Background: Different modalities of quarantines were one of the main measures implemented worldwide to avoid the spread of SARS-CoV2 virus.
Aim: To analyze and compare retrospectively the implementation of the Step- to-Step plan devised by the Chilean Ministry of Health during the pandemic. To propose a decision-making path based on an artificial intelligence fuzzy system to determine confinements in specific territories.
Material And Methods: The Step-to-Step Plan threshold values such hospital network capacity, epidemic spreading, testing and contact tracing capability were modeled using fuzzy numbers and fuzzy rule-based systems.
Results: Ministry of Health's decision-making opportuneness were unrelated with the Step-to-Step Plan indicators for deconfinement. Such disagreements undermined epidemiological indicators.
Conclusions: Using an artificial intelligence system could improve decision-making transparency, emergency governance, and risk communication to the population.
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http://dx.doi.org/10.4067/s0034-98872023000200197 | DOI Listing |
Food Res Int
February 2025
State Key Laboratory of Food Science and Technology, Jiangnan University, 214122 Wuxi, Jiangsu, China; Jiangsu Province International Joint Laboratory on Fresh Food Smart Processing and Quality Monitoring, Jiangnan University, 214122 Wuxi, Jiangsu, China.
The prepared foods sector has grown rapidly in recent years, driven by the fast pace of modern living and increasing consumer demand for convenience. Prepared foods are taking an increasingly important role in the modern catering industry due to their ease of storage, transportation, and operation. However, their processing faces several challenges, including labor shortages, inefficient sorting, inadequate cleaning, unsafe cutting processes, and a lack of industry standards.
View Article and Find Full Text PDFISA Trans
December 2024
GEELY Automobile Research Institute Co. Ltd, Ningbo, Zhejiang 315699, China. Electronic address:
The voltage is one of limited reliable information for battery management system, and the faults of voltage sampling will result in adverse effects and lead to potential risks for operation, which emphasize the importance for investigating the failure modes of voltage sampling and diagnosis algorithm. In this article, a knowledge-data driven sampling diagnosis algorithm is established and an online intelligent diagnosis algorithm is proposed accordingly based on outlier detection with fuzzy entropy. The fault diagnosis algorithm is established and evaluated under positive exploitation, where the knowledge-base of failure mode based on equivalent simulating models is firstly constructed.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Engineering, Imam Khomeini Naval Science University of Nowshahr, Nowshahr, Iran.
J Food Sci
January 2025
College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi'an, China.
To enhance the drying quality of peony flowers, this study developed an integrated intelligent control and monitoring system. The system incorporates computer vision technology to enable real-time continuous monitoring and analysis of the total color change (ΔE) and shrinkage rate (SR) of the material. Additionally, by integrating drying time and temperature data, a hybrid neural network model combining convolutional neural networks, long short-term memory, and attention mechanisms (CNN-LSTM-Attention) was employed to accurately predict the moisture ratio (MR) of peony flowers.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Computer and AI, Cairo University, Giza, Egypt.
Drug discovery and development is a challenging and time-consuming process. Laboratory experiments conducted on Vidarabine showed IC 6.97 µg∕mL, 25.
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