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Full-Text Articles in Physical Sciences and Mathematics
Pixel-Wise Machine Learning And Deep Learning Methods Implementation On Multi-Class Wildfire Mapping, Mingda Wu
Pixel-Wise Machine Learning And Deep Learning Methods Implementation On Multi-Class Wildfire Mapping, Mingda Wu
Honors Capstones
Wildfires are destructive natural hazards. Artificial Intelligence (AI) has been a trendy topic in recent years due to its powerful applicability. This study focuses on the use of artificial intelligence (AI) in hazard management, specifically in the field of wildfire mapping. Machine learning and Deep learning are two subsets of AI. This study applied pixel-wise machine learning and deep learning methods to do multi-class mapping on two wildfire events in California, USA. The purpose of this research is to demonstrate the usefulness and advantages of using AI in the field of hazard management. The machine learning methods selected are Random …
Using Machine Learning To Search For Vector Boson Scattering At The Cms Detector During Run 2, Mark Mekosh
Using Machine Learning To Search For Vector Boson Scattering At The Cms Detector During Run 2, Mark Mekosh
Graduate Research Theses & Dissertations
This work reports on the use of different machine learning (ML) techniques in the search for vector boson scattering (VBS) events in the semileptonic $WV$ channel. VBS is an important process for studying electroweak symmetry breaking (EWSB), the Higgs mechanism, as well as for probing beyond the standard model physics. Boosted decision trees as well as deep neural networks were trained on Monte Carlo simulation samples and applied to 137 fb$^{-1}$ of proton-proton collision data taken from 2016 to 2018 by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) with a center of mass energy $\sqrt{s} …
Using Machine Learning To Predict Student Outcomes, Saba Fatima
Using Machine Learning To Predict Student Outcomes, Saba Fatima
Graduate Research Theses & Dissertations
Predicting students’ performance to identify which students are at risk of receiving aD/Fail/Withdraw (DFW) grade and ensuring their timely graduation is not just desirable but also necessary in most educational entities. In the US, not only is the Science, Technology, Engineering, and Mathematics (STEM) major becoming less popular among students, the graduation rate of STEM students is steadily declining. The lack of STEM graduates in the US is a serious problem that will place this country at a disadvantage as a competitor in international technological advancement. In order to secure its status as a technological leader internationally, the US institutions …
Development Of Machine Learning Models To Predict The Online Impact Of Research, Mohammed Murtuza Shahzad Syed
Development Of Machine Learning Models To Predict The Online Impact Of Research, Mohammed Murtuza Shahzad Syed
Graduate Research Theses & Dissertations
Scientific research is being increasingly shared online in a way such that there is a need to develop methodologies to measure the impact of specific papers in ways that go beyond traditional indicators of scholarly citations and beyond the scholarly community. In this thesis, new machine learning models are developed to measure and predict the impact ofresearch in the online context. The extent to which research papers are mentioned on social media platforms, i.e., their online sustainability, indicates the public's interest in and perhaps even the level of understanding of scientific topics. A research paper having a long lifespan, i.e., …