Physical Sciences and Mathematics Commons^™

Improved Extraction And Detection Of Disinfection Byproducts, Impacts Of Wildland-Urban Interface Wildfires On Drinking Water, And Change In Disinfection Byproducts Over Time In Chlorinated Vs. Chloraminated Distribution Systems, Patrick Thomas Justen

Theses and Dissertations

Drinking water disinfection is critical to prevent the occurrence of waterborne pathogens in drinking water. However, disinfection causes the unintended formation of disinfection byproducts (DBPs) through the reaction of disinfectants (e.g., chlorine, chloramine) with natural organic matter (NOM), algal matter, or anthropogenic pollutants present in source waters. Exposure to DBPs is associated with increased bladder cancer, colorectal cancer, miscarriage, and birth defects. The U.S. EPA currently regulates eleven DBPs in drinking water—four trihalomethanes, five haloacetic acids, bromate, and chlorite. However, research shows that DBP related toxicity in drinking water is driven mainly by other, non-regulated DBPs, particularly iodinated DBPs and …

Gravitational Perturbations And Quantum Field Interactions In Modified Spacetime Backgrounds, Abhishek Rout

Theses and Dissertations

This dissertation presents a study of gravitational perturbations and quantum field dynamics in modified spacetime backgrounds. The research is motivated by the quest to understand how quantum fields behave in curved spacetimes, particularly when extensions to general relativity, such as Chern--Simons modifications, are introduced.

The first part examines quantum field interactions with oscillating solitonic backgrounds, inspired by breather-type solutions of the sine--Gordon equation. Fermion bound states are shown to undergo destabilization due to the oscillatory background, leading to particle production and flux propagation to infinity. These results highlight the challenges of maintaining localized fermionic states in time-dependent topological backgrounds.

The …

Coefficients Of The Characteristic Polynomial Of A Hypergraph And Their Combinatorial Properties, Utku Okur

Theses and Dissertations

We investigate the combinatorial properties of the characteristic polynomial $\phi_\mathcal{H}\ev{t}$ of a hypergraph $\mathcal{H}$, in particular, its coefficients. Due to a classical result of Jacobi, the generating function of closed walks at a vertex $u$ in a graph $G$ is determined by the rational function $\phi_{G-u}(t) / \phi_G(t)$. The connection between closed walks of $G$ and its characteristic polynomial has a known elegant proof via an application of Viennot's Heaps of Pieces framework, where cycles are taken as pieces and the concurrence relation is sharing a vertex. Here, we prove a bijection between heaps with a unique maximal piece containing …

Thesis: Comparing Functional And Effective Brain Connectivity Metrics For Eeg, Diksha Srishyla

Theses and Dissertations

Background:Brain connectivity measures have been used to study communication between brain regions using electroencephalography (EEG). Functional and effective connectivity estimate the synchronization and the flow of information between regions, respectively. However, findings from studies using different measures to investigate similar connections do not converge. To guide the selection of functional and effective connectivity measures in future studies, we systematically compared a set of measures in the context of resting state EEG. We examined four functional connectivity metrics (coherence (Coh), the imaginary part of coherence (imCoh), the corrected imaginary part of phase lagged value (ciPLV), the debiased weighted phase-locking index (dwPLI)) …

Multi-Perspective Feature Learning For Facial Expression Recognition In The Wild, Xiangyu Hu

Theses and Dissertations

With the rapid progress of deep learning, Facial Expression Recognition (FER) has seen substantial improvements in performance, particularly “in the wild” meaning real world conditions. Despite these advances, most existing methods extract features from facial images as the sole emotional cues, which limits the model’s ability to capture the full complexity of human emotional expressions.

