首页|Researchers from State University Describe Findings in Machine Learning [Machine Learning Approach for Ion Imprinted (Iip) and Non-imprinted (Nip) Polymer Discrimination Based On Pyrolysis Kinetic Data]
Researchers from State University Describe Findings in Machine Learning [Machine Learning Approach for Ion Imprinted (Iip) and Non-imprinted (Nip) Polymer Discrimination Based On Pyrolysis Kinetic Data]
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingfrom Salvador, Brazil, by NewsRx journalists, research stated, “The improper disposal of effluents containingtoxic elements, such as nickel and mercury, can result in the gradual deterioration of surface waterquality, impacting aquatic ecosystems and human health. Ionically imprinted polymers (IIPs) are promisingcandidates for remediating toxic areas due to their high removal rates and selectivity.”
SalvadorBrazilSouth AmericaCyborgsEmerging TechnologiesMachine LearningState University
NETL
NSTL
