A critical distance parameter is introduced to describe the stress gradient effect of notched metallic structures under random vibration loadings,which is the frequency domain expression of the theory of critical dist...
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A critical distance parameter is introduced to describe the stress gradient effect of notched metallic structures under random vibration loadings,which is the frequency domain expression of the theory of critical distance(TCD)based line method *** life estimation on notched metallic structures could be carried out by combining this parameter with the spectral method for random vibration fatigue life *** fatigue experiment under random vibration loadings is conducted on two types of notched plate specimens of 7075-T6 aviation-grade aluminum alloy,where both circumstances of large and small stress gradients in the notch region are *** correlation between the calculated results given by the proposed model and the experimental fatigue life results shows the satisfactory prediction capability on random vibration fatigue life for notch conditions of both steep and mild stress distribution variations.
NJmat is a user-friendly,data-driven machine learning interface designed for materials design and *** platform integrates advanced computational techniques,including natural language processing(NLP),large language mod...
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NJmat is a user-friendly,data-driven machine learning interface designed for materials design and *** platform integrates advanced computational techniques,including natural language processing(NLP),large language models(LLM),machine learning potentials(MLP),and graph neural networks(GNN),to facili-tate materials *** platform has been applied in diverse materials research areas,including perovskite surface design,catalyst discovery,battery materials screening,structural alloy design,and molecular *** automating feature selection,predictive modeling,and result interpretation,NJmat accelerates the development of high-performance materials across energy storage,conversion,and structural ***,NJmat serves as an educational tool,allowing students and researchers to apply machine learning techniques in materials science with minimal coding *** automated feature extraction,genetic algorithms,and interpretable machine learning models,NJmat simplifies the workflow for materials informatics,bridging the gap between AI and experimental materials *** latest version(available at https://***/articles/software/NJmatML/24607893(accessed on 01 January 2025))enhances its functionality by incorporating NJmatNLP,a module leveraging language models like MatBERT and those based on Word2Vec to support materials prediction *** utilizing clustering and cosine similarity analysis with UMAP visualization,NJmat enables intuitive exploration of materials *** NJmat primarily focuses on structure-property relationships and the discovery of novel chemistries,it can also assist in optimizing processing conditions when relevant parameters are included in the training *** providing an accessible,integrated environment for machine learning-driven materials discovery,NJmat aligns with the objectives of the Materials Genome Initiative and promotes broader adoption of AI techniques in materials science.
In this paper, we explore a distributed online convex optimization problem over a time-varying multi-agent network. The network aims to minimize a global loss function through local computation and communication with ...
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In this paper, we explore a distributed online convex optimization problem over a time-varying multi-agent network. The network aims to minimize a global loss function through local computation and communication with neighboring agents. To effectively handle the optimization problem which involves highdimensional and structural constraint sets, we develop a distributed online multiple Frank-Wolfe algorithm that circumvents the expensive computational cost associated with projection operations. The dynamic regret bounds are established as O(T1-γ+ HT) with the linear oracle number O(T1+γ), which depends on the horizon（total iteration number） T, the function variation HT, and the tuning parameter 0 < γ < *** particular, when the prior knowledge of HTand T is available, the bound can be enhanced to O（1 +HT）. Moreover, we explore the significant advantages provided by the multiple iteration technique and reveal a trade-off between dynamic regret bound, computational cost, and communication cost. Finally,the performance of our algorithm is validated and compared through the distributed online ridge regression problems with two constraint sets.
The Neural Radiance Field (NeRF) method has emerged as a groundbreaking technique for human reconstruction, enabling the generation of high-quality, photorealistic rendering of reconstructed objects. Despite its promi...
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This paper proposes a noise-resistant coded aperture snapshot spectral imaging (CASSI) reconstruction algorithm based on a spectral awareness network (SANet). The method maps the snapshot compressed measurements to a ...
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Point cloud completion aims to infer complete point clouds based on partial 3D point cloud *** previous methods apply coarseto-fine strategy networks for generating complete point ***,such methods are not only relativ...
