Digital Commons Network^™

Phosphate Removal And Recovery From Aqueous Solutions Using Iron-Coated Steel Slag, Siavash Ebrahimzadeh, Guanghui Hua, Christopher Schmit

Civil and Environmental Engineering Faculty and Student Publications

Phosphate pollution from human activities significantly contributes to the eutrophication of aquatic ecosystems. Additionally, phosphorus is a finite, irreplaceable resource, making its management and recovery critical. This study explores the use of iron-coated steel slag (ICS) as a cost-effective material for phosphate removal and recovery from water. Ferric chloride was used to coat electric arc furnace slag via oven drying under various conditions. Batch adsorption tests evaluated phosphate adsorption, and the optimum coating conditions were identified as 0.5–1 mm slag, 0.5 M FeCl₃, and coating pH 1. The effect of solution pH and coexisting ions on phosphate removal were also …

Frameworks And Life Cycle Assessment For Reinforced Concrete Bridges For Sustainability In Transportation, Yu-Fu Ko, Jessica Gonzalez

Mineta Transportation Institute

Bridge structures are critical components of California’s transportation network, with reinforced concrete (RC) bridges being among the most widely used. Extending the lifespan of these structures can lead to significant reductions in environmental impacts. However, California’s frequent seismic activity has repeatedly exposed the vulnerability of existing RC bridges, highlighting the urgent need for seismic retrofitting and maintenance to improve infrastructure resilience against earthquakes and to increase sustainability. This research used detailed computer simulations known as nonlinear finite element models, which are highly detailed computer models, incorporating section damage indices to predict damage and assess structural deficiencies in RC bridges during …

Building An Inclusive Ai Chatbot For Diverse Student Communities At Cal Poly: Uplift Ai, Gideon Telahun

College of Engineering Summer Undergraduate Research Program

This research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and …

“The Good Life” Of Ai, Lauren Smith

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

Artificial Intelligence, or AI, is powered by data centers, sprawling warehouses of servers that require massive amounts of electricity and water to operate. The United Statesalready has more than 1,000 data centers, with nearly 400 more on the way.

Nebraska is next. Google is building a major new data center in North Lincoln, adding to the 18 operating across the state.

Our collective use of tools like ChatGPT, Google’s Gemini and Microsoft’s Copilot has fueled a boom in generative AI, and with it a surge in energy and water consumption.

The need for AI regulation isn’t a future concern. It’s …

Creativity In Large Language Models, Robert Kenneth Morain

Theses and Dissertations

As artificial intelligence systems approach human-level performance across a wide variety of domains, creative domains remain a critical yet underexplored area of research. Unlike traditional AI tasks with well-defined objectives, creative tasks rely on inherently subjective measures, making them particularly challenging for machines that lack human experiential context. This dissertation establishes the fundamental importance of creativity in AI systems and presents methods for improving and evaluating the creative capabilities of LLMs on the pathway toward AGI. This work addresses and examines key limitations in current LLM creativity through model innovations, development frameworks, and comparative studies. The dissertation develops novel architectural …

Genai Literacy Framework For Library Instruction, Adwoa Boateng, Jennifer Freer, Greyson Pasiak, Erich Short, Ryan Tolnay, Rit Libraries

Presentations and other scholarship

A generative artificial intelligence (genai) framework for library instruction. This short framework is designed to incorporate into existing library instruction across many subject areas. The basic elements of the framework are: know & understand genai, use & evaluate genai, and library research & discovery with genai.

Closing The Loop On Textile Waste: Policy, Technology, And Consumer Behavior In Sustainable Fashion, Anthony Amotoe-Bondzie

Collected Student Papers

Textile waste has become one of the most visible consequences of the fashion industry’s linear production and consumption model, where materials are rapidly extracted, transformed, consumed, and discarded. This paper critically examines how sustainable fashion can move beyond isolated recycling efforts toward a more integrated circular economy framework. Rather than treating textile waste as only an end-of-life problem, the study analyzes it as a systems issue shaped by overproduction, weak product design, limited recovery infrastructure, fragmented regulation, and consumer habits that normalize short garment lifespans. The paper argues that closing the loop on textile waste requires coordinated interventions across policy, …

(Si15-093) Dynamics Of The Generalized Nonlinear Schrödinger Equation With A Source Using An Analytical Method, Manish Raghav, Manoj .

