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...
The ferromagnetic resonance (FMR) phenomenon serves as a sensitive probe of the effective internal fields in a magnetic material. FMR spectroscopy has consequently become a well-established technique, extensively employed in assessing material properties such as magnetic anisotropy, Landé g-factor, damping parameter, and the magnetoelastic constants of magnetic materials. Determining these...
This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Despite an increase in the number of people who rely on manual wheelchairs, there are still substantial economic barriers to affordable and accessible localization systems. As a result, there is a pressing need to build a versatile yet low cost localization system for manual wheelchairs. Such systems allow users to...
Distributed version control allows developers to manage software evolution among distributed development teams. But it does not eliminate all consistency and concurrency issues, and instead introduces additional complexity when merging code. And resolving merge conflicts is nontrivial when automated merging fails. In such cases, developers are forced to inspect the...
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,...
Given the abundance of images related to operations that are being captured and stored, it behooves firms to innovate systems using image processing to improve operational performance that refers to any activity that can save labor cost. In this paper, we use deep learning techniques, combined with classic image/signal processing...
Low-power receivers (RX) with 100$\mu W$-scale power consumption can enable several power/energy-constrained IoT applications. However, achieving sensitivity, interferer tolerance and wide operating range with low power presents a challenge for existing architectures, particularly those constrained to highly integrated solutions without high-Q off-chip components. Existing solutions rely heavily on high quality...
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...
Social media platforms use many techniques to engage users' attention with their platforms, including notifications, popups, and gamification elements. The impact of social media on physical and mental health has been studied, but limited publicly available research exists on how social media users can be helped to disengage from these...
Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
Rapid and sensitive detection of stress hormones, such as cortisol and dehydroepiandrosterone (DHEA), can benefit the diagnosis of diseases related to adrenal gland disorders, post-traumatic stress disorders, chronic fatigue syndrome, and more. Stress hormones fluctuate in a circadian rhythm, the highest in the early morning and the lowest at night;...
Current methods for visualizing forest rely on geospatial and remote sensed data. Such data can be used to create visualization and to perform simulations. Currently, however, these visualizations are often limited to 2D or abstract representations. These methods can be effective for large scale data visualization and low accuracy needs....
A variety of important machine learning applications require predictions on test data with different characteristics than the data on which a model was trained and validated. In particular, test data may have a different relative frequency of positives and negatives (i.e., class distribution) and/or different mislabeling costs of false positive...
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...
A secret sharing scheme allows a dealer to distribute a secret with a set of parties, such that only a certain subset of parties can collaborate and learn the shared secret. Traditional secret sharing schemes have been used as building blocks in various subdomains of cryptography. Recently, two new extensions...
One of the pervasive problems arising in our modern, digital world surrounds data breaches where an adversary, through zero-day exploitations, phishing, or old-fashioned social engineering attacks, gains access to a service’s data stores. Our society increasingly relies on these cloud-based services for everything from our taxes to personal communication. As...
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...
Additive manufacturing has become a promising method for the fabrication of inexpensive, green, flexible sensors and electronics. Printed electronics on low- temperature substrates are very appealing for the flexible hybrid electronics market for their use in disposable and biocompatible electronic applications and in areas like packaging, wearables, and consumer electronics....
While digital inclusivity researchers and software practitioners have been trying to address exclusion biases in Windows, Icons, Menus, and Pointers (WIMP) user interfaces (UIs) for a long time, little has been done to investigate if and how inclusive software design and its methods that have been devised for WIMP UIs...
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...
Over time, Open Source Software (OSS) has become indispensable in the creation and upkeep of software products, serving as the fundamental building block for widely used solutions in our daily lives, including applications that enable communication, entertainment, and productivity. A sustainable OSS ecosystem is one that attracts and retains 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 an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
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...
This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
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...
Secure Computation is a powerful tool that enables a set of parties to jointly compute any function over their private inputs, without a trusted third party. Private Set Intersection is a specific case of two-party Secure Computation, where Alice (with private set X) and Bob (with private set Y) specifically...
Generating abundant, renewable energy from Earth’s oceans is an attractive option for meeting increasing energy demand. Marine renewable energy also comes with the variability of renewable sources, which impact the reliability and power quality of the electrical grid. On a transmission-level, this dissertation looks at ensuring reliability of the power...
The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
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....
Machine learning applied to computer architecture has rapidly transitioned from a theoretical novelty to being a driving force behind design, control, and simulation in practically all components. These machine-learning-based methodologies are further notable for their scalability to increasingly complex design challenges, which has allowed these methodologies to surpass the prior...
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...
Clos-based network topologies have been deployed in production data center networks to provide multiple path alternatives between the pairs of network hosts. Production data centers operate under varying traffic dynamics and topological asymmetry. Therefore, a good load balancing scheme must adapt to network conditions and dynamics in real-time and intelligently...
The OSU Motor Systems Resource Facility (MSRF), co-directed by the Principal Investigators (PI's, bios included), is an Energy Systems Laboratory with operating capabilities up to 750kV A, testbeds up to 300hp, a 120kVA fully programmable source, and a bi-directional grid interface enabling regeneration back onto the grid. The MSRF was...
This paper presents an overview of cogeneration, also known as combined heat and power (CHP). The technology of cogeneration is described and the three primary cogeneration processes are discussed. The transition between parallel operation with the utility and stand-alone operation is discussed. The tradeoff between a synchronous and an induction...
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...
Modern datacenters are constructed with multirooted tree topologies and support multiple service queues per switch port. They support a wide variety of applications and services with stringent performance needs and conflicting requirements. To meet these requirements, recent works focus on load balancing or ECN marking approaches. Though existing load-balancing approaches...
Recently, Explicit Congestion Notification (ECN) has been leveraged by most Datacenter Network (DCN) protocols for congestion control to achieve high throughput and low latency. However, the majority of these approaches assume that each switch port has one queue while current industry trends towards having multiple queues per switch port. To...
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...
Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...
As the fifth generation of mobile communication systems (5G) is being deployed, massive multiple-input multiple-output (MIMO) serves as one of its enabling technologies where reliable and ultra low latency communications are achieved while being power and spectrum efficient. This thesis studies the security aspect of massive MIMO system from the...