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Timelines Over Tokens: Summarization, Prompting, And Explainable Fine-Tuning For User-Level Suicide Risk Detection, Aditya Tekale
Timelines Over Tokens: Summarization, Prompting, And Explainable Fine-Tuning For User-Level Suicide Risk Detection, Aditya Tekale
Master's Theses
This research presents a two-stage pipeline for user-level suicide risk detection from Reddit: first, inference-only prompting with summarization; second, fine-tuned encoder classification with explainability and expert validation. The data are user-level: each of the 500 C-SSRS Reddit items is one user’s chronologically concatenated posts and comments (a user timeline), annotated by psychiatrists. Stage one: six prompting strategies zero-shot, few-shot, chain-of-thought, tree-of-thought, least-to-most, and self-consistency are evaluated across six LLMs on multi-class and binary formulations; simple zero-shot achieves the highest balanced accuracy (0.53 multi-class). Error analysis shows longer inputs associate with misclassification (p = 0.002); domain-specific summarization (timelines >2,000 tokens) reduces …
Rthermal: Gate Level Power And Thermal Simulation For 3d-Stacked Chips, Peter Xiong
Rthermal: Gate Level Power And Thermal Simulation For 3d-Stacked Chips, Peter Xiong
Master's Theses
As the number of transistors in modern processors increases, heat dissipation has become a major bottleneck to scalability. The use of 3D stacking further intensifies this problem, as heat from multiple layers can accumulate vertically. These challenges create a growing need for tools that can accurately and efficiently simulate the thermal behavior of 3D chips during design and validation. Several existing tools model thermal behavior for 3D-stacked chips and can simulate average heat over large spatial regions or long time intervals. However, when heat is concentrated in a small area or over a short time window, such models can miss …
Biologically-Based Alternatives To Plastic Mulch Enrich Microbiome And Buffer Yield In Small-Scale Strawberry Production, Olivia L. Fragiacomo
Biologically-Based Alternatives To Plastic Mulch Enrich Microbiome And Buffer Yield In Small-Scale Strawberry Production, Olivia L. Fragiacomo
Master's Theses
Much of commercial agriculture has used plastic mulch since the 1950s to contain fungicides and fertilizers, control weeds, retain soil moisture, and warm the top soil to start the growing season earlier. Research suggests that small-scale strawberry (Fragaria x ananassa) growers may be able to incorporate biological techniques, such as wheat straw mulch with microbial amendments, to reduce the use of single-use plastic mulch with a comparable yield. For this study, I carried out a randomized complete block comparison of five strawberry management techniques: plastic mulch (PM), straw mulch alone, and straw mulch inoculated with either arbuscular mycorrhizal fungi (AMF), …
Investigating Learning In Immersive Virtual Reality, Andrew Negrette
Investigating Learning In Immersive Virtual Reality, Andrew Negrette
Master's Theses
Students often struggle with learning challenging subjects throughout their education. This also tends to lead to lower enjoyment and science self-efficacy for learning. Some subjects may be better represented in 3-dimensional spaces utilizing immersive virtual reality (IVR). Recently, IVR headsets have become more accessible and affordable and therefore are in wider use. The purpose of this study was to investigate whether differences in science selfefficacy, enjoyment, presence and knowledge retention exist between IVR and controls on an ocean acidification lesson. I predicted that participants taking the lesson in IVR would score higher compared to a laptop on all measures, due …
Interpretable Wellness Prediction From Passive Wearable Sensor Data Using Large Language Models, Cheng-Huan Yu
Interpretable Wellness Prediction From Passive Wearable Sensor Data Using Large Language Models, Cheng-Huan Yu
Master's Theses
This thesis presents a unified framework for multi-target wellness prediction using passive wearable sensor data and large language models (LLMs). The study integrates two complementary paradigms: prompt-based regression and representation-driven classification. In the first stage, structured wearable representations derived from daily physiological signals are used to prompt LLMs to predict stress, fatigue, sleep quality, and readiness. Two input representations are evaluated: statistical summaries and hybrid inputs combining statistical summaries with raw sensor values. To improve interpretability and prediction consistency, the second stage introduces a representation-centric classification framework in which wearable signals and wellness targets are discretized into categorical levels. Multiple …
