In this comprehensive thesis, we present a series of experiments and findings that highlight the
critical importance of TDC Voltage Sensors in the hardware security domain. Our research begins
by introducing a novel self-calibrating module, demonstrating its efficiency through preliminary
calibration tests. We then delve into the Peak-to-Peak tests, which...
Metric spaces (X, d) are ubiquitous objects in mathematics and computer science that are able to capture pairwise distance relationships d(x, y) between points x, y ∈ X. Because of this, it is natural to ask what useful generalizations there are of metric spaces for capturing “k-wise distance relationships” d(x1,...
Explainable Artificial Intelligence (XAI) systems aim to improve users’ understanding of AI but rarely consider the inclusivity aspects of XAI. Without inclusive approaches, improving explanations might not work well for everyone. This study investigates leveraging users’ diverse problem-solving styles as an inclusive strategy to fix an XAI prototype, with the...
We present student perceptions of a new first-year engineering programming class that was designed by informed research practices. While the College of Engineering at Oregon State University saw a lot of major switching in the first year, there were not many students switching into computer science (CS). This could have...
A multidisciplinary perspective is necessitated for the analysis of wave energy conversion systems, spanning hydrodynamics, mechanics, electric power, and control systems. The complexity inherent in these scientific domains poses challenges for unified analysis. This paper addresses these challenges by connecting various domains through the application of circuit theory, characterizing the...
In this thesis, we propose a systematic code for correcting t = 1 insertion/deletion errors of the character ”0” that can occur between any two consecutive 1’s in a binary string. The code requires balanced input strings, where each word of length n contains ⌈n/2⌉ 0’s and ⌊n/2⌋ 1’s. This...
SpotFinder is the mobile frontend of a parking system that helps drivers find a parking spot on campus. (The backend piece of the parking system was developed by others in the lab as part of a previous project.) Finding parking can be viewed as both a search problem and a...
Emerging research shows that individual differences in how people use technology sometimes cluster by socioeconomic status (SES) and that when technology is not socioeconomically inclusive, low-SES individuals may abandon it. To understand how to improve technology’s SES-inclusivity, we present a multi-phase case study on SocioEconomicMag (SESMag), an emerging inspection method...
Using supervised machine learning (ML) to train a computer vision model typically requires human annotators to label objects in images and video. Given a large training dataset, this can be labor intensive, presenting a significant bottleneck in the model-development process. LabelFlicks is an open-source desktop application that aims to address...
RF data-driven device fingerprinting through the use of deep learning has recently surfaced as a possible method for secure device identification and authentication. Traditional approaches are commonly susceptible to the domain adaptation problem where a model trained on data from one domain performs badly when tested on data from a...