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Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction
(Applied Soft Computing Journal, 2020-08)
In the advent of the novel coronavirus epidemic since December 2019, governments and authorities have been struggling to make critical decisions under high uncertainty at their best efforts. In computer science, this ...
A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak
(Applied intelligence, 2021)
Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 ...
Alzheimer's Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes
(Institute of Electrical and Electronics Engineers Inc., 2021)
There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 s. Alzheimer's disease (AD) is a progressive neurodegenerative disease and various machine ...
Social IoT Approach to Cyber Defense of a Deep-Learning-Based Recognition System in front of Media Clones Generated by Model Inversion Attack
(IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023)
Model inversion attack (MIA) is a cyber threat with an increasing alert even for deep-learning-based recognition systems (DLRSs). By targeting a DLRS under a scenario of attacker access to the model structure and parameters, ...
DisastDrone: A Disaster Aware Consumer Internet of Drone Things System in Ultra-Low Latent 6G Network
(IEEE Transactions on Consumer Electronics, 2023)
Internet of Things application in disaster responses and management is a predominant research domain. The introduction of the consumer drones, flying ad-hoc networks, low latency 5G, and beyond 5G produce significant ...