Abstract: Procrastination, the action of delaying or postponing something, is a well-known phenomenon that is relatable to all. While it has been studied in academic settings, little is known about ...

Abstract: Electrical load forecasting plays a crucial role in decision-making for power systems. The integration of renewable energy sources and the occurrence of external events, such as the COVID-19 ...

Abstract: Orthognathic surgery is applied to restore esthetical facial profile and functional occlusion for patients with dentofacial deformity. Virtual surgical planning (VSP) is indispensable for ...

Abstract: Gallium nitride (GaN) power semiconductors are being explored as promising alternatives for the next generation of high-power traction inverters, suitable for both high- and low-voltage ...

Abstract: In this paper, a reinforcement learning (RL) based fault tolerant control (FTC) strategy is investigated for the bleed air temperature control system (BATCS) of an aero-engine with time ...

Abstract: Classical beamforming algorithms face challenges such as increased complexity with more users and base station antennas (BSAs), as well as the requirement of accurate channel state ...

Abstract: In smart grids, smart meters periodically collect users’ fine-grained multi-dimensional energy data, which poses great concerns on users’ privacy and security. Existing privacy-preserving ...

Abstract: Pansharpening in the presence of thin clouds is a practical yet under-explored problem, as it requires both recovery of spatial details and correction of cloud-induced spectral distortions.

Abstract: Estimating cognitive states from oculomotor data is challenging due to context-dependency and metric ambiguity. This paper proposes a conceptual dynamic numerical framework that integrates ...

Abstract: We identify topological imbalance in semi-supervised node classification, where varying neighborhood structures of labeled nodes cause biased learning. Directionality exacerbates this ...

Abstract: Data uncertainty refers to the degree of uncertainty in model predictions caused by data variability, challenging the model robustness in multimedia applications. The increased variability ...

Abstract: Ina direct current (dc) distribution network, the modular multilevel high-frequency dc converter (MDCC) can achieve electrical isolation, voltage conversion and power transmission between ...