A variable impedance decentralized control method of reconfigurable robot manipulator (RRM) with human robot collaboration (HRC) using Gaussian process-based motion intention estimation is proposed in this paper. The ...
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Organic electrode materials(OEMs)have attracted substantial attention for aqueous zinc-ion batteries(AZIBs)due to their advantages in relieving resource and environmental ***,the potential of OEMs is plagued by their ...
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Organic electrode materials(OEMs)have attracted substantial attention for aqueous zinc-ion batteries(AZIBs)due to their advantages in relieving resource and environmental ***,the potential of OEMs is plagued by their low achievable capacity and high ***,we have proposed a new concept of“co-coordination force”and designed a rigid-flexible coupling crystalline polymer that can overcome the abovementioned *** obtained crystalline polymer(BQSPNs)with multiredox centres makes the BQSPNs exist intermolecular hydrogen bonds(HB)among-C=O,-C=N,and-NH and consequently exhibits transverse two-dimensional arrays and longitudinalπ-πstacking ***,in-situ FTIR,Raman,variable temperature FTIR spectra,and 2D nuclear overhauser effect spectroscopy(NOESY)well capture the existence and evolution process of HB during the electrochemistry reaction process of BQSPNs,uncovering the effect of HB in stabilizing the structure and promoting the reaction *** a result,the BQSPNs with rationally designed“co-coordination force”deliver a high capacity of 459.6 m Ah/g and a stable cycling lifetime for more than 100,000 cycles at 10 A/g in *** results disclose the HB effect and provide a brand-new strategy for high-performance OEMs design.
In this digital era, users frequently share their thoughts, preferences, and ideas through social media, which reflect their Basic Human Values. Basic Human Values (aka values) are the fundamental aspects of human beh...
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Cloud Computing (CC) is widely adopted in sectors like education, healthcare, and banking due to its scalability and cost-effectiveness. However, its internet-based nature exposes it to cyber threats, necessitating ad...
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In this paper, we investigate adaptive dynamic programming-based quintic polynomial trajectory planning and optimal tracking control for collaborative robotic systems. According to polynomial interpolation, a quintupl...
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Multi-wavelength computational ghost imaging typically involves extensive data processing and computation, while also facing challenges such as low image reconstruction quality. Various methods have been reported for ...
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For modular robot manipulators (MRMs) with physical human-robot interaction (pHRI) tasks, an adaptive fuzzy impedance control method based on the estimation of human motion intention is proposed in this paper. Dynamic...
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The paper introduces a deep decryption method based on chaotic ghost imaging, termed Chaotic Ghost Imaging with Deep Decryption (CGI-DD). Utilizing chaotic sequences generated by the Hénon system as encryption ke...
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In the charity sector, fundraising and transparency have long been key issues. Charity NFT (Non-Fungible Token) auctions, an emerging charity fundraising model integrating blockchain and NFT concepts, bring opportunit...
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Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that h...
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Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.
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