Digital Commons Network^™

Mathematical Models Of Multisensory Detection And Decision-Making, Rebecca M. Brady

Doctoral

The brain seamlessly integrates signals from multiple sensory modalities to interpret the world efficiently. By using information from various senses, the brain can enhance its ability to detect and respond to stimuli more quickly and accurately. However, combining sensory cues from multiple modalities is only sometimes beneficial as it may lead to illusions and reduced behavioural performance. Behavioural and electrophysiological experiments have revealed that detection and decision-making strategies for multisensory cues evolve throughout human development and ageing. Additionally, studies have demonstrated that maladaptive multisensory processing is a key indicator of a proclivity to falls in older adults and individuals with …

Towards Efficient Continual Learning: From Memory Optimization To Foundation Models, Zilin Luo

Dissertations and Theses Collection (Open Access)

Continual learning, also termed lifelong learning, enables machine learning models to incrementally acquire new knowledge while mitigating the degradation of previously learned information—a capability essential for adapting to dynamic, real-world data environments. This dissertation investigates the core challenges of continual learning and extends its application to enhancing training efficiency in the era of foundation models. The first part of this dissertation addresses the constraints of few-shot exemplar storage with a novel compression framework. While leveraging class activation maps to downsample non-discriminative pixels, we introduce an adaptive masking model, optimized through bilevel optimization, to store more exemplars efficiently. The second part …

Draft Final Silver Bow Creek Conservation Area (Sbcca) Butte Reduction Works (Brw) Air Monitoring For Interim Demolition Activities – Phase Ii Data Summary Report (Dsr), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Bpsou Unreclaimed Sites: Ur-46 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Update: Colorado River Basin Storage Continues Slide Toward System Crash, Anne Castle, Jack Schmidt, Eric Kuhn, Kathryn Sorensen, Katherine Tara

The Traveling Wilburys of the Colorado River

If the Colorado River Basin (Basin) experiences another dry year, similar to Water Year 2025, it is likely that reasonably accessible storage in Lake Powell and Lake Mead would be mostly depleted, even if consumptive uses and losses are at or near historic lows. Run-of-the-river operations would shortly ensue. This would be an outcome with devastating consequences. In contrast, if next year is very wet, similar to Water Year 2023, the Basin’s largest federal reservoirs would recover somewhat, but would provide only about two years of cushion before we find ourselves again in the same position we are in today, …

Oer Organic Chemistry I Lab Manual, Ji Kim

Open Educational Resources

This Organic Chemistry I Lab Manual presents ten inquiry-based modules that integrate green chemistry principles into every stage of the microscale laboratory experience. Students use Kontes microscale glassware to perform essential techniques, including distillation, recrystallization, extraction, chromatography, and nucleophilic substitution reactions. Each module features standardized learning objectives, pre-lab questions, microscale procedures, data tables, and post-lab analysis. Green Chemistry Connections explicitly links each experiment to the Twelve Principles, emphasizing waste prevention, safer solvents, renewable feedstocks, and accident reduction. From isolating caffeine from tea and lycopene from tomato paste to synthesizing cyclohexene via E1 elimination, students learn classical organic chemistry through an …

Self-Adjoint Extensions Of Symmetric Operators, Malak Mousa

ETDs from 2020-2029

This thesis introduces operators in Hilbert Space, definitions and properties. And then introduce a method for constructing a self-Adjoint extensions of a symmetric operator and illuminating the method by example.

Experimental Methods For Cryogenic Rare Event Detection: Cuore And Cupid, Alessandro Libenson

Physics

This senior project was written with the primary purpose of serving as a introductory guide for undergraduate students learning about the experimental methods used in the CUORE and CUPID Collaborations. In particular, this project is geared towards getting students in Dr. Gutierrez's research group at Cal Poly up to speed on what CUORE and CUPID actually do. I wrote this as an undergraduate aiming to help future undergraduates. For Cal Poly students, I would suggest the following prerequisites before reading this paper: Electronics and Instrumentation, Quantum Laboratory 1, and the equivalent of the coding/analysis class. It is also important to …

Hillslope Aspect And Other Potential Controlling Factors On The Spacing Of Periglacial Stone Stripes In Se Oregon, Blue Hansen

University Honors Theses

Stone stripes are a type of patterned landscape that can be polygenetic in origin, but in the High Lava Plains province are interpreted to be relict periglacial features based on similarities to active stone stripe formation in current periglacial settings. Periglacial stone stripes are hypothesized to form via frost process, including ice-driven cracking and soil heave which is dependent on temperature, long-term differences in temperature may contribute to differences in stone stripe patterns or density. Stone stripes in Oregon and Idaho have previously been studied using field techniques, but there is room for reexamination of temperature controls on hillslope density …