Moral: Multimodal Reasoning For Autonomous Language Models With Sensor-Grounded Spatial Bev Rendering, Ambarish Govindarajulu Kaliamurthi
Moral: Multimodal Reasoning For Autonomous Language Models With Sensor-Grounded Spatial Bev Rendering, Ambarish Govindarajulu Kaliamurthi
Master's Theses
Autonomous-driving vision-language models describe scenes fluently but reason poorly about metric, safety-critical spatial relationships because they do not read sensor geometry in a grounded way. This thesis presents MoRAL (Multimodal Reasoning for Autonomous Language Models), a two-stage fine-tuning pipeline that teaches a compact 2-billion-parameter VLM to decode a physics-encoded Bird’s Eye View (BEV) representation – LiDAR distance as color, object class as cluster shape, radar Doppler velocity as directional wedges – and then trains it to reason over that representation for driving decisions. Stage 2 then fine-tunes on 57,696 teacher-generated chain-of-thought examples across eight question types, using Cosmos-Reason2-8B as teacher …
Superresolution Spectroscopy Of Atomically Thin Semiconductors And Moiré Heterostructures, Chien-Chu (Charity) Wei
Superresolution Spectroscopy Of Atomically Thin Semiconductors And Moiré Heterostructures, Chien-Chu (Charity) Wei
Master's Theses
Atomically thin semiconductors and moir’e heterostructures provide an important platform for studying quantum phenomena shaped by reduced dimensionality, interlayer coupling, strain, and local structure. In MoS2, the transition from bulk to monolayer form changes the material from an indirect to a direct band gap, while stacked and strain-engineered systems can produce spatially varying moir’e potentials on nanometer length scales. Because these effects are highly localized, conventional far-field optical spectroscopy is often limited in its ability to resolve them directly. This thesis explores superresolution vibrational spectroscopy as a route toward probing local behavior in atomically thin semiconductors and moir’e heterostructures. Far-field …
Remote Reality: Exploring The Outcomes Of Psychological Contract Breach On Telecommuting Employees, Karen L. Ng
Remote Reality: Exploring The Outcomes Of Psychological Contract Breach On Telecommuting Employees, Karen L. Ng
Master's Theses
The purpose of this study was to investigate the relationship between psychological contract breach (PCB) and attitudinal outcomes, specifically job satisfaction, organizational commitment, and turnover intent, within the telecommuter population. Results of an online survey administered to 213 participants revealed strong support of all hypotheses: PCB was negatively associated with job satisfaction and organizational commitment and positively associated with turnover intent. Exploratory analyses revealed moderating effects of remote work frequency and organizational tenure with PCB and attitudinal outcomes. High-frequency remote workers and longer-tenured employees showed stronger negative reactions to PCB, indicating their amplified vulnerability to breaches. Age and gender showed …
The Zeal Instruction Set Architecture, Joseph A. Gerani
The Zeal Instruction Set Architecture, Joseph A. Gerani
Master's Theses
The Instruction Set Architecture of a CPU (Central Processing Unit) determines what type of instructions the CPU is able to understand, how those instructions are encoded, and what it should output upon receiving those instructions as input. There are currently three popular ISAs meant for the consumer market: x86, RISC-V, and ARM, as well as a fourth that mostly now exists in the server market by the name of Power. One of the most important parts of an ISA is for engineers to be able to understand it and make use of it. If an ISA is too complicated, nobody …
The Moderating Role Of Flexible Work Styles On The Relationship Between Relational Identification And Affective Organizational Commitment, Justine Lee
Master's Theses
The purpose of this study was to explore the moderating role of flexible work styles (in-person, hybrid, and remote) on the relationship between relational identification and affective organizational commitment (AOC). The study utilized an online survey to collect data from 69 respondents. The results demonstrated that although relational identification and AOC were related, this relationship was not moderated by flexible work styles. The three different work styles of in-person, hybrid, and remote work did not show differing affects for a subordinate’s relational identification and the strength of their AOC. The results emphasize that organizations can foster strong relational identification to …
