Titlebook: Web and Big Data; 4th International Jo Xin Wang,Rui Zhang,Yang-Sae Moon Conference proceedings 2020 Springer Nature Switzerland AG 2020 art

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DHBFT: Dynamic Hierarchical Byzantine Fault-Tolerant Consensus Mechanism Based on Creditreward-punishment scheme. The consensus nodes with better performances are assigned higher credit value and have higher probability to become the primary. Thirdly, we propose a dynamic promotion-demotion scheme. It enables faulty nodes to be excluded from the consensus set and reliable candidate nod

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commune

Enabling Efficient Multi-keyword Search Over Fine-Grained Authorized Healthcare Blockchain Systemhese issues become prominent since it’s more inconvenient to adjust a blockchain-based system to support efficient multi-keyword search and fine-grained authorization comparing to traditional RDBMS. To overcome the two challenges, we propose a novel multi-keyword searching scheme by establishing a s

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Improved Brain Segmentation Using Pixel Separation and Additional Segmentation Featuresrts in medical imaging to evaluate our segmentation results. We observe that our results are fairly close to the manual reference. Moreover, we observe that our model is 1.2.–2.6. faster than prior models. We conclude that our model is more efficient and accurate in practice for both infant and adul

Suppository

DHBFT: Dynamic Hierarchical Byzantine Fault-Tolerant Consensus Mechanism Based on Creditreward-punishment scheme. The consensus nodes with better performances are assigned higher credit value and have higher probability to become the primary. Thirdly, we propose a dynamic promotion-demotion scheme. It enables faulty nodes to be excluded from the consensus set and reliable candidate nod

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