Applications and Applied Mathematics: An International Journal (AAM)

In the present article, an analytical method is used to obtain hyperbolic, trigonometric, and rational solutions of the generalized nonlinear Schrödinger (GNLS) equation with a source. The ability of solitons to preserve their shapes during propagation makes them suitable for optical fiber communication. Solutions to the generalized nonlinear Schrödinger equation with a source can also describe solitons, and understanding their dynamics helps to design communication systems based on solitons. The analytical method used is compelling and effective for finding exact solutions to various nonlinear evolution equations (NLEEs). To further understand the phenomena, we create 3−D, contour, and 2−D graphs of …

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 Pastor As Romantic Author: Ai, Preaching, And The Unacknowledged Inheritance Of Authenticity, Daniel Plate, James Hutson

Faculty Scholarship

This article interrogates contemporary reactions to sermons produced with generative technologies through a historical–conceptual lens, arguing that widespread judgments of such outputs as “soulless,” “generic,” or lacking a “beating heart” are best explained by an unacknowledged inheritance from nineteenth-century Romantic expressivism. Rather than treating resistance to machine authorship as a theological verdict on computational incapacity, the study reconstructs how Romanticism centered authorship in sincere self-expression and solitary genius, displacing earlier heraldic expectations that prized fidelity to a received message. Methodologically, the analysis combines intellectual history with discourse analysis of global Christian experiments in synthetic composition (2020–2025), denominational guidance, and media …

Deep Learning For Hate Speech Detection: A Comparative Study, Jitendra Singh Malik, Hezhe Qiao, Guansong Pang, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Automated hate speech detection is an important tool in combating the spread of hate speech, particularly in social media. Numerous methods have been developed for the task, including a recent proliferation of deep-learning based approaches. A variety of datasets have also been developed, exemplifying various manifestations of the hate-speech detection problem. We present here a largescale empirical comparison of deep and shallow hate-speech detection methods, mediated through the three most commonly used datasets. Our goal is to illuminate progress in the area, and identify strengths and weaknesses in the current state-of-the-art. We particularly focus our analysis on measures of practical …

Tactile Data Comics: Combining Step-By-Step Presentation Of Tactile Graphics With Verbal Narration For The Blind And Visually Impaired, Yang Jiao, Ruoting Sun, Rong Luo, Xiwen Yao, Xinran She, Kotaro Hara, Yuewen Zhang, Xinyi Fu

Research Collection School Of Computing and Information Systems

Tactile graphics on a refreshable display have proven effective in enabling visually impaired people to comprehend pictorial content. To further evaluate the effectiveness of refreshable tactile displays in blind education, we designed tactile data comics, a method that combines step-by-step presentation of tactile graphics with verbal narration. We conducted a user study with sixteen visually impaired students to compare tactile data comics against verbal-only and static tactile graphics. Our findings show that tactile data comics significantly improve participants’ comprehension and engagement during the learning experience. These empirical results suggest that the integration of refreshable tactile displays and tactile data comics …

Diffusion Of Innovation Of Port Decarbonization Measures : A Case Study Approach, Clint Rocky Mcculloch, Lucas Fernando Vaquero Roviriego

Port Management Dissertations

The dissertation is a study of how stakeholders diffuse innovation in port decarbonization strategies through a case study approach, with emphasis on the Diffusion of Innovation (DOI) relating to the technical and operational measures in the developing regions. Port, being a critical hub in global supply chains, have to manage the increasing pressure of reducing greenhouse gas (GHG) emissions in alignment with International Maritime Organization (IMO) 2023 GHG strategy as well as the Paris Agreement. However, there is a gap in empirical research, specifically in non-European regions like South America and the Caribbean, highlighting the need for insights from stakeholders’ …

A Better Great Plains: Bridging The Implementation Gap For A Better Future, David W. Sandahl

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

The Northern Great Plains is experiencing extensive native grassland loss and landscape degradation, jeopardizing both ecological integrity and the socio-economic systems that rely upon these ecosystems. In an early effort to lessen degradation, the United States Department of Agriculture (USDA) introduced the Conservation Reserve Program (CRP) which generated ecosystem services benefits such as reduced soil erosion, improved water quality, and increased species diversity through the retirement of cropland and rangeland for 10- or 15-year contracts. However, CRP has not fully modernized alongside today’s agriculturalists and adoption remains shaped by an historically fraught socio-political context characterized by deep-seated mistrust between ranchers, …

(Si15-010) On Perturbations Of Gabor Frames, Jamkhongam Touthang

Applications and Applied Mathematics: An International Journal (AAM)

Stability plays a crucial role in frame theory and its applications. The present paper studies the interaction between Gabor frames and perturbations, presenting perturbation results related to small changes of the frame parameters and the window functions both in regular and irregular settings. Examples are provided for illustration. Additionally, the paper briefly discusses algorithms pertinent to Gabor frames under perturbations and highlights challenging areas in the field.