Data Augmentation For Vision-Language-Action Models: Bridging Vision And Language, Miaosen Zhou
Data Augmentation For Vision-Language-Action Models: Bridging Vision And Language, Miaosen Zhou
Master's Theses
This thesis focuses on real-time task execution and object detection for autonomous robots through dataset augmentation. We propose a data augmentation approach to address dataset imbalance in Vision-Language-Action (VLA) models across both image and text modalities during the fine-tuning process. The proposed method takes an image as input and generates a structured textual description using a prompt engineering strategy to augment the textual input. The generated augmented text includes key elements such as the task goal, scene description, reasoning, and execution plan, along with other relevant contextual information. This enriched representation improves the quality of the training data and supports …
Towards Neural Network Optimization: Addressing Issues With Corrupted Weights Within Models, Nick Najafizadeh
Towards Neural Network Optimization: Addressing Issues With Corrupted Weights Within Models, Nick Najafizadeh
Master's Theses
Neural networks are a recent popular technology inspired from human brains. Much of their popularity arises from how they excel in reasoning and logic, and are generally rather efficient in their tasks. With those strengths, they are frequently used in transportation and business among many other fields. However, neural networks have many factors that can deteriorate their performance, one of the most critical being weight corruption. Therefore, it is of utmost importance to detect and handle them as soon as possible so as to minimize the negative impact on a network’s performance. The optimization of neural networks would be especially …
Accessibility Fairness Practices In Ai Applications For People With Disabilities, Megan Gross
Accessibility Fairness Practices In Ai Applications For People With Disabilities, Megan Gross
Master's Theses
Advancements in artificial intelligence (AI) improve the lives of people every day with tools like the auto-captioning of videos, improved screen-reader capabilities, and advanced mobility control through speech. However, are all groups of people benefiting from AI or are some being overlooked and left out? Although AI tools made for people with disabilities (PWDs) have improved their lives, AI for the general population generally ignores the experiences of PWDs, making them unable to interact with and benefit from technology. This research evaluates ChatGPT and Gemini in Gmail for usability fairness and analyzes how current regulations and development processes fail to …
Diagrammatic Methods For Calculating Correlation Functions In Low-Dimensional Quantum Gravity, Nicholas A. Parrilla
Diagrammatic Methods For Calculating Correlation Functions In Low-Dimensional Quantum Gravity, Nicholas A. Parrilla
Master's Theses
This thesis investigates connections between random matrix theory and low-dimensional quantum gravity through the spectral form factor (SFF), a well-studied function that characterizes correlations in the eigenvalue spectrum of an operator. In random matrix ensembles, a feature of the SFF known as the “ramp” is governed by universal spectral correlations, and in Jackiw–Teitelboim (JT) gravity this regime is due to the double-trumpet wormhole geometry. We study the connected correlation functions underlying the SFF using combinatorial, diagrammatic methods from a mathematical formalism known as second-order free probability theory, where they are expressed in terms of annular noncrossing permutations. To access a …
Rewriting The Calculus 3 Workshop At San José State University, Moorea Lippert
Rewriting The Calculus 3 Workshop At San José State University, Moorea Lippert
Master's Theses
Calculus 3 at San José State University is a very important course for any student pursuing a STEM degree. However, the course is very challenging, so the university offers a supplemental workshop course for Calculus 3 students. Unfortunately, this workshop has not aligned with modern research in math education. This thesis documents efforts to recreate the workshop to better align with this modern research.
