Robotics & Machine Learning Daily News2024,Issue(Sep.11) :28-28.

Guangdong University of Petrochemical Technology Reports Findings in Machine Lea rning (Machine learning-assisted fluorescence visualization for sequential quant itative detection of aluminum and fluoride ions)

Robotics & Machine Learning Daily News2024,Issue(Sep.11) :28-28.

Guangdong University of Petrochemical Technology Reports Findings in Machine Lea rning (Machine learning-assisted fluorescence visualization for sequential quant itative detection of aluminum and fluoride ions)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Maoming, People’s Republ ic of China, by NewsRx journalists, research stated, “The presence of aluminum ( Al) and fluoride (F) ions in the environment can be harmful to ecosystems and hu man health, highlighting the need for accurate and efficient monitoring. In this paper, an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum (Al) and fluoride (F) ions in a queous solutions.”

Key words

Maoming/People’s Republic of China/Asia/Aluminum/Anions/Cyborgs/Emerging Technologies/Fluorides/Hydrofluoric Acid/Light Metals/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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