Mitigating Cross-Modal Representation Bias For Multicultural Image-To-Recipe Retrieval, Qing Wang, Chong-Wah Ngo, Yu Cao, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Existing approaches for image-to-recipe retrieval have the implicit assumption that a food image can fully capture the details textually documented in its recipe. However, a food image only reflects the visual outcome of a cooked dish and not the underlying cooking process. Consequently, learning cross-modal representations to bridge the modality gap between images and recipes tends to ignore subtle, recipe-specific details that are not visually apparent but are crucial for recipe retrieval. Specifically, the representations are biased to capture the dominant visual elements, resulting in difficulty in ranking similar recipes with subtle differences in use of ingredients and cooking methods. …

Diffusionmat: Alpha Matting As Deterministic Sequential Refinement Learning, Yangyang Xu, Shengfeng He, Wenqi Shao, Yong Du, Kwan-Yee K. Wong, Yu Qiao, Jun Yu, Ping Luo

Research Collection School Of Computing and Information Systems

In this paper, we introduce DiffusionMat, a novel image matting framework that employs a diffusion model for the transition from coarse to refined alpha mattes. Diverging from conventional methods that utilize trimaps merely as loose guidance for alpha matte prediction, our approach treats image matting as a deterministic sequential refinement learning process. This process begins with the addition of noise to trimaps and iteratively denoises them using a pre-trained diffusion model, which incrementally guides the prediction towards a clean alpha matte. The key innovation of our framework is a correction module that adjusts the output at each denoising step, ensuring …

A Data-Driven Framework For Optimal Retail Store Location, Ming Hui Tan

Dissertations and Theses Collection (Open Access)

This study develops a data-driven framework for optimal retail store location planning that integrates road network analysis, mobility data and optimization techniques. By addressing the limitations of traditional approaches that rely on outdated census data and manual site selection, this research offers a scalable and adaptable solution for retail expansion in diverse urban environments. Chapters 1 and 2 establish the foundational context and theoretical underpinnings of this research. Chapter 1 introduces the research problem and motivation, highlighting the limitations of existing approaches and defining three key research objectives: automating candidate site identification, improving footfall estimation, and developing a scalable multi-site …

Examining The City Of Philadelphia’S Proposition Bill #250768 “Stop Trashing Our Air Act” By Addressing Waste Management And Environmental Justice Challenges In Chester City, Pennsylvania And The Philadelphia Region, Dylan Wascavage

Student Publications

This paper offers a policy analysis of the City of Philadelphia’s "Stop Trashing Our Air Act" by summarizing the reasoning for the bill's call to action, its legislative background, identifying key players and their strategies, and how these strategies reflect philosophies of environmental governance and the policy cycle. It seeks to inform local community members and policymakers of the implications of this bill, to highlight the lack of state and federal intervention on this issue, and to address the environmental justice and pollution concerns of the Covanta waste incinerator in Chester City and its neighboring communities. It also aims to …

Trust And Ethics In Ai-Driven E-Commerce: Persuasion Vs. Privacy, Akriti Nepal

Student Publications

This study examines how AI-driven features in e-commerce influence user satisfaction and the role of trust in these interactions. Using a survey-based dataset of 100 consumers, we investigated whether trust moderates or mediates the impact of AI persuasiveness and perceptions of bias, intrusiveness, and preference understanding on satisfaction. Results indicate that AI’s perceived ability to understand user preferences strongly predicts satisfaction, while trust partially mediates the relationship between helpful AI features and urgency messages and user satisfaction. Conversely, trust did not significantly moderate these relationships, and concerns about bias and intrusiveness had minimal impact. Findings suggest that AI-driven satisfaction is …

