Quantum computing for healthcare: A review
In recent years, the interdisciplinary field of quantum computing has rapidly developed and
garnered substantial interest from both academia and industry due to its ability to process …
garnered substantial interest from both academia and industry due to its ability to process …
Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives
In light of the constantly changing terrain of the COVID outbreak, medical specialists have
implemented proactive schemes for vaccine production. Despite the remarkable COVID-19 …
implemented proactive schemes for vaccine production. Despite the remarkable COVID-19 …
FedCSCD-GAN: A secure and collaborative framework for clinical cancer diagnosis via optimized federated learning and GAN
Digital technologies present unrivaled opportunities to improve healthcare services
worldwide. Medical devices and hospitals are now using innovative techniques to diagnose …
worldwide. Medical devices and hospitals are now using innovative techniques to diagnose …
Reliability-aware multi-objective memetic algorithm for workflow scheduling problem in multi-cloud system
S Qin, D Pi, Z Shao, Y Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the development of cloud computing, multi-cloud systems have become common
platforms for hosting and executing workflow applications in recent years. However, the …
platforms for hosting and executing workflow applications in recent years. However, the …
Deadline-constrained cost-aware workflow scheduling in hybrid cloud
Cloud computing offers resources to users for computing and storage needs on the policy
pay-what-you-use model. A private cloud is an excellent cost-saving option because the …
pay-what-you-use model. A private cloud is an excellent cost-saving option because the …
Optimizing workload distribution in Fog-Cloud ecosystem: A JAYA based meta-heuristic for energy-efficient applications
Fog-integrated Cloud has emerged as a novel computing paradigm that brings Cloud
computing services to the network's edge in real-time, though with limited capabilities …
computing services to the network's edge in real-time, though with limited capabilities …
Knowledge-driven adaptive evolutionary multi-objective scheduling algorithm for cloud workflows
H Zhang, X Zheng - Applied Soft Computing, 2023 - Elsevier
Workflow scheduling in cloud platforms is a highly challenging issue because it faces
multiple conflicting optimization objectives and large-scale decision variables. Most of the …
multiple conflicting optimization objectives and large-scale decision variables. Most of the …
Robust optimization of multi-objective multi-cycle remanufacturing supply chain network considering incentive compatibility theory under improved algorithm
Z Wang, C Ye, J Guo - Computers & Industrial Engineering, 2024 - Elsevier
In recent years, industrial production and transportation have generated a significant amount
of carbon emissions, leading to a heightened focus on environmental resource …
of carbon emissions, leading to a heightened focus on environmental resource …
[HTML][HTML] A multi-objective medical process mining model using event log and causal matrix
Medical analytics in genetic process mining have developed models with multiple and often
conflicting criteria. Some studies have reduced the complexities inherent in multiple and …
conflicting criteria. Some studies have reduced the complexities inherent in multiple and …
Chaotic hybrid multi-objective optimization algorithm for scientific workflow scheduling in multisite clouds
A Mohammadzadeh, D Javaheri… - Journal of the Operational …, 2024 - Taylor & Francis
A cloud is made up of many data centers, with its own set of data and resources. The
reasons for employing several cloud sites to operate a workflow are that the data is already …
reasons for employing several cloud sites to operate a workflow are that the data is already …