In reality, facial expressions are composed of diverse and multi-perspective information, including appearance-based cues and geometric structural deformations due to activations of facial muscles. Depending exclusively on one type of representation may fail to exploit the complementary nature of these cues, an issue that becomes …

New Approaches On Source Coding For Quantum Stochastic Sources And Implementation Of Quantum Fanout Gate, Rabins Wosti

Theses and Dissertations

The accurate computation of advanced quantum algorithms like Shor’s integer factorization, quantum phase estimation (QPE), and the quantum Fourier transform (QFT) requires quantum circuits of considerable size and depth. It is difficult to achieve reliable computation with deep quantum circuits due to the limited coherence times of the current noisy quantum devices. The quantum fanout gate is known to be a powerful primitive for reducing the depth of many quantum circuits (Høyer and Špalek 2003; Gottesman and Chuang 1999). Shallow or constant-depth quantum circuits are desirable for both near-term and fault-tolerant quantum computations as they reduce noise and allow faster …

Computational Analogies In The Era Of Large Language Models, Amarakoon Mudiyanselage Thilini Wijesiriwardene

Theses and Dissertations

Analogical reasoning is an important part of human cognition requiring the integration of abstract reasoning, pattern recognition, and background knowledge. Despite significant advances in language modeling, the capacity of current methods to accurately identify, model, and evaluate analogies remains fundamentally underexplored.

Analogies enable individuals to perceive deep similarities between superficially different situations. Effective analogy-making requires integrating knowledge about the external world with abstract reasoning and pattern recognition capabilities. While current language models (LMs), trained on massive textual corpora using autoregressive or masked objectives, achieve impressive performance across Natural Language Processing (NLP) tasks such as text generation, summarization, and classification, their …

Investigating The Influence Of Instructional Strategies On The Development Of Procedural And Conceptual Knowledge In Advanced Algebra Ii Students, Maura Frances Yinger

Theses and Dissertations

This mixed-methods action research study investigated the influence of instructional strategies shown to improve students’ procedural and conceptual understanding in a rational expressions and equations unit in Advanced Algebra II. The instructional strategies used in the study include comparing, self-explaining, and exploring before instruction. The students (N=27) completed a pre-test and a post-test, both of which were followed by questions asking students to justify their responses on two questions. All students also responded to six digital self-explanation journal prompts. Randomly selected students were placed into three homogenous groups to participate in performance task observations. Analysis of the data …

Assessing The Effectiveness Of Bridge Grate And Pipe Cattle Guard Designed To Mitigate Ocelot Road Mortality On Texas State Highway, Rupesh Maharjan, John H. Young Jr., Kevin W. Ryer, Md. Saydur Rahman, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

The mitigated and fenced section of State Highway 100, extending from Laguna Vista to Los Fresnos, includes five wildlife crossing structures and 16 modified cattle guards (also called wildlife guards) installed to mitigate ocelot road mortality. Bridge grate and pipe wildlife guards were deployed at vehicle entries, and we evaluated their effectiveness in preventing meso-carnivores and ungulates from entering the roadway through the fence gaps from April 2020 to 2024. Wildlife guards collectively were >82% effective in repelling ungulate attempts to enter the roadway, while only 16.64% of meso-carnivore attempts were repelled. The pipe wildlife guard (PWG) design repelled 86.79% …

Tess Light Curves And Period Changes In Low-Mass Eclipsing Binary Bb Persei, Marek Wolf, Petr Zasche, Miloslav Zejda, Martin Mašek, Andrej Mudray, Hana Kučáková, Waldemar Ogłoza, Jaroslav Merc, Jan Kára, Vojtěch Dienstbier

Physics & Astronomy Faculty Publications

We present a detailed analysis of the low-mass detached eclipsing binary system BB Persei, which contains two K-type stars in a circular orbit with a short period of 0.4856 d. We used light curves from the Transiting Exoplanet Survey Satellite (Tess), which observed BB Per in five sectors, to determine its photometric properties and a precise orbital ephemeris. The solution of the Tess light curve in Phoebe results in a detached configuration, where the temperature of the primary component was fixed to T 1 = 5 300 K according to Lamost, which gives us T 2 = 5 050 ± …

Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Remedial Action Work Plan (Rawp): Bres No. 104 (Colorado Dump) North Slope, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Pioneering The Pacific In Earth Sciences: Uh Mānoa Students Establish The First Sigma Gamma Epsilon Chapter In HawaiʻI And Beyond, Ken H. Tungpalan, Olivia Schmitt, Wellington Rothschild, Susannah Heller, Alyssa N. Kamanu

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Iota Delta Chapter is proud to announce its establishment as the first Sigma Gamma Epsilon chapter in the Pacific, with the hope that it will serve as a foundation for future chapters across the region. The chapter has been created at the University of Hawaiʻi at Mānoa within the School of Ocean and Earth Science and Technology (SOEST). The Department of Earth Sciences is loosely divided into three working research divisions (Geophysics and Tectonics [G&T], Marine and Environmental Geology [MEG], and Volcanology, Geochemistry, and Petrology [VGP]), with numerous laboratories and research facilities.

