Large-scale graphs usually exhibit global sparsity with local cohesiveness,and mining the representative cohesive subgraphs is a fundamental problem in graph *** k-truss is one of the most commonly studied cohesive su...
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Large-scale graphs usually exhibit global sparsity with local cohesiveness,and mining the representative cohesive subgraphs is a fundamental problem in graph *** k-truss is one of the most commonly studied cohesive subgraphs,in which each edge is formed in at least k 2 triangles.A critical issue in mining a k-truss lies in the computation of the trussness of each edge,which is the maximum value of k that an edge can be in a *** works mostly focus on truss computation in static graphs by sequential ***,the graphs are constantly changing dynamically in the real *** study distributed truss computation in dynamic graphs in this *** particular,we compute the trussness of edges based on the local nature of the k-truss in a synchronized node-centric distributed *** decomposing the trussness of edges by relying only on local topological information is possible with the proposed distributed decomposition ***,the distributed maintenance algorithm only needs to update a small amount of dynamic information to complete the *** experiments have been conducted to show the scalability and efficiency of the proposed algorithm.
Data dependencies, such as functional dependencies (FDs), have been long recognized as integrity constraints in databases [42]. They are firstly utilized in database design [3]. Conventionally, data dependen...
The rapid development of artificial intelligence and big data has enabled the deployment of federated learning (FL) in the Industrial Internet of Things (IIoT). In FL, IIoT devices (as clients) can collaboratively tra...
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Video Question Answering (VideoQA) tasks require not only correct answers but also visual evidence. The "localize-then-answer" strategy, while enhancing accuracy and interpretability, faces challenges due to...
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In recent years, with the aging population and the increasing incidence of natural cavity diseases and cancer tumors, the demand for minimally invasive surgery has risen. This, in turn, requires robotic arms with grea...
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The hydrovoltaic device（HD） based on silicon nanowires（SiNWs） is a promising green energy technology;however, efficient carrier collection remains a key challenge that limits the output performance of SiNW-based H...
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The hydrovoltaic device（HD） based on silicon nanowires（SiNWs） is a promising green energy technology;however, efficient carrier collection remains a key challenge that limits the output performance of SiNW-based HDs. In this study, we propose using conductive microspheres as the top electrode to enhance carrier collection and improve the power output of SiNW HDs. Stacked nickel-coated polystyrene microspheres conformally contact the top surface of the SiNW array,facilitating efficient carrier collection from individual SiNWs and enabling effective parallel connection of multiple SiNW hydrovoltaic microunits. Optimal microsphere parameters, specifically a 10 μm diameter and 2.8 mg cm-2deposition density,are identified, balancing the positive effects of charge collection with the negative impact of water microflow induced by microsphere deposition. After optimization, the open-circuit voltage of SiNW HDs increases by 21%, and the maximum output power density rises by 49%, from 0.67 V and 8.2 μW cm-2in HDs without the microsphere electrode to 0.81 V and 12.2 μW cm-2in HDs with the microsphere electrode. This work provides a simple yet effective solution to the carrier collection problem in SiNW HDs, offering a significant step forward in the development and application of high-performance SiNW HDs.
December 2019 witnessed the outbreak of a novel coronavirus, thought to have started in the Chinese city of Wuhan. The situation worsened owing to its quick spread across the globe, leading to a worldwide pandemic tha...
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Graph convolutional neural networks, which aim to learn the spatial correlation within multivariate time-series data, have achieved significant advancements in traffic prediction. Despite the proliferation of various ...
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The robust human representation embedding is the key challenge of the person-identification task. Although the previous methods achieve competitive results, they still depend on the appearance feature which can be fai...
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Pretrained models for code have exhibited promising performance across various code-related tasks, such as code summarization, code completion, code translation, and bug detection. However, despite their success, the ...
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