In recent years, industrial manufacturing has undergone massive technological changes that embrace digitalization and automation towards the vision of intelligent manufacturing plants. With the aim of maximizing efficiency and profitability in production, an important goal is to enable flexible manufacturing, both, for the customer (desiring more individualized products) and for the manufacturer (to adjust to market demands). Manufacturing-as-a-service can support this through manufacturing plants that are used by different tenants who utilize the machines in the plant, which are offered by different providers. To enable such pay-per-use business models, Distributed Ledger Technology (DLT) is a viable option to establish decentralized trust and traceability. Thus, in this paper, we study potential DLT technologies for efficient and intelligent integration of DLT-based solutions in manufacturing environments. We propose a general framework to adapt DLT in manufacturing, and then we introduce the use case of shared manufacturing, which we utilize to study the communication and computation efficiency of selected DLTs in resource-constrained wireless IoT networks.
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http://dx.doi.org/10.1038/s41598-022-22612-3 | DOI Listing |
Risk Anal
January 2025
Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China.
Vaccination is the most effective method of preventing and controlling the transmission of infectious diseases within populations. However, the phenomenon of waning immunity can induce periodic fluctuations in epidemic spreading. This study proposes a coupled epidemic-vaccination dynamic model to analyze the influence of immunity waning on the epidemic spreading within the context of voluntary vaccination.
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November 2024
Management Science and Information Systems Department, Rutgers University, Newark, NJ 07102-3122 USA.
Interest in supporting Federated Learning (FL) using blockchains has grown significantly in recent years. However, restricting access to the trained models only to actively participating nodes remains a challenge even today. To address this concern, we propose a methodology that incentivizes model parameter sharing in an FL setup under Local Differential Privacy (LDP).
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August 2024
Chief Medical Officer, GuardianMedx, Las Vegas, Nevada.
Web 3.0 represents the next significant evolution of the internet that embodies the underlying decentralized network architectures, distributed ledgers, and advanced AI capabilities. Though the technologies are maturing rapidly, considerable barriers exist to high-scale adoption.
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August 2024
ChainAim, Newington, Connecticut, USA.
WEB3 technologies on network architectures, distributed ledgers and decentralised artificial intelligence represent a transformative shift in how data are handled, stored and shared. These innovations promise to significantly enhance consumer data privacy rights by addressing fundamental vulnerabilities associated with traditional centralised systems and self-custody wallets. Data breaches in traditional systems operated mainly by third parties are more common, resulting in significant data leaks because of centralised storage and excessive data movement, sometimes unnecessarily.
View Article and Find Full Text PDFJMIR Form Res
December 2024
Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, United States.
Background: In interfacility transport care, a critical challenge exists in accurately matching ambulance response levels to patients' needs, often hindered by limited access to essential patient data at the time of transport requests. Existing systems cannot integrate patient data from sending hospitals' electronic health records (EHRs) into the transfer request process, primarily due to privacy concerns, interoperability challenges, and the sensitive nature of EHR data. We introduce a distributed digital health platform, Interfacility Transport Care (ITC)-InfoChain, designed to solve this problem without compromising EHR security or data privacy.
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