Abstract: Metal halide perovskite solar cells (PSCs) have made substantial progress in power conversion efficiency (PCE) and stability in the past decade thanks to the advancements in perovskite ...

Abstract: Maxwell's equations are replaced by a set of finite difference equations. It is shown that if one chooses the field points appropriately, the set of finite difference equations is applicable ...

This book presents an original generalized transmission line approach associated with non-resonant structures that exhibit larger bandwidths, lower loss, and higher design flexibility. It is based on ...

Abstract: The maneuvering of a large-scale unmanned aerial vehicle (UAV) swarm, notable for flexible flight with collision-free, is still challenging due to the significant number of UAVs and the ...

Abstract: Emerging applications, such as autonomous driving and Internet of Things (IoT) services put forward the demand for simultaneous sensing and communication functions in the same system.

Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past ...

Abstract: In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly ...

Abstract: Real-time image dehazmg is crucial for applications such as autonomous driving, surveillance, and remote sensing, where haze can significantly reduce visibility. However, many deep learning ...

Abstract: In addition to enhancing wireless communication coverage quality, reconfigurable intelligent surface (RIS) technique can also assist in positioning. In this work, we consider RIS-assisted ...

Abstract: Graph deep learning (GDL) has demonstrated impressive performance in predicting population-based brain disorders (BDs) through the integration of both imaging and non-imaging data. However, ...

Abstract: Object detection methods using deep convolutional neural networks (CNNs) have derived major advances in normal images. However, such success is hardly achieved with adverse weather due to a ...

Abstract: Load forecasting and renewable energy forecasting are fundamental for the optimization and scheduling of new power systems, which play a crucial role in ensuring the safe, stable, and ...