Pipeline Optimization Of Agentic Llms For Text-To-Sql, Peter Conant
Pipeline Optimization Of Agentic Llms For Text-To-Sql, Peter Conant
Master's Theses
Current database interfaces limit users’ interaction to those with technical skills, creating timely roadblocks for non-technical professionals. Text-to-SQL aims to simplify database interactions by translating natural language questions into database queries, but long-standing challenges like question understanding, question-schema linking, and SQL generation have held the field back. In the AI era, foundational LLMs prove to be very capable of question understanding SQL, perform well in Schema Linking, Generation, and Evaluation tasks. However the cost to run these model is a hurdle for many organization with low funds and resources. Text-to-SQL solutions often operate across large enterprise size databases with, and …
Early Failure Detection In Web Navigation Agents Via Closed Sequential Pattern Mining, Sergio Talavera
Early Failure Detection In Web Navigation Agents Via Closed Sequential Pattern Mining, Sergio Talavera
Master's Theses
LLM-based web navigation agents fail on the majority of tasks while consuming substantial computational resources before failure becomes apparent. This thesis investigates whether closed sequential pattern mining on the first K steps of agent execution traces can predict task failure early enough to enable meaningful computational savings with interpretable justification. We develop a two-phase system: an offline pipeline that symbolizes agent traces, extracts K-step prefixes, mines closed patterns via BIDE+, and ranks them by failure precision; and an online detector that matches live executions against the resulting pattern library. We evaluate on 1,544 MiniWoB++ traces across three open-weight language models …
The Great Return In Higher Education: Employee Perspectives Survey, Tonya P. Person
The Great Return In Higher Education: Employee Perspectives Survey, Tonya P. Person
Master's Theses
The COVID-19 pandemic transformed traditional workplace structures across higher education, accelerating the adoption of hybrid and remote work arrangements. In the post-pandemic period, as universities implement or refine mandatory return-to-office (RTO) policies, understanding employee perspectives remains critical for informed decision-making. The present exploratory study investigated staff experiences with hybrid work, anticipated reactions to a five-day in-office mandate, and preferences for future work models within a large public university. Data were collected from 155 university staff members through a 12-item survey assessing perceived benefits of hybrid work, expected impact of a mandatory in-office requirement, and preferred work arrangements when given a …
Probabilistic Metric Dimension, Kyle Worley
Probabilistic Metric Dimension, Kyle Worley
Master's Theses
The metric dimension of a graph G is the smallest number of unique vertices (often called “marked vertices” or “landmarks”) such that each vertex has a unique distance to the marked vertices. If a set of vertices S ⊆ V (G) when marked gives all vertices unique distances, it is called a resolving set. Hence if G is a graph with a resolving set S, then for all v, u ∈ V (G) there exists s ∈ S such that d(v, s) ̸= d(u, s). The metric dimension dim(G) = min(|S|). Two widely studied variants exist, one where edges are …
Adaptive Task-Driven Lidar Point Cloud Compression For Autonomous Driving, Su Hyun Kim
Adaptive Task-Driven Lidar Point Cloud Compression For Autonomous Driving, Su Hyun Kim
Master's Theses
Autonomous-driving systems generate large LiDAR point clouds, but compression can damage the sparse object-support structure needed by 3D detectors even when reconstructions appear visually plausible. This thesis asks whether adaptive LiDAR compression can preserve downstream detection better than uniform compression by allocating more fidelity to detector-relevant regions. The main study builds a mask-aware range-image codec with an encoder-decoder bottleneck, an importance head, and an adaptive quantization variant. It compares this adaptive variant package with a confirmed masked uniform baseline under one fixed RangeDet evaluation surface and one fixed KITTI validation subset. Two supporting studies bound the result: a projection-reconstruction PointPillars …
Prepration And Characterization Of Alginate Biocomposite Films From Natural Seaweed Containing Glycerol And Silica, Bahareh Ebrahimi Mojaveri
Prepration And Characterization Of Alginate Biocomposite Films From Natural Seaweed Containing Glycerol And Silica, Bahareh Ebrahimi Mojaveri