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Point cloud completion aims to infer complete point clouds based on partial 3D point cloud *** previous methods apply coarseto-fine strategy networks for generating complete point ***,such methods are not only relatively time-consuming but also cannot provide representative complete shape features based on partial *** this paper,a novel feature alignment fast point cloud completion network(FACNet)is proposed to directly and efficiently generate the detailed shapes of *** aligns high-dimensional feature distributions of both partial and complete point clouds to maintain global information about the complete *** its decoding process,the local features from the partial point cloud are incorporated along with the maintained global information to ensure complete and time-saving generation of the complete point *** results show that FACNet outperforms the state-of-theart on PCN,Completion3D,and MVP datasets,and achieves competitive performance on ShapeNet-55 and KITTI ***,FACNet and a simplified version,FACNet-slight,achieve a significant speedup of 3–10 times over other state-of-the-art methods.
Effective propagation of information among multiple users is the purpose of realizing large-scale quantum communication networks. In this paper, multicast protocols for any single, two and three qubits with real ampli...
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Effective propagation of information among multiple users is the purpose of realizing large-scale quantum communication networks. In this paper, multicast protocols for any single, two and three qubits with real amplitude and complex phase information are presented. They were realized using a composite of Greenberger–Horne–Zeilinger states as shared channels. Joint remote state preparation was the main method for completing quantum multicast. At the same time, quantum state tomography of the schemes was carried out on the IBM Quantum *** obtained states were compared with the target states by fidelity. The analysis of communication efficiency and noise effects shows that our protocol has advantages in the case of complex coefficients.
Video salient object detection(VSOD)aims at locating the most attractive objects in a video by exploring the spatial and temporal *** poses a challenging task in computer vision,as it involves processing complex spati...
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Video salient object detection(VSOD)aims at locating the most attractive objects in a video by exploring the spatial and temporal *** poses a challenging task in computer vision,as it involves processing complex spatial data that is also influenced by temporal *** the progress made in existing VSOD models,they still struggle in scenes of great background diversity within and between ***,they encounter difficulties related to accumulated noise and high time consumption during the extraction of temporal features over a long-term *** propose a multi-stream temporal enhanced network(MSTENet)to address these *** investigates saliency cues collaboration in the spatial domain with a multi-stream structure to deal with the great background diversity challenge.A straightforward,yet efficient approach for temporal feature extraction is developed to avoid the accumulative noises and reduce time *** distinction between MSTENet and other VSOD methods stems from its incorporation of both foreground supervision and background supervision,facilitating enhanced extraction of collaborative saliency *** notable differentiation is the innovative integration of spatial and temporal features,wherein the temporal module is integrated into the multi-stream structure,enabling comprehensive spatial-temporal interactions within an end-to-end *** experimental results demonstrate that the proposed method achieves state-of-the-art performance on five benchmark datasets while maintaining a real-time speed of 27 fps(Titan XP).Our code and models are available at https://***/RuJiaLe/MSTENet.
Safe batteries are the basis for next-generation application scenarios such as portable energy storage devices and electric vehicles,which are crucial to achieving carbon ***,separators,and electrodes as main componen...
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Safe batteries are the basis for next-generation application scenarios such as portable energy storage devices and electric vehicles,which are crucial to achieving carbon ***,separators,and electrodes as main components of lithium batteries strongly affect the occurrence of safety *** materials,which can respond to external stimuli or environmental change,have triggered extensive attentions recently,holding great promise in facilitating safe and smart *** review thoroughly discusses recent advances regarding the construction of high-safety lithium batteries based on internal thermal-responsive strategies,together with the corresponding changes in electrochemical performance under external ***,the existing challenges and outlook for the design of safe batteries are presented,creating valuable insights and proposing directions for the practical implementation of safe lithium batteries.
This paper aimed to propose two algorithms,DA-M and RF-M,of reducing the impact of multipath interference(MPI)on intensity modulation direct detection(IM-DD)systems,particularly for four-level pulse amplitude modulati...
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This paper aimed to propose two algorithms,DA-M and RF-M,of reducing the impact of multipath interference(MPI)on intensity modulation direct detection(IM-DD)systems,particularly for four-level pulse amplitude modulation(PAM4)***-M reduced the fluctuation by averaging the signal in blocks,RF-M estimated MPI by subtracting the decision value of the corresponding block from the mean value of a signal block,and then generated interference-reduced samples by subtracting the interference signal from the product of the corresponding MPI estimate and then weighting *** paper firstly proposed to separate the signal before decision-making into multiple blocks,which significantly reduced the complexity of DA-M and *** results showed that the MPI noise of 28 GBaud IMDD system under the linewidths of 1e5 Hz,1e6 Hz and 10e6 Hz can be effectively alleviated.
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