Sigma Gamma Epsilon Chapter And Student Awards For Academic Year 2024–2025, Lee S. Potter

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon (SGE) encourages efforts to broaden the education and impact of its members through community outreach. In Academic Year 2024–2025, seven (7) awards were given at the chapter level: The Chapter Service Award to Gamma Sigma, Gamma Chi, and Epsilon Sigma; and The James C. Walters Quality Chapter Award to Gamma Sigma, Gamma Chi, Epsilon Sigma, and Theta Beta. Individual merit was recognized through the W. A. Tarr awards given to thirty-two members by their respective chapters. Two awards, the Austin A. Sartin and Charles J. Mankin Outstanding Poster Awards, were given to two students …

47th Biennial Convention Of Sigma Gamma Epsilon, Western Illinois University, April 11–13, 2025, Richard L. Ford, Lee S. Potter

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon (SGE), the national honorary society for the Earth sciences, held its 47th biennial convention (April 11–13, 2025) at the Quad Cities campus, located in Moline, Illinois, of Western Illinois University (WIU). The convention was hosted by SGE’s Delta Psi Chapter and the Department of Earth, Atmospheric, and Geographic Information Sciences at WIU. Ten (10) of SGE’s approximately 57 active collegiate chapters sent delegates to the convention. The traditional convention field trip, an exploration of the Paleozoic stratigraphy and economic geology of the Quad Cities area of Illinois and Iowa, made stops at the Fryxell …

Better Digital Contracts With Prosocial Friction-In-Design, Brett Frischmann, Moshe Y. Vardi

Faculty Publications

Contract law is supposed to enable people to reach genuine agreements and cooperate. If this ideal was ever a reality, the rise of mass market contracts and boil­erplate rendered it pure fiction. Modern consumer contracts are incomprehensible to most people. No one reads them anyway.

Digital contracting involves design features that amplify traditional boilerplate harms and create others. For example, digital contracting is too cheap; low marginal costs lead to overexpansion in scale and scope. To make matters worse, the loss of autonomy from repeat engagement with digital contracting systems is pernicious. People become increasingly predictable and programmable as digital …

Improving Universities Through The Use Of Ai & Transformative Technology: A Case Study Analysis At The University Of South Carolina, Cameron A. Caulk

Senior Theses

This thesis aims to give university leaders a practical guide to implementing AI, using lessons learned from the University of South Carolina’s experience as a case study. The project started with a review of literature and industry practices for the Finance & Administration division, which led to key deliverables like AI usage guidelines, DoIT’s position paper on AI systems, and the ParkUSC parking app. One ongoing project, Project Shuttlecock, even sets the stage for future AI initiatives at the university.

AI holds immense promise, but universities often hesitate due to concerns about ethics, costs, and the learning curve for staff …

Revised Draft Final 2022 Unreclaimed Sites Sampling: Ur-20 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

The Science Of Sound: Studying The Cognitive, Emotional, And Physiological Effects Of Frequency, Genre, And Music, Jett Yarborough

Senior Honors Theses

Music influences emotion, physiology, and cognition, yet little is known about how the frequency it is tuned to affects these influences. Prior research has shown that music tuned to 432 Hz can reduce stress, lower blood pressure, and improve sleep. My colleagues and I conducted two studies to investigate this. Our research found that music tuned to 432 Hz promotes a significant increase in memory retention and induces a state of focus and relaxation. These results suggest that shifting from the standard tuning frequency of 440 Hz to 432 Hz could have a profoundly positive impact on our daily lives. …

The Compass - Volume 94 Issue 3 - Complete Issue, Scott R. Beason

The Compass: Earth Science Journal of Sigma Gamma Epsilon

No abstract provided.