Agile In The Age Of Ai: Considerations And Improvements For Streamlining Developer Workflows, Stephen Feng

University Honors Theses

This paper examines the integration of AI language models into Agile developer workflows during a six-month software development project. Using the development of SagacityWall, a mindfulness-based social media application built by a team of eight undergraduates, it identifies three key areas in Agile processes where AI provided meaningful leverage: translating business requirements into actionable developer work tickets, accelerating framework research and technology stack decisions, and reducing onboarding friction through AI-assisted code scaffolding and Behavior-Driven Development story formatting. The study finds that AI meaningfully boosted productivity across these stages – not by replacing developer judgment, but by reducing overhead at each …

Towards Auto-Evaluation For Large Language Models, Jiahao Ying

Dissertations and Theses Collection (Open Access)

The rapid advancement of large language models (LLMs) has created an urgent need for evaluation methodologies that are timely, scalable, reliable, and informative. Conventional evaluation benchmarks, although essential for measuring model capabilities and guiding model development, are often constructed and maintained through labor-intensive human annotation. As LLMs continue to improve through increases in model scale, training data, and computational resources, static benchmarks may quickly lose discriminative power. Moreover, the growing use of large and diverse training corpora increases the risk of benchmark leakage, which can inflate evaluation results and obscure the true capabilities of models. These challenges call for a …

Anatomical Domain Shifts: Test-Time Heterogeneous Adaptation For 3d Human Pose Prediction, Qiongjie Cui, Pan Zhou, Jingjing Chen, Na Zhao

Research Collection School Of Computing and Information Systems

The research frontier in human pose prediction (HPP) is advancing toward continual test-time adaptation (TTA), where models must self-adapt to dynamic test distributions. To date, the homeostatic continual TTA remains the sole viable solution, which isolates the model parameters and update domain-sensitive ones. Despite mitigating full-body domain gaps, human anatomical heterogeneity (domain shifts often localize to specific regions) is ignored. This anatomical-agnostic approach forces uniform parameter adaptation across kinematically distinct segments, causing: over-adaptation of stable regions and under-adaptation of shift-prone articulations. To address it, we introduce TT-HA, a novel Test-Time Heterogeneous Adaptation that implicitly estimates domain changes for anatomical segments, …

On-The-Fly Generation-Quality Enhancement Of Deep Code Models Via Model Collaboration, Weifeng Sun, Naiqi Huang, Meng Yan, Zhongxin Liu, Hongyan Li, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

The growing prominence of deep code models in automating software engineering tasks is undeniable. However, their deployment encounters significant challenges in on-the-fly performance enhancement, which refers to dynamically improving the performance of deep code models during real-time execution. Conventional techniques, such as retraining or fine-tuning, are effective in controlled pre-deployment scenarios but fall short when adapting to on-the-fly adjustments post-deployment. CodeDenoise, a notable on-the-fly performance enhancement technology, leverages uncertainty-based methods to identify misclassified inputs and applies an input modification strategy to rectify classification errors. While effective for classification tasks, this approach is inapplicable to generative tasks due to two key …

A Pruning-Based Question-Answering For Interactive Video Search: A Simple Baseline, Yu Tong Cheng, Phuong Anh Nguyen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

There are various factors affecting the performance of video search. An imprecise query will enlarge search space and reduce the discriminative power of ranking functions. This problem is further exacerbated by the presence of numerous visually or semantically similar videos in large datasets. Consequently, users need to painstakingly browse through many highly similar candidates to locate the search target, leading to increased cognitive load and inefficient searching. Ideally, engaging users through interactive questioning to resolve uncertainties in the search process is an effective strategy for progressively narrowing down the search space. However, despite rapid advances in deep learning, generating informative …

Rode: Linear Rectified Mixture Of Diverse Experts For Food Large Multi-Modal Models, Pengkun Jiao, Xinlan Wu, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yu-Gang

Research Collection School Of Computing and Information Systems

Large Multi-modal Models (LMMs) have significantly advanced a variety of vision-language tasks. The scalability and availability of high-quality training data play a pivotal role in the success of LMMs. In the realm of food, while comprehensive food datasets such as Recipe1M offer an abundance of ingredient and recipe information, they often fall short of providing ample data for nutritional analysis. The Recipe1M+ dataset, despite offering a subset for nutritional evaluation, is limited in the scale and accuracy of nutrition information. To bridge this gap, we introduce Uni-Food, a unified food dataset that comprises over 100,000 images with various food labels, …

Interfold: Learning Interpretable Diffusion Manifolds Beyond Binary Samples, Alexander Vincent Lewi, Rainer Tan, Shengfeng He

