While semantic communication has become an active area of research, a unifying theoretical foundation remains elusive. In this letter, we aim to partly fill this gap by providing a new perspective on goal-oriented sem...
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Recent progress made in the prediction,characterisation,and mitigation of multipactor discharge is reviewed for single‐and two‐surface ***,an overview of basic concepts including secondary electron emission,electron...
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Recent progress made in the prediction,characterisation,and mitigation of multipactor discharge is reviewed for single‐and two‐surface ***,an overview of basic concepts including secondary electron emission,electron kinetics under the force law,multipactor susceptibility,and saturation mechanisms is provided,followed by a discus-sion on multipactor mitigation *** strategies are categorised into two broad areas–mitigation by engineered devices and engineered radio frequency(rf)*** approach is useful in different *** advances in multipactor physics and engineering during the past decade,such as novel multipactor prediction methods,un-derstanding space charge effects,schemes for controlling multipacting particle trajec-tories,frequency domain analysis,high frequency effects,and impact on rf signal quality are *** addition to vacuum electron multipaction,multipactor‐induced ioni-zation breakdown is also reviewed,and the recent advances are summarised.
Distributed energy resources, especially residential behind-the-meter photovoltaics (BTM PV), have been playing increasingly important roles in modern smart grids. Residential netload, which is closely tied with custo...
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This paper reports on ongoing and innovative research in the area of eXplainable Artificial Intelligence (XAI). A classical XAI task is considered as finding an explanation of the model generated via Machine Learning ...
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The design and implementation of sensing and power mechanisms in microdevices for biomedical applications present significant challenges. In this context, we introduce a new three-layer bi-metallic metamaterial absorb...
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Autonomous systems rely on artificial intelligence to perform their tasks more effectively. With the increasing complexity of tasks, it is essential to provide a structured way to define tasks. This paper explores a n...
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3D object detection is crucial for applications like autonomous driving and robotics. However, in real-world environments, variations in sensor data distribution due to sensor upgrades, weather changes, and geographic...
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3D object detection is crucial for applications like autonomous driving and robotics. However, in real-world environments, variations in sensor data distribution due to sensor upgrades, weather changes, and geographic differences can adversely affect detection performance. Semi-Supervised Domain Adaptation (SSDA) aims to mitigate these challenges by transferring knowledge from a source domain, abundant in labeled data, to a target domain where labels are scarce. This paper presents a new SSDA method referred to as Target-Oriented Domain Augmentation (TODA) specifically tailored for LiDAR-based 3D object detection. TODA efficiently utilizes all available data, including labeled data in the source domain, and both labeled data and unlabeled data in the target domain to enhance domain adaptation performance. TODA consists of two stages: TargetMix and AdvMix. TargetMix employs mixing augmentation accounting for LiDAR sensor characteristics to facilitate feature alignment between the source-domain and target-domain. AdvMix applies point-wise adversarial augmentation with mixing augmentation, which perturbs the unlabeled data to align the features within both labeled and unlabeled data in the target domain. Our experiments conducted on the challenging domain adaptation tasks demonstrate that TODA outperforms existing domain adaptation techniques designed for 3D object detection by significant margins. IEEE
Artificial intelligence (AI)-based learning control plays a critical role in the evolution of intelligent control, particularly for complex network systems. Traditional intelligent control methods assume the agent can...
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Climate-induced extreme weather events, such as floods and heatwaves, pose significant challenges to the resilience of urban power distribution grids. This paper examines the outage and restoration dynamics of Pittsbu...
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Microgrids(MGs)with high penetration of dis-tributed generators may cause congestion in the distribution net-work during *** address this issue,this paper proposes a two-time-scale congestion management scheme for mul...
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Microgrids(MGs)with high penetration of dis-tributed generators may cause congestion in the distribution net-work during *** address this issue,this paper proposes a two-time-scale congestion management scheme for multiple MGs integrated distribution ***-ahead hourly-scale dynamic congestion management(DCM)is formulated as a con-strained optimization problem,which can be solved by utilizing the proposed alternating iterative method,with the privacy of both the distribution network and MGs being *** sub-hourly-scale contract energy tracking aims at fully utilizing the controllable resources of the MGs to minimize the difference of the contract and actual exchanged energy between the MG and distribution *** coordination of the proposed two timescales of management schemes,the MGs integrated distribution networks can operate economically while avoiding the probable congestion predicament with high penetration of renewable *** studies with a i3-bus system MGs integrated distribution network demonstrated this proposed approach is effective to manage the congestion problem in the distribution network,while the energy tracking approach can improve the welfare of the MGs engaged in energy contracts ***-Alternating giterativemethod,congestion management,microgrids,renewable energy integration.
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