Harnessing Se Community Knowledge For Developer-Centric Code Intelligence, Chengran Yang

Dissertations and Theses Collection (Open Access)

The integration of Large Language Models (LLMs), particularly those tailored for programming tasks—referred to as code LLMs—has created novel opportunities to enhance developer productivity. These advanced models automate routine and repetitive coding tasks, such as code generation and debugging, and enable faster prototyping and more efficient problem-solving. Despite these remarkable advantages, the current generation of code LLMs exhibits notable limitations that impact their practical effectiveness in real-world software engineering scenarios. These models frequently produce code that is inefficient or suboptimal in runtime performance, demonstrate opaque reasoning processes, and struggle to adapt effectively to diverse developer contexts and specific requirements. Moreover, …

Hlcg: A Hierarchical Lane-Changing Gaming Decision Model For Heterogeneous Traffic Flow On Two-Lane Highways, Tianyi Wang, Chong He, Hao Li, Yixuan Li, Yiming Xu, Yangyang Wang, Junfeng Jiao

Research Collection College of Integrative Studies

Discretionary lane-changing behavior is one of the most common highway operations, which seriously affects traffic efficiency and safety. Nowadays, connected and automated vehicles (CAVs) are advancing rapidly, though not yet fully widespread. As a result, a mixed traffic environment with traditional human-driven vehicles (HDVs) and CAVs will persist for the foreseeable future. To achieve effective automatic lane-changing maneuvers, it’s necessary to propose a lane-changing decision model for heterogeneous traffic flow on two-lane highways. This paper firstly extends longitudinal car-following models based on the intelligent driver model and lateral lane-changing models using quintic polynomial curves to accommodate heterogeneous traffic flow, and …

Ai-Enabled Multi-Layer Security Operations: A Combined Siem, Ids, And Threat Intelligence Model For Adaptive Cyber Defense, Mohamad Khayat

Dissertations

This dissertation presents a comprehensive framework for the evolution of Security Operation Centers (SOCs) through the integration of advanced artificial intelligence (AI), blockchain, and optimization techniques. Motivated by the increasing complexity of cyber threats and the limitations of traditional reactive SOC strategies, this work begins with a systematic literature review that identifies critical gaps in current SOC operations. Based on these insights, a reference architecture is proposed to guide the integration of intelligent components into SOC environments. To address the challenge of secure and trustworthy information sharing, a blockchain-based threat intelligence platform is developed, leveraging Byzantine Fault Tolerance and Zero-Knowledge …

Juxtaposing Approaches To Risk-Based Ai Governance In Different ‘Rights’ Contexts: A Comparative Analysis Between Singapore And The Eu, Jane Loo, Mark Findlay

Research Collection Yong Pung How School Of Law

Comparative analysis of European and certain Asian approaches to governance often degenerates into simplistic dichotomies based on universal human rights assumptions. This chapter rejects such dualities, ill-informed by theory and historical reflection. The emerging argument is founded on a historical realist approach to theorising difference. Assisted by Polanyi’s double movement, the detailed substantive comparison is preceded by considerations of how recent trends in governing AI have uniformly adopted a countermovement against the dis-embedding of data and technology from the social leading to a risk/responsibility paradigm. From here, a more nuanced reflection of AI governance approaches in the EU and Singapore …

Memory-Efficient 4-Bit Preconditioned Stochastic Optimization, Jingyang Li, Kuangyu Ding, Kim-Chuan Toh, Pan Zhou

Research Collection School Of Computing and Information Systems

Preconditioned stochastic optimization algorithms, exemplified by Shampoo, outperform first-order optimizers by offering theoretical convergence benefits and practical gains in large-scale neural network training. However, they incur substantial memory overhead due to the storage demands of non-diagonal preconditioning matrices. To address this, we introduce 4-bit quantization for Shampoo’s preconditioners. We introduce two key methods: First, we apply Cholesky decomposition followed by quantization of the Cholesky factors, reducing memory usage by leveraging their lower triangular structure while better preserving spectral properties to minimize information loss. To our knowledge, this is the first quantization approach applied to Cholesky factors of preconditioners. Second, we …

Cookingdiffusion: Cooking Procedural Image Generation With Stable Diffusion, Yuan Wang, Bin Zhu, Yanbin Hao, Chong-Wah Ngo, Yi Tan, Xiang Wang

Research Collection School Of Computing and Information Systems

Recent advancements in text-to-image generation models have excelled in creating diverse and realistic images. This success extends to food imagery, where various conditional inputs like cooking styles, ingredients, and recipes are utilized. However, a yet-unexplored challenge is generating a sequence of procedural images based on cooking steps from a recipe. This could enhance the cooking experience with visual guidance and possibly lead to an intelligent cooking simulation system. To fill this gap, we introduce a novel task called cooking procedural image generation. This task is inherently demanding, as it strives to create photo-realistic images that align with cooking steps while …

