Engineering Papers⌕ Search

Engineering topics

Arnold, David

Publications and source records attributed to Arnold, David.

Homomorphic Encryption for Machine Learning and Artificial Intelligence Applications

Third-party and expert analysis is a cost-effective solution for solving specialized problems or processing large datasets related to reactor structural health monitoring and nondestructive evaluation. However, when handling proprietary information, third-party and expert analysts pose a privacy risk. To address this challenge, Homomorphic Encryption (HE) permits arithmetic operations on encrypted data without exposing the underlying data. Implementations of Machine Learning (ML) and Artificial Intelligence (AI) algorithms using HE greatly enhances the capabilities of third-party analysts while maintaining a low security risk. This paper details current success in applying Principal Component Analysis (PCA) and Fully Connected Neural Networks (NN) using the Microsoft SEAL implementation of the popular CKKS Fully Homomorphic Encryption (FHE) algorithm. The MNIST Handwritten Dataset is analyzed as a proof-of-concept demonstration of the implementations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experimental measurement and theoretical modeling of microwave scattering and the structure of the sea surface influencing radar observations from space

The electromagnetic (EM) bias 'epsilon' is an error present in radar altimetry of the ocean due to the nonuniform reflection from wave troughs and crests. The EM bias is defined as the difference between the mean reflecting surface and the mean sea surface. A knowledge of the EM bias is necessary to permit error reduction in mean sea level measurements by satellite radar altimeters. Direct measurements of the EM bias were made from a Shell Offshore oil production platform in the Gulf of Mexico for a six month period during 1989 and 1990. Measurements of the EM bias were made at 5 and 14 Ghz. During the EM bias experiments by Melville et al., a wire wave gauge was used to obtain the modulation of the high frequency waves by the low frequency waves. It became apparent that the EM bias was primarily caused by the modulation of the short waves. This was reported by Arnold et al. The EM bias is explained using physical optics scattering and an empirical model for the short wave modulation. Measurements of the short wave modulation using a wire wave gauge demonstrated a linear dependence of the normalized bias on the short wave modulation strength, M. The theory accurately predicts this dependence by the relation epsilon = -alphaMH sub 1/3. The wind speed dependence of the normalized bias is explained by the dependence of the short wave modulation strength on the wind speed. While other effects such as long wave tilt and curvature will have an effect on the bias, the primary cause of the bias is shown to be due to the short wave modulation. This report will present a theory using physical optics scattering and an empirical model of the short wave modulation to estimate the EM bias. The estimated EM bias will be compared to measurements at C and Ku bands.

Arnold, David↗

Experimental measurement and theoretical modeling of microwave scattering and the structure of the sea surface influencing radar observations from space

The electromagnetic bias is an error present in radar altimetry of the ocean due to the non-uniform reflection from wave troughs and crests. A study of the electromagnetic bias became necessary to permit error reduction in mean sea level measurements of satellite radar altimeters. Satellite radar altimeters have been used to find the upper and lower bounds for the electromagnetic bias. This report will present a theory using physical optics scattering and an empirical model of the short wave modulation to predict the electromagnetic bias. The predicted electromagnetic bias will be compared to measurements at C and Ku bands.

Arnold, David↗