Research Collection School Of Computing and Information Systems

We propose InterFold, a framework for learning and applying interpretable semantic manifolds in latent diffusion models, without requiring binary or paired supervision. Existing methods for semantic editing either rely on limited paired data or uncover only coarse, unsupervised directions that fail to capture user-specific, fine-grained attributes. InterFold addresses these limitations by learning a target attribute manifold in the H-space of diffusion models using only a set of positive, unlabeled examples. To edit a new image, InterFold projects its H-space representation toward this learned manifold through test-time optimization, enabling precise, identity-preserving modifications of complex, non-binary concepts. To make these edits effective …

Sam3-Litetext: An Anatomical Study Of The Sam3 Text Encoder For Efficient Vision-Language Segmentation, Chengxi Zeng, Yuxuan Jiang, Ge Gao, Shuai Wang, Duolikun Danier, Bin Zhu, Stevan Rudinac, David Bull, Fan Zhang

Research Collection School Of Computing and Information Systems

Vision-language segmentation models such as SAM3 enable flexible, prompt-driven visual grounding, but inherit large, general-purpose text encoders originally designed for open-ended language understanding. In practice, segmentation prompts are short, structured, and semantically constrained, leading to substantial over-provisioning in text encoder capacity and persistent computational and memory overhead. In this paper, we perform a large-scale anatomical analysis of text prompting in vision–language segmentation, covering 404,796 real prompts across multiple benchmarks. Our analysis reveals severe redundancy: most context windows are underutilized, vocabulary usage is highly sparse, and text embeddings lie on a low-dimensional manifold despite high-dimensional representations. Motivated by these findings, we …

Not Too Early, Not All At Once: Design Tensions In Ai-Mediated Self-Disclosure In Online Dating, Pei-Hua Tsai, Tianyi Zhang, Emran Bin Elias Poh, Anthony Tang, Yung-Ju Chang

Research Collection School Of Computing and Information Systems

Online dating relies on self-disclosure, yet initial conversations are fragile: users must navigate uncertainty around timing, boundaries, and reciprocity with little shared context. While advances in AI raise the possibility of mediating disclosure, how such support might reshape the experience of early-stage relational disclosure remains underexplored. We conducted 29 semi-structured interviews to examine how daters envision AI-mediated self-disclosure in online dating. Our findings surface recurring design tensions rather than simple opportunities or risks. Participants welcomed guidance that could pace disclosure, support reflection, and reduce social awkwardness, but stressed preserving agency and authorship. They valued interpretive assistance for sense-making of ambiguous …

Context Matters: Auditing Gender Bias In T2i Generation Through Risk-Tiered Use-Case Profiles, Jose Luis Luna Campoverde, Yankun Wu, Xiaofei Xie, Noa Garcia

Research Collection School Of Computing and Information Systems

Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting to be integrated into higher-impact pipelines. Since generated images tend to reinforce stereotypes, producing representational erasure via “default” depictions and shaping perceptions of who belongs in certain roles, a growing body of work has proposed metrics to quantify gender bias in T2I outputs. Yet existing evaluations remain fragmented. Metrics are often reported without a shared view of what they measure, what assumptions they entail, or how their results should be interpreted under different deployment contexts. This limits the usefulness of gender …

Rc-Nf: Robot-Conditioned Normalizing Flow For Real-Time Anomaly Detection In Robotic Manipulation, Shijie Zhou, Bin Zhu, Jiarui Yang, Xiangyu Zhao, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Recent advances in Vision-Language-Action (VLA) models have enabled robots to execute increasingly complex tasks. However, VLA models trained through imitation learning struggle to operate reliably in dynamic environments and often fail under Out-of-Distribution (OOD) conditions. To address this issue, we propose Robot-Conditioned Normalizing Flow(RC-NF), a real-time monitoring model for robotic anomaly detection and intervention that ensures the robot's state and the object's motion trajectory align with the task. RC-NF decouples the processing of task-aware robot and object states within the normalizing flow. It requires only positive samples for unsupervised training and calculates accurate robotic anomaly scores during inference through the …

Ai In Healthcare: Regulatory Guidelines And Judge-Made Negligence Principles For Ai Implementers, Gary K. Y. Chan

Research Collection Yong Pung How School Of Law

The use of artificial intelligence (AI) in healthcare may, notwithstanding its potential benefits, result in harm to patients from allegedly negligent acts or omissions by hospitals and medical doctors. In such circumstances, how should the principles in the tort of negligence (duty of care, breach, causation, remoteness of damage, and defences) respond to AI innovations in healthcare? In particular, how may the standard of care expected of hospitals and medical doctors be informed by regulatory guidelines? We refer to case law precedents and regulatory guidelines on the roles and responsibilities of doctors and hospitals as AI implementers. Importantly, they prompt …

