The utilization of fifth-generation wireless technology (5G) and artificial intelligence (AI) has opened many paths toward making solar power utility systems run more efficiently. 5G and AI have emerged within the las...
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Healthcare resource management is essential for ensuring the quality of patient care. However, it can be a complex and costly task. This work addresses the patient admission scheduling (PAS) problem, a complex aspect ...
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Offline planning has recently emerged as a promising reinforcement learning (RL) paradigm for locomotion and control tasks. In particular, model-based offline planning learns an approximate dynamics model from the off...
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Generative artificial intelligence systems such as large language models (LLMs) exhibit powerful capabilities that many see as the kind of flexible and adaptive intelligence that previously only humans could exhibit. ...
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While passive side-channel attacks and active fault attacks have been studied intensively in the last few decades, strong attackers combining these attacks have only been studied relatively recently. Due to its simpli...
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Heterogeneous networks are promising solutions for enhancing network performance of LTE-A mobile networks by deploying small cells within the area of the serving macro cells. The goal of deploying such networks is to ...
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The accurate prediction of photovoltaic(PV)power generation is significant to ensure the economic and safe operation of power *** this end,the paper establishes a new digital twin(DT)empowered PV power prediction fram...
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The accurate prediction of photovoltaic(PV)power generation is significant to ensure the economic and safe operation of power *** this end,the paper establishes a new digital twin(DT)empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power *** this framework,considering potential data contamination in the collected PV data,a generative adversarial network is employed to restore the historical dataset,which offers a prerequisite to ensure accurate mapping from the physical space to the digital ***,a new DT-empowered PV power prediction method is ***,we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model(i.e.,a parallel network of convolution and bidirectional long short-term memory model)for capturing the hidden spatiotemporal *** proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model,resulting in enhanced prediction ***,a real dataset is conducted to assess the effectiveness of the proposed method.
3D point cloud classification requires distinct models from 2D image classification due to the divergent characteristics of the respective input data. While 3D point clouds are unstructured and sparse, 2D images are s...
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This article presents an initial solution based selective harmonic elimination (SHE) method for multilevel inverter (MLI) that aims to solve SHE problem with high accuracy while significantly reducing the number of it...
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The breach of data confidentiality, integrity, and availability due to cyberattacks can adversely impact the operation of grid-connected Photovoltaic (PV) inverters. Detecting such attacks based on their signatures or...
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