Master's Theses
This study focuses on the development of sodium alginate, a seaweed-derived biopolymer, as a sustainable alternative to conventional food packaging films. The alginate is extracted from natural brown seaweed with a yield of 31% and is formed into alginate films by the solution casting method. This study discusses the alginate extraction and film formation techniques as well as the conditions that affect film properties. Additionally, it explores using composite formulations to enhance alginate properties through additives such as glycerol and silica. Glycerol, tested at different concentrations (15, 25, and 50 wt.%), works as a plasticizer to enhance the flexibility of …
Pick Up The Pieces: Multicultural Men’S Experiences Of Represenentation And Belonging In Higher Education, Lucion Armani Fuller
Pick Up The Pieces: Multicultural Men’S Experiences Of Represenentation And Belonging In Higher Education, Lucion Armani Fuller
Master's Theses
To examine how multicultural students experience identity, representation, and belonging within U.S. higher education structured around monoracial classification systems, the present study interviewed six self-identified multicultural male college students. Drawing on Frantz Fanon’s concept of identity fragmentation and Critical Multiracial Theory, the study explored how institutional categorization and racialized perception shape lived experiences of identity formation and misrecognition. Using semi-structured interviews and reflexive thematic analysis informed by interpretive phenomenology, participant narratives were analyzed to understand how identity is negotiated within institutional spaces. The study has three themes. The first is experiencing imposed identity and racial misrecognition. The second is navigating …
System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby
System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby
Master's Theses
The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project that seeks to enable the simulation and validation of sensors, actuators, and control logic related to spacecraft attitude control. The SADS platform rests atop a spher- ical air-bearing device which allows for nearly frictionless rotation in all three axes. The orientation of the platform is controlled by four reaction wheels arranged in a pyramidal configuration. Over the past few years, there have been significant updates to the reaction wheel subsystem, as well as requests for a more capable central com- puter. Therefore, a new system architecture for the …
Lora Networking Hardware Reference Designs For Terrestrial And Low-Earth-Orbit Communications, Kevin Nottberg
Lora Networking Hardware Reference Designs For Terrestrial And Low-Earth-Orbit Communications, Kevin Nottberg
Master's Theses
The work presented here demonstrates a highly robust and tested LoRa networking hardware reference design to meet the needs of the embedded networking company OWL Integrations. The hardware presented integrated a unique combination of features and design choices. The detailing of its unique design is potentially of use to others for use in fielded battery powered terrestrial sensor networking hardware utilizing LoRa. Also, the terrestrial hardware presented is shown to have the capability to support command and control (C2) LoRa links in low-earth orbit beyond terrestrial systems. The design presented has a more U.S. centric component bill-of-materials (BOM), with the …
City Farm Slo: A Case Study Of Nonprofit Regenerative Agriculture, Carver Tunnell
City Farm Slo: A Case Study Of Nonprofit Regenerative Agriculture, Carver Tunnell
Master's Theses
The focus of this thesis is to create a case study on City Farm SLO, a nonprofit based in San Luis Obispo, California, that has engaged in education and regenerative agriculture on City owned land since 2013. This case study is intended for use in undergraduate agribusiness and natural resource management courses, to encourage thoughtful discussion surrounding nonprofit and regenerative agricultural systems. The case presents the nonprofit at a time of relative success, having recently secured a lease renewal, extending stewardship 40 years into the future. However, the reliance on grants and donations threatens the security of the operation going …
Skinclusive Ai: Towards Equitable Skin Cancer Detection For Deployment On Edge Devices, Joseph Galicinao
Skinclusive Ai: Towards Equitable Skin Cancer Detection For Deployment On Edge Devices, Joseph Galicinao
Master's Theses
