PRIVACY AND TRUST REDEFINED IN FEDERATED MACHINE LEARNING

Privacy and Trust Redefined in Federated Machine Learning

A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures.In situations with highly sensitive data such as healthcare records, accessing CONCEALER this information is challenging and often prohibited.Luckily, privacy-preserving technologies have been developed to overcome this hurdle by di

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Chain mediations of perceived social support and emotional regulation efficacy between role stress and compassion fatigue: insights from the COVID-19 pandemic

BackgroundNurses at the frontline faced high risks of the COVID-19 infection, undertook lip balm heavy workloads of patient care, and experienced tremendous stress that often led to compassion fatigue.AimThis study was to explore the role of positive psychosocial resources (i.e., perceived social support and emotional regulation efficacy) in the re

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A Blockchain-Based Framework for Supply Chain Provenance

The complexity of the electronics 6.17 supply chain has grown significantly due to the expansion of globalization in the 21st century.Electronic parts are now manufactured, distributed, and sold globally.Ensuring the security and integrity of the supply chain has become extremely challenging due to the widespread infiltration of untrusted hardware,

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