Abstract: As we all know, the change of mode interference caused by the curvature change in multi-mode fiber (MMF) can be well represented as a fiber specklegram recorded by CCD (Charge-coupled Device ...
Abstract: Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like complex ...
Abstract: In the field of English for Academic Purposes (EAP), the role of AI-assisted language learning in developing writing skills has been extensively researched and has yielded positive outcomes.
Abstract: In this paper, a deep reinforcement learning (DRL)-based electric vehicles (EVs) management strategy is proposed to achieve peak shaving and regulate the voltage violations in distribution ...
Abstract: In massive multiple-input multiple-output (MIMO) systems, the user equipment (UE) needs to feed the channel state information (CSI) back to the base station (BS) for the following ...
Abstract: Pervasive edge computing refers to one kind of edge computing that merely relies on edge devices with sensing, storage and communication abilities to realize peer-to-peer offloading without ...
Abstract: Distant supervised relation extraction (DSRE) obtains large amounts of data cost-effectively by aligning knowledge base with natural texts but also brings noisy data. Existing methods deal ...
Abstract: Numerous significant temporal graph tasks, such as graph similarity ranking, trend analysis and anomaly detection, necessitate low-dimensional and high-order graph-level embedding in terms ...
Abstract: In this paper, a deep learning-based fault diagnosis has been proposed for improving reliability when detect faulty switches of four-level active neutral point clamped (ANPC) inverters. The ...
Abstract: Document-level biomedical relation extraction (Bio-DocRE) involves identifying relations between entities distributed across multiple sentences in biomedical literature. Most existing ...
Abstract: A network intrusion detection system (NIDS) is an important technology for cyber security. Recently, machine learning based NIDSs are being actively researched as various machine learning ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results