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...
The electric power grids of countries across the globe rely on load and generation forecasting to know when, where, and how much resources need to be dispatched to sustain proper grid operation. Because of this, forecasting needs to be highly accurate to avoid unnecessary resource dispatch which can be costly....
In the ever-evolving field of computer science (CS) education, the significance of teachers and their backgrounds have often been overshadowed by the predominant focus on students. Teachers in the K-12 often lack the necessary expertise and have limited support provided by existing CS-based curricula. While research on CS education effectiveness...
The understanding of Discipline-Specific Language is an important competency for students of any field to begin mastering early in their studies, since it serves as a prerequisite for both the analysis of expert text and precise communication. Therefore, an introductory curriculum should pay careful attention to how it incorporates, defines,...
Voltage fault injection is a technique to disrupt power supply, such that the data or instruction flow in a microcontroller can be modified. Recently, a new class of voltage glitches was introduced termed arbitrary wave voltage glitches. Despite its demonstrated success in practical studies it comes with additional challenges, such...
Just off the coast of the Pacific Northwest lies the Cascadia Subduction Zone (CSZ); odds of a very large CSZ earthquake occurring in the next 50 years is estimated to be about 37%. A CSZ seismic event has the potential to cause wide scale damage not just to the power...
Compactness in deep learning can be critical to a model’s viability in low-resource applications, and a common approach to extreme model compression is quantization. We consider Iterative Product Quantization (iPQ) with Quant-Noise [Fan et al., 2020] to be state-of-the-art in this area, but this quantization framework suffers from preventable inference...
Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
Materials with a strong spin Hall effect and Rashba-Edelstein effect have the potential to improve the efficiency of solid-state magnetic memory technologies and other magnetic logic devices. Heavy metals have been identified as having these properties, including the beta crystal phase of tungsten. In this work, we determine the strength...
Hyperspectral images consist of intensity measurements associated with a large number of EM wavelengths per pixel. When a pixel contains a single material, the measurements of the pixel match the spectral signature of the material. When multiple materials are present in a single pixel, spectral mixing occurs, and signatures of...
Deep learning is now being utilized widely in applications where sensitive data is being used for model training, for example, in health care. In this scenario, any data leakage will cause privacy concerns to whose data records are used to train the model. An attacker can actively cause privacy leakage...