to limited battery lifetime …

Ddl: Empowering delivery drones with large-scale urban sensing capability

X Chen, H Wang, Y Cheng, H Fu, Y Liu… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Delivery drones provide a promising sensing platform for smart cities thanks to their city-
wide infrastructure and large-scale deployment. However, due to limited battery lifetime and …

ilocus: Incentivizing vehicle mobility to optimize sensing distribution in crowd sensing

S Xu, X Chen, X Pi, C Joe-Wong… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Vehicular crowd sensing systems are designed to achieve large spatio-temporal sensing
coverage with low-cost in deployment and maintenance. For example, taxi platforms can be …

Cyber vulnerabilities of energy systems

AP Zhao, S Li, C Gu, X Yan, PJH Hu… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
In an era characterized by extensive use of and reliance on information and communications
technology (ICT), cyber–physical power systems (CPPSs) have emerged as a critical …

Transformloc: Transforming mavs into mobile localization infrastructures in heterogeneous swarms

H Wang, J Xu, C Zhao, Z Lu, Y Cheng… - … -IEEE Conference on …, 2024 - ieeexplore.ieee.org
A heterogeneous micro aerial vehicles (MAV) swarm consists of resource-intensive but
expensive advanced MAVs (AMAVs) and resource-limited but cost-effective basic MAVs …

H-swarmloc: Efficient scheduling for localization of heterogeneous mav swarm with deep reinforcement learning

H Wang, X Chen, Y Cheng, C Wu, F Dang… - Proceedings of the 20th …, 2022 - dl.acm.org
Emergency rescue scenarios are considered to be high-risk scenarios. Using a micro air
vehicle (MAV) swarm to explore the environment can provide valuable environmental …

Scheduling uav swarm with attention-based graph reinforcement learning for ground-to-air heterogeneous data communication

J Ren, Y Xu, Z Li, C Hong, XP Zhang… - Adjunct Proceedings of the …, 2023 - dl.acm.org
In disaster scenarios, unmanned aerial vehicles (UAVs) can serve as mobile base stations
because of their maneuverability and synergy. However, due to constrained UAV …

Adaptive hybrid model-enabled sensing system (HMSS) for mobile fine-grained air pollution estimation

X Chen, S Xu, X Liu, X Xu, HY Noh… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Fine-grained city-scale outdoor air pollution maps provide important environmental
information for both city managers and residents. Installing portable sensors on vehicles (eg …

Electric vehicle charging planning: A complex systems perspective

AP Zhao, S Li, Z Li, Z Wang, X Fei, Z Hu… - … on Smart Grid, 2024 - ieeexplore.ieee.org
In this paper, we introduce an innovative framework for the strategic planning of electric
vehicle (EV) charging infrastructure within interconnected energy-transportation networks …