Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Einstein-Roscoe Regression For The Slag Viscosity Prediction Problem In Steelmaking, Hiroto Saigo, Dukka Kc, Noritaka Saito
Einstein-Roscoe Regression For The Slag Viscosity Prediction Problem In Steelmaking, Hiroto Saigo, Dukka Kc, Noritaka Saito
Michigan Tech Publications
In classical machine learning, regressors are trained without attempting to gain insight into the mechanism connecting inputs and outputs. Natural sciences, however, are interested in finding a robust interpretable function for the target phenomenon, that can return predictions even outside of the training domains. This paper focuses on viscosity prediction problem in steelmaking, and proposes Einstein-Roscoe regression (ERR), which learns the coefficients of the Einstein-Roscoe equation, and is able to extrapolate to unseen domains. Besides, it is often the case in the natural sciences that some measurements are unavailable or expensive than the others due to physical constraints. To this …
On The Detection Of Statistical Heterogeneity In Rain Measurements, A. R. Jameson, Michael L. Larsen, A. Kostinski
On The Detection Of Statistical Heterogeneity In Rain Measurements, A. R. Jameson, Michael L. Larsen, A. Kostinski
Department of Physics Publications
The application of the Wiener–Khintchine theorem for translating a readily measured correlation function into the variance spectrum, important for scale analyses and for scaling transformations of data, requires that the data be wide-sense homogeneous (stationary), that is, that the first and second moments of the probability distribution of the variable are the same at all times (stationarity) or at all locations (homogeneity) over the entire observed domain. This work provides a heuristic method independent of statistical models for evaluating whether a set of data in rain is wide-sense stationary (WSS). The alternative, statistical heterogeneity, requires 1) that there be no …
On The Variability Of Drop Size Distributions Over Areas, A. R. Jameson, M. L. Larsen, A. B. Kostinski
On The Variability Of Drop Size Distributions Over Areas, A. R. Jameson, M. L. Larsen, A. B. Kostinski
Department of Physics Publications
Past studies of the variability of drop size distributions (DSDs) have used moments of the distribution such as the mass-weighted mean drop size as proxies for the entire size distribution. In this study, however, the authors separate the total number of drops Nt from the DSD leaving the probability size distributions (PSDs); that is, DSD = Nt × PSD. The variability of the PSDs are then considered using the frequencies of size [P(D)] values at each different drop diameter P(PD | D) over an ensemble of observations collected using a …