Yu Liu

TL;DR: In this paper , a V2V Energy Trading in Residential Microgrids (VETRM) considering multiple constraints via Bayesian game model is proposed, which results in uncertainties that the game participants determine the roles of seller or buyer that depends on the states of power surplus or lack.

TL;DR: This paper presents CrowdLOC-S, a crowdsourced seamless localization framework that combines Wi-Fi fingerprinting, GNSS, and low-cost sensors to provide accurate indoor/outdoor localization, leveraging a hybrid CNN-LSTM-MLP quality indicator and transfer learning for efficient and precise positioning in complex urban environments.

TL;DR: This paper proposes a robust DPDD-TE framework for long-term navigation using wearable inertial sensors, integrating data and physical models with Bi-LSTM algorithms for magnetic field detection, walking speed estimation, and multi-source fusion for improved accuracy.

TL;DR: This paper proposes a Bayesian game-based V2V energy trading model considering user satisfaction and low-carbon objectives, incorporating stochastic EV charging/discharging, user responsiveness, and energy exchange costs to promote green energy utilization and incentivize low-carbon electricity trading.