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    AI-RACS: Innovative tool for mining aluminum-tolerant strains in acidic soils

    1-1页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Researchers from the Single-Cell Center at the Qi ngdao Institute of Bioenergy and BioprocessTechnology of the Chinese Academy of Sciences (CAS), together with collaborators, have developed anartificial intel ligence-assisted Raman-activated cell sorting (AI-RACS) system. This innovative system hasautomated the isolation and functional analysis of aluminum-tolerant microorganisms (ATMs) from acidicsoil, marking a shift from manual, labor-inten sive procedures to high-throughput automated workflows.This study was published in Analytical Chemistry.

    AI-RACS: Innovative tool for mining aluminum-tolerant strains in acidic soils

    1-1页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Researchers from the Single-Cell Center at the Qi ngdao Institute of Bioenergy and BioprocessTechnology of the Chinese Academy of Sciences (CAS), together with collaborators, have developed anartificial intel ligence-assisted Raman-activated cell sorting (AI-RACS) system. This innovative system hasautomated the isolation and functional analysis of aluminum-tolerant microorganisms (ATMs) from acidicsoil, marking a shift from manual, labor-inten sive procedures to high-throughput automated workflows.This study was published in Analytical Chemistry.

    Researchers from Shandong University of Science and Technology Provide Details o f New Studies and Findings in the Area of Machine Learning (Optimizing multi-cla ssifier fusion for seabed sediment classification using machine learning)

    2-2页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in artificial intelligence. According to news originatingfrom Qingdao, People’s Re public of China, by NewsRx editors, the research stated, “ABSTRACTSeabedsedimen t mapping with acoustical data and ground-truth samples is a growing field in ma rine science.In recent years, multi-classifier ensemble models have gained prom inence for classification problems bycombining several base classifiers.”

    Researchers from Shandong University of Science and Technology Provide Details o f New Studies and Findings in the Area of Machine Learning (Optimizing multi-cla ssifier fusion for seabed sediment classification using machine learning)

    2-2页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in artificial intelligence. According to news originatingfrom Qingdao, People’s Re public of China, by NewsRx editors, the research stated, “ABSTRACTSeabedsedimen t mapping with acoustical data and ground-truth samples is a growing field in ma rine science.In recent years, multi-classifier ensemble models have gained prom inence for classification problems bycombining several base classifiers.”

    Research Reports from University of Manchester Provide New Insights into Machine Learning (Machine-learning-assisted analysis of highly transient X-ray imaging sequences of weld pools)

    3-3页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from Manchester, United Kingdom, by NewsRx correspondents, research stated, “Fusion-basedwelding and additive manufacturing are two key pillars of manufacturing.”

    Research Reports from University of Manchester Provide New Insights into Machine Learning (Machine-learning-assisted analysis of highly transient X-ray imaging sequences of weld pools)

    3-3页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from Manchester, United Kingdom, by NewsRx correspondents, research stated, “Fusion-basedwelding and additive manufacturing are two key pillars of manufacturing.”

    Toyama Prefectural University Researcher Has Published New Study Findings on Com putational Intelligence (Online Topological Mapping on a Quadcopter with Fast Gr owing Neural Gas)

    3-4页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New study results on computational int elligence have been published. According tonews originating from Toyama, Japan, by NewsRx correspondents, research stated, “This paper presentsan online topol ogical mapping method on a quadcopter with fast-growing neural gas. Recently, pe rceivingthe real world in 3D space has become increasingly important, and robot ics is no exception.”

    Toyama Prefectural University Researcher Has Published New Study Findings on Com putational Intelligence (Online Topological Mapping on a Quadcopter with Fast Gr owing Neural Gas)

    3-4页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New study results on computational int elligence have been published. According tonews originating from Toyama, Japan, by NewsRx correspondents, research stated, “This paper presentsan online topol ogical mapping method on a quadcopter with fast-growing neural gas. Recently, pe rceivingthe real world in 3D space has become increasingly important, and robot ics is no exception.”

    Research Conducted at Texas Technical University Has Provided New Information ab out Machine Learning (Enhancing Shale Gas Eur Predictions With Tpe Optimized Smo gn: a Comparative Study of Machine Learning Algorithms In the Marcellus Shale Wi th ...)

    4-5页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Machine Learning have be en published. According to news originatingfrom Lubbock, Texas, by NewsRx corre spondents, research stated, “Oil and gas operators frequentlyrely on traditiona l methods to predict Estimated Ultimate Recovery (EUR) but, these methods oftenfail to accurately predict shale gas EUR. Therefore, machine learning (ML) algor ithms were shown aspromising alternatives but, the negative effects of imbalanc ed datasets on their performance still remainsunderexplored.”

    Research Conducted at Texas Technical University Has Provided New Information ab out Machine Learning (Enhancing Shale Gas Eur Predictions With Tpe Optimized Smo gn: a Comparative Study of Machine Learning Algorithms In the Marcellus Shale Wi th ...)

    4-5页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Machine Learning have be en published. According to news originatingfrom Lubbock, Texas, by NewsRx corre spondents, research stated, “Oil and gas operators frequentlyrely on traditiona l methods to predict Estimated Ultimate Recovery (EUR) but, these methods oftenfail to accurately predict shale gas EUR. Therefore, machine learning (ML) algor ithms were shown aspromising alternatives but, the negative effects of imbalanc ed datasets on their performance still remainsunderexplored.”