Probabilistic Prototype Calibration Of Vision-Language Models For Generalized Few-Shot Semantic Segmentation, Jie Liu, Jiayi Shen, Pan Zhou, Jan-Jakob Sonke, Stratis Gavves

Research Collection School Of Computing and Information Systems

Generalized Few-Shot Semantic Segmentation (GFSS) aims to extend a segmentation model to novel classes with only a few annotated examples while maintaining performance on base classes. Recently, pretrained vision-language models (VLMs) such as CLIP have been leveraged in GFSS to improve generalization on novel classes through multi-modal prototypes learning. However, existing prototype-based methods are inherently deterministic, limiting the adaptability of learned prototypes to diverse samples, particularly for novel classes with scarce annotations. To address this, we propose FewCLIP, a probabilistic prototype calibration framework over multi-modal prototypes from the pretrained CLIP, thus providing more adaptive prototype learning for GFSS. Specifically, FewCLIP …

From Holistic To Localized: Local Enhanced Adapters For Efficient Visual Instruction Fine-Tuning, Pengkun Jiao, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yugang Jiang

Research Collection School Of Computing and Information Systems

Efficient Visual Instruction Fine-Tuning (EVIT) seeks to adapt Multimodal Large Language Models (MLLMs) to downstream tasks with minimal computational overhead. However, as task diversity and complexity increase, EVIT faces significant challenges in resolving data conflicts. To address this limitation, we propose the Dual Low-Rank Adaptation (Dual-LoRA), a holistic-to-local framework that enhances the adapter’s capacity to address data conflict through dual structural optimization. Specifically, we utilize two subspaces: a skill space for stable, holistic knowledge retention, and a rank-rectified task space that locally activates the holistic knowledge. Additionally, we introduce Visual Cue Enhancement (VCE), a multi-level local feature aggregation module designed …

Exploring Object Status Recognition For Recipe Progress Tracking In Non-Visual Cooking, Franklin Mingzhe Li, Kaitlyn Ng, Bin Zhu, Patrick Carrington

Research Collection School Of Computing and Information Systems

Cooking plays a vital role in everyday independence and well-being, yet remains challenging for people with vision impairments due to limited support for tracking progress and receiving contextual feedback. Object status — the condition or transformation of ingredients and tools — offers a promising but underexplored foundation for context-aware cooking support. In this paper, we present OSCAR (Object Status Context Awareness for Recipes), a technical pipeline that explores the use of object status recognition to enable recipe progress tracking in non-visual cooking. OSCAR integrates recipe parsing, object status extraction, visual alignment with cooking steps, and time-causal modeling to support real-time …

Reproducibility Debt In Scientific Software, Zara Hassan, Christoph Treude, Graham Williams, Michael Norrish, Alex Potanin

Research Collection School Of Computing and Information Systems

Reproducibility Debt (RpD) refers to accumulated technical and organisational issues in scientific software that hinder the ability to reproduce research results. While reproducibility is essential to scientific integrity, RpD remains poorly defined and under-addressed. This study introduces a formal definition of RpD and investigates its causes, effects, and mitigation strategies using a mixed-methods approach involving a systematic literature review (214 papers), interviews (23 practitioners), and a global survey (59 participants). We identify seven categories of contributing issues, 75 causes, 110 effects, and 61 mitigation strategies. Findings are synthesised into a cause-effect model and supported by taxonomies of team roles and …

Teaching Diffusion Models To Ground Alpha Matte, Tianyi Xiang, Weiying Zheng, Yutao Jiang, Tingrui Shen, Hewei Yu, Yangyang Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

The power of visual language models is showcased in visual understanding tasks, where language-guided models achieve impressive flexibility and precision. In this paper, we ex tend this capability to the challenging domain of image matting by framing it as a soft grounding problem, enabling a single diffusion model to handle diverse objects, textures, and transparencies, all directed by descriptive text prompts. Our method teaches the diffusion model to ground alpha mattes by guiding it through a process of instance-level localization and transparency estimation. First, we introduce an intermediate objective that trains the model to accurately localize semantic components of the …