Digital Commons Network^™

Scientific Crosstalk: Natural Language Processing, Praveshika Bhandari

Theses and Dissertations

While sentiment analysis has made significant strides in domains such as social media and personal correspondence, its application to formal scientific writings remains under-explored. The crosstalk between emotional expressions in personal and professional communications has also received limited attention despite its potential to reveal insights into the emotional drivers of scientific creativity. Our research introduces a computational framework designed to detect and quantify emotional expressions across various documents over time. Leveraging state-of-the-art transformer models fine-tuned on domain-specific corpora, the framework models emotional tone distribution. Integrating emotion analysis with knowledge graph modeling enables the exploration of emotional trends alongside key scientific …

30 Db On-Chip Ultra-High Inverse Weak Value Amplification, Yuhan Mei, Meiting Song, Andrew N. Jordan, Jaime Cardenas

Mathematics, Physics, and Computer Science Faculty Articles and Research

Weak value amplification (WVA) has emerged as a powerful technique that enhances measurement precision. However, traditional table-top WVA setups and on-chip demonstrations have not achieved an amplification over 20 dB. The practical limit of the amplification is the fidelity of photon post-selection. To address this limit, we design a weak value device with an over 30 dB interferometer extinction ratio, where the stray light in the dark port is minimized with thermally tunable phase shifters. As a result, the device successfully shows 30 dB WVA, termed ultra-high WVA. This WVA optimization strategy by improving interferometer extinction is extensible to a …

A Large Language Model-Based Analysis Of Vulnerability Discovery In Windows Software, Puya Pakshad, Samson Quaye, Jamal Al-Karaki, Marwan Omar, Maurice E. Dawson

All Works

Source code security auditing is essential before software release in order to identify programming faults that may lead to vulnerabilities and functional failures. In this paper, we present a structured security assessment of the Windows App SDK by integrating multiple static analysis tools with a context-aware and disagreement-aware Large Language Model (LLM) interpretation layer. Although static analyzers are effective in reporting potential weaknesses, their raw outputs often contain redundant alerts, limited contextual explanation, and inconsistent severity assignments. To address these limitations, the proposed LLM-based interpretation layer normalizes and de-duplicates alerts, filters context-limited or nonactionable warnings, and refines severity prioritization under …

Olaf: Towards Robust Llm-Based Annotation Framework In Empirical Software Engineering, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the Operationalization for LLM-based Annotation Framework (OLAF), a conceptual framework that organizes key constructs: reliability, calibration, drift, consensus, aggregation, and transparency. The paper …

C*-Extreme Quantum Instruments; Completion And Disintegration Of Completely Positive Maps, Arghya Chongdar

Doctoral Theses

This thesis develops a comprehensive operator-algebraic framework for the study of completely positive (CP) instruments, with contributions spanning convexity theory, integration theory, completion problems, and disintegration theory. We begin by laying the foundational groundwork in the theory of C*-algebras and von Neumann algebras, introducing key structures such as CP maps, positive operator-valued measures (POVMs), and CP instruments, along with their dilation-theoretic properties. Pure and decomposable instruments are characterized via minimal bi-dilations, and CP instruments are realized as bivariate maps, providing a rigorous quantum analogue of classical joint measures. The thesis then investigates convexity-theoretic aspects of instruments. A structural characterization of …

Public Acceptance Of Meat-Reduction Policies Across Cultures: Comparing Singapore And Switzerland, Bianca Wassmann, Shu Tian Ng, Mark Chong, Angela K. Y. Leung, Michael Siegrist

Research Collection Lee Kong Chian School Of Business

Purpose – As meat-reduction policies are discussed across the globe, many are met with public resