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Using Machine Learning to Improve Neutron Tagging Efficiency in Water Cherenkov Detectors 

Stubbs, Matthew (University of Winnipeg, 2021-11-25)
When an anti-neutrino collides with a proton in the atomic nucleus, it yields an anti-lepton and a free neutron. In a water Cherenkov neutrino detector like Super-K or the next generation Hyper-K, the free neutron is ...
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Short Text Classification with Tolerance Near Sets 

Patel, Vrushang (University of Winnipeg, 2021-08-13)
Text classification is a classical machine learning application in Natural Language Processing, which aims to assign labels to textual units such as documents, sentences, paragraphs, and queries. Applications of text ...
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Rough-set based learning methods: A case study to assess the relationship between the clinical delivery of cannabinoid medicine for anxiety, depression, sleep, patterns and predictability 

Ashrafi, Negin (University of Winnipeg, 2022-08-22)
COVID-19 is an unprecedented health crisis causing a great deal of stress and mental health challenges in populations in Canada. Recently, research is emerging highlighting the potential of cannabinoids’ beneficial effects ...

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AuthorAshrafi, Negin (1)Patel, Vrushang (1)Stubbs, Matthew (1)Subject
Machine Learning (3)
Cannabinoid Medicine (1)Granular Computing (1)Graph Neural Networks (GNN) (1)Mental Health (1)Natural Language Processing (1)Neutron Tagging (1)Particle Physics (1)Rough Sets (1)Rough-Fuzzy Sets (1)... View MoreDate Issued2021 (2)2022 (1)Has File(s)Yes (3)

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