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Full-Text Articles in Engineering
Evolution Of Mg Az31 Twin Activation With Strain: A Machine Learning Study, Andrew D. Orme
Evolution Of Mg Az31 Twin Activation With Strain: A Machine Learning Study, Andrew D. Orme
Undergraduate Honors Theses
Machine learning is being adopted in various areas of materials science to both create predictive models and to uncover correlations which reveal underlying physics. However, these two aims are often at odds with each other since the resultant predictive models generally become so complex that they can essentially be described as a black box, making them difficult to understand. In this study, complex relationships between microstructure and twin formation in AZ31 magnesium are investigated as a function of increasing strain. Supervised machine learning is employed, in the form of J-48 decision trees. In one approach, strain is incorporated as an …
A Framework For Studying The Physical Degradation Characteristics Of Dvds And Their Relationship To Digital Errors, Brian K. Saville
A Framework For Studying The Physical Degradation Characteristics Of Dvds And Their Relationship To Digital Errors, Brian K. Saville
Theses and Dissertations
The methods used to store data on DVD-R discs have been proven to work over the last 15 years. However, there has been a growing concern that these discs will be outlasted by the paper records they were meant to replace. The data on a DVD-R is stored as optical contrasts which have the potential to be misread and even damaged. This damage may occur either on the surface or internally to the disc, especially on the recording layer itself. The literature is saturated with studies attempting to determine the time period in which discs may fail and what the …