Skin cancer is one of the most prevalent cancers worldwide, yet existing deep-learning models exhibit significant racial disparities because many widely used datasets are heavily skewed toward lighter skin tones. In addition, many approaches are not designed for deployment on resource-constrained devices, which limits accessibility. This work presents a comprehensive evaluation of classical machine learning and deep-learning based models for binary skin lesion classification, identifying the Swin-Tiny transformer architecture as the most effective backbone. To address bias, we curate a skin-tone balanced dataset, and introduce fairness-aware training through adversarial training, and joint distribution oversampling, to improve performance across protected attributes. …
A Polygon Approach For Satellite Coverage Computation Problems, Caleb I. Arbreton
A Polygon Approach For Satellite Coverage Computation Problems, Caleb I. Arbreton
Master's Theses
During celestial body observation mission planning, predicted sensor coverage is a key analysis tool used by designers to inform concept of operations. It enables trade studies by applying a metric to assess how well different sensor, satellite, and constellation configurations can observe a mission's region of interest. The effectiveness of the studied components is then paramount in determining whether they are justified in the system architecture. Coverage computation becomes more difficult as sensor types and regions of interest (RoIs) deviate from simple shapes, and as problem formulations seek higher-fidelity results. These simplifications include: conical camera sensors, RoIs represented as simple, …
50,000 Spectra And Counting: Preparing For A Roman Spectral Atlas, Maya Jordan Seagraves
50,000 Spectra And Counting: Preparing For A Roman Spectral Atlas, Maya Jordan Seagraves
Master's Theses
Slitless spectroscopy with the Hubble Space Telescope's Wide Field Camera 3 \linebreak (WFC3/IR) enables simultaneous spectral coverage of all sources in a field, but large-scale single-orientation datasets remain challenging to process. We developed a pipeline that automates HSTaXe spectral extraction across hundreds of Hubble Space Telescope observations, enabling efficient processing of 84 fields and producing over 50,000 spectra from three filters (F110W, F125W, and F160W) and two grisms (G102 and G141). This was achieved by creating a companion Python package, the Module for Infrared Label Analysis (MILA), that integrates data calibration, extraction, and visualization. To assess the scientific utility of …
Dot Product Engine Based Neuromorphic Hardware For Continuous-Time Biomedical Signal Classification, Sanjeev Srinivasan
Dot Product Engine Based Neuromorphic Hardware For Continuous-Time Biomedical Signal Classification, Sanjeev Srinivasan
Master's Theses
Accurate diagnosis of pathological conditions from biomedical signals, such as electrocardiograms (ECGs) is often performed offline, making it time-consuming, costly, and inefficient, especially when abnormal patterns are rare and long-term monitoring generates large amounts of data. To address this, this work proposes a compact, scalable, and programmable neuromorphic system designed for real-time preliminary arrhythmia detection and classification using ECG signals, that can be extended to other biomedical signals. The proposed design processes ECG signals using a delta modulation-based spike encoder, followed by classification with a dot-product engine (DPE) based spiking neural network (SNN) processor and winner-take-all (WTA) circuit. The architecture …
Development Of A Multi-Mode Switching-Inverter Laboratory Module For An Introductory Power Electronics Course, Darcy Eliasi
Development Of A Multi-Mode Switching-Inverter Laboratory Module For An Introductory Power Electronics Course, Darcy Eliasi
Master's Theses
DC–AC converters, or inverters, are essential power‑electronic interfaces widely used in photovoltaic systems, microgrids, energy‑storage installations, and numerous other modern electrical applications. This thesis presents the design, construction, and testing of an improved laboratory module developed as a student learning tool for demonstrating four fundamental inverter switching techniques: simple square wave (SSWI), modified square wave (MSWI), bipolar PWM, and unipolar PWM. Building upon the previous module, the improved design centers on three key enhancements. These include the selection of a more suitable wave‑generation solution, a multiplexer‑based mode‑selection architecture that reduces user complexity and eliminates conflicting signal configurations, and the integration …