A Culturally Responsive Approach Toward Influencing General Chemistry Students’ Belonging And Perceptions Of Chemistry And Science: Metacognition Instruction Versus Role Model Narratives, Althea Berlyn, Rukayya Fall, Shanmugam Puvanendran, Jacinta M. Mutambuki

Chemistry Faculty Research and Publications

This study compared the influence of two distinct interventions, STEM role model narratives and metacognitive instruction, on students’ perceived sense of belonging in the General Chemistry 1 course and STEM program, as well as their perceptions of chemistry and science. We also investigated whether the influence reported differs between the two interventions and the manner in which students articulate this influence. Additionally, variations in the reported positive influence were analyzed based on gender, race/ethnicity, and first-generation status. Grounded in a culturally responsive teaching framework, the study utilized a randomized design to collect qualitative data through an open-ended questionnaire. One group …

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 …

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 …

“Toward A World Where Many Worlds Fit”: Thinking-Feeling Our Way In The Pluriverse, Michael Burns

Sustainability Research & Practice Seminar Presentations

Dr. Michael Burns, English, shares "Toward a 'World Where Many Worlds Fit': Thinking-Feeling Our Way into the Pluriverse" Recording shares the lecture portion. Following the lecture participants shared their thoughts with one another.

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 …

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

The Compass: Earth Science Journal of Sigma Gamma Epsilon

No abstract provided.

Rethinking Teaching Evaluation Reports: Designing Ai-Transformed Student Feedback For Instructor Engagement, Ruoxi Shang, Keri Mallari, Au Wei Bin Yeong, Ken Yasuhara, Anthony Tang, Gary Hsieh

Research Collection School Of Computing and Information Systems

Student feedback is critical for improving teaching, yet instructors often avoid reading evaluations due to emotional burden and information overload. We present a systematic exploration of how language models can distill and transform student evaluations into adaptive, actionable insights. Through a systematic design space exploration combining 4 feedback strategies (removing harmful content, paraphrasing criticism, sandwiching negatives, adding constructive suggestions) with 4 presentation formats (themes, cards, letters, chatbots), we created six AI-augmented prototypes of teaching evaluations. Interviews with 16 post-secondary instructors revealed that effective use of AI in feedback processing should: (1) support action formation through focused views and divergent thinking, …

Polymind: Parallel Visual Diagramming With Large Language Models To Support Prewriting Through Microtasks, Qian Wan, Jiannan Li, Huanchen Wang, Zhicong Lu

Research Collection School Of Computing and Information Systems

Prewriting is the process of generating and organising ideas before a first draft. It consists of a combination of informal, iterative, and semi-structured strategies such as visual diagramming, which poses a challenge for collaborating with large language models (LLMs) in a turn-taking conversational manner. We present Polymind, a visual diagramming tool that leverages multiple LLM-powered agents to support prewriting. The system features a parallel collaboration workflow in place of the turn-taking conversational interactions. It defines multiple ''microtasks'' to simulate group collaboration scenarios such as collaborative writing and group brainstorming. Instead of repetitively prompting a chatbot for various purposes, Polymind enables …

Governance In The Absence Of Government, Tracy Hresko Pearl

Faculty Articles

Artificial intelligence (AI) is advancing at an unprecedented pace, with generative systems exerting growing influence over social, economic, and political life. While Al offers opportunities for innovation and efficiency, it also poses risks ranging from misinformation and job displacement to existential threats if highly autonomous systems evade human control. Across industry, government, and civil society, there is broad consensus that Al requires oversight.

Yet traditional U.S. regulatory approaches face six significant barriers: (1) technology outpacing legislation, (2) limited Al expertise among policymakers, (3) regulatory capture, (4) political gridlock, (5) outdated governance structures, and (6) the inherent complexity of Al. Combined …

Meshless Discrete Velocity Boltzmann Model For Porous Media Flow, Amandine Maidenberg

Doctoral Dissertations and Master's Theses

This dissertation explores the combination of two sophisticated techniques for addressing computational fluid dynamics: the discrete velocity Boltzmann equation (DVBE) and the localized collocation meshless model with upwinding (U-LCMM). The DVBE is a high-level model that describes the foundations of transport phenomena by addressing the microscale motions of particles themselves and the effect of their aggregate behaviors on continuum principles. This equation integrates multiple scales of phenomena; while it can be used for fluid flow at Navier-Stokes scales, it can also resolve fine features that can only be described at the molecular level. This type of model is necessary for …