On The Fractional Laplacian Type Operator, Maysam Abdulnaser Zain

Theses

In this thesis, we study analytical structures arising from Dunkl theory and their

applications to harmonic analysis and fractional Laplacian operators. Dunkl operators are differential–difference operators associated with finite reflection groups, providing a natural generalization of the classical Fourier analysis through the introduction of root systems and multiplicity functions. Within this framework, several classical transforms appear as special cases of the (k,a)-generalized Fourier transform. We study the generalized Fourier transform ��ₖ,ₐ, its kernel B_k,a (x,y), and the associated translation operator and convolution structures. Using these tools, we construct the corresponding heat …

Crab: A Novel Clustering Score Using Clustering With Rivals And Buddies For Unsupervised Learning, Allen Choi

Master's Theses

Unsupervised clustering algorithms today are used across a wide variety of fields such as biology, engineering, and industry in order to classify observations into groups where labels are not provided. This can provide important latent information regarding the observations within groups, as well as insight regarding the groups themselves. In order to judge the optimal number of clusters for an unsupervised clustering algorithm, many methods exist such as the Elbow Method and Silhouette Score; however, these methods come with drawbacks and are not necessarily flexible across many unsupervised methods. We present a novel clustering score framework relying on a resampling-based …

Potential Recyclable Materials In Buildings: A Framework For Greenhouse Gas Emissions Assessment Of Residential Buildings In Singapore, Pradeep Alva, Riccardo Talami, Wanyu Pei, Goran Sibenik, Martin Mosteiro-Romero, Clayton Miller, Rudi Stouffs

Research Collection College of Integrative Studies

As countries aim to reduce resource consumption and greenhouse gas (GHG) emissions, Whole Life Carbon Assessment (WLCA) has become a vital method for quantifying embodied and operational GHG emissions. However, few studies have conducted WLCA on an urban scale, often addressing operational or embodied GHG emissions in isolation without considering their cumulative impact. This study introduces a city-wide WLCA framework to assess the potential recyclable materials of urban building stock, using Singapore as a case study with 5915 public residential buildings. Upfront GHG emissions are calculated from material intensity and building information, while operational emissions are based on energy use …

Gobbling Activity And Use Of Structural Habitat At Nest Sites By Wild Turkeys (Meleagris Gallopavo) In Western Nebraska, Robyn M. Dausener

School of Natural Resources: Dissertations, Theses, and Student Research

Wild turkey (Meleagris gallopavo) populations in Nebraska have declined substantially in recent years. Understanding gobbling chronology and its environmental drivers may inform spring hunting season structure and management actions. I used autonomous recording units (ARUs) in two ecologically distinct regions of Nebraska, the northwestern (NW) Pine Ridge landscape, and the southwestern (SW) agricultural landscape, to quantify gobbling activity from 2023-2025. I paired gobbling data with nesting chronology, cumulative daily hunting pressure, weather conditions, and moon phase using Bayesian generalized additive mixed models. Gobbling peaked during mid-to-late April in both regions, preceding peak nest initiation and incubation, with no …

A Copula-Based Framework For Multivariate Count Time Series With Mixed Marginal Distributions, Dimuthu Fernando, Yuxin Wen, Wimarsha Jayanetti

Engineering Faculty Articles and Research

We developed a class of multivariate integer-valued time series models using copula theory. Each count time series is modeled as a Markov chain, with serial dependence characterized through copula-based transition probabilities for Poisson and negative binomial marginals. Cross-sectional dependence is modeled via a trivariate Gaussian or a “t-copula”, allowing for both positive and negative correlations and providing a flexible dependence structure. Model parameters are estimated using likelihood-based inference, where the trivariate Gaussian or t-copula integrals are evaluated through standard randomized Monte Carlo methods. Simulation results, along with an analysis of annual counts of major hurricanes (Category 3+) across the North …

Of Climate Justice And Magical Realism, Sonya Ziaja

Michigan Law Review

A review of Climate Justice: What Rich Nations Owe the World—and the Future. By Cass R. Sunstein.

Graded Contact Geometry And The Aksz Formalism, Ivan Contreras, Nicolas Martinez Alba, Rajan Amit Mehta

Mathematics Sciences: Faculty Publications

The AKSZ formalism is a construction of topological field theories where the target spaces are differential graded symplectic manifolds. In this paper, we describe an analogue of the AKSZ formalism where the target spaces are differential graded contact manifolds. We show that the space of fields inherits a weak contact structure, and we construct a solution to the analogue of the classical master equation, defined via the Jacobi bracket. In the n =1 case, we recover the Jacobi sigma model, and in the n = 2 case, we obtain three-dimensional topological field theories associated to Courant-Jacobi algebroids.

Legal Ethics Of Ai Snake Oil: Navigating The Hype, Harm, And Hope Of Legal Ai, Drew Simshaw

Michigan Law Review

A review of AI Snake Oil.By Arvind Narayanan and Sayash Kapoor.

2026 June - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.