Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading...Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading to poor performance and privacy breaches.Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms,ensuring businesses can focus on business development.To ensure data security in cloud platforms,this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing(HD2C)model.However,the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things(IoT)in the cloud.HD2C is developed by combining Federated Learning(FL)with a Blockchain consensus algorithm to connect smart contracts with Proof of Authority.The“Data Island”problem can be solved by FL’s emphasis on privacy and lightning-fast processing,while Blockchain provides a decentralized incentive structure that is impervious to poisoning.FL with Blockchain allows quick consensus through smart member selection and verification.The HD2C paradigm significantly improves the computational processing efficiency of intelligent manufacturing.Extensive analysis results derived from IIoT datasets confirm HD2C superiority.When compared to other consensus algorithms,the Blockchain PoA’s foundational cost is significant.The accuracy and memory utilization evaluation results predict the total benefits of the system.In comparison to the values 0.004 and 0.04,the value of 0.4 achieves good accuracy.According to the experiment results,the number of transactions per second has minimal impact on memory requirements.The findings of this study resulted in the development of a brand-new IIoT framework based on blockchain technology.展开更多
Two clinical ablation protocols, 2C3L and stepwise, have been routinely used in our group to treat atrial fibrillation （AF）, but with a less than 60% long-term arrhythmia-free outcome achieved in patients. The goal ...Two clinical ablation protocols, 2C3L and stepwise, have been routinely used in our group to treat atrial fibrillation （AF）, but with a less than 60% long-term arrhythmia-free outcome achieved in patients. The goal of this study was to examine the underlying mechanism of low success in clinical outcome. MRI images from one patient were used to reconstruct a human atrial anatomical model, and fibrotic tissue was manually added to represent the arrhythmia substrate. AF was induced with standard protocols used in clinical practice. 2C3L and stepwise were then used to test the efficacy of arrhythmia termination in our model. The results showed that re-entries induced in our model could not be terminated by using either 2C3L or the stepwise protocol. Although some of the induced re-entries were terminated, others emerged in new areas. Ablation using only the 2C3L or stepwise method was not sufficient to terminate all re-entries in our model, which may partially explain the poor long-term arrhythmiafree outcomes in clinical practice. Our findings also suggest that computational heart modelling is an important tool to assist in the establishment of optimal ablation strategies.展开更多
文摘Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading to poor performance and privacy breaches.Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms,ensuring businesses can focus on business development.To ensure data security in cloud platforms,this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing(HD2C)model.However,the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things(IoT)in the cloud.HD2C is developed by combining Federated Learning(FL)with a Blockchain consensus algorithm to connect smart contracts with Proof of Authority.The“Data Island”problem can be solved by FL’s emphasis on privacy and lightning-fast processing,while Blockchain provides a decentralized incentive structure that is impervious to poisoning.FL with Blockchain allows quick consensus through smart member selection and verification.The HD2C paradigm significantly improves the computational processing efficiency of intelligent manufacturing.Extensive analysis results derived from IIoT datasets confirm HD2C superiority.When compared to other consensus algorithms,the Blockchain PoA’s foundational cost is significant.The accuracy and memory utilization evaluation results predict the total benefits of the system.In comparison to the values 0.004 and 0.04,the value of 0.4 achieves good accuracy.According to the experiment results,the number of transactions per second has minimal impact on memory requirements.The findings of this study resulted in the development of a brand-new IIoT framework based on blockchain technology.
基金The work was supported by the CAMS Fund of the Nonprofit Central Research Institutes （No. 2016ZX330015）, National Natural Science Foundation of China （No. 11421202） and the 111 Project （No. B13003）.
文摘Two clinical ablation protocols, 2C3L and stepwise, have been routinely used in our group to treat atrial fibrillation （AF）, but with a less than 60% long-term arrhythmia-free outcome achieved in patients. The goal of this study was to examine the underlying mechanism of low success in clinical outcome. MRI images from one patient were used to reconstruct a human atrial anatomical model, and fibrotic tissue was manually added to represent the arrhythmia substrate. AF was induced with standard protocols used in clinical practice. 2C3L and stepwise were then used to test the efficacy of arrhythmia termination in our model. The results showed that re-entries induced in our model could not be terminated by using either 2C3L or the stepwise protocol. Although some of the induced re-entries were terminated, others emerged in new areas. Ablation using only the 2C3L or stepwise method was not sufficient to terminate all re-entries in our model, which may partially explain the poor long-term arrhythmiafree outcomes in clinical practice. Our findings also suggest that computational heart modelling is an important tool to assist in the establishment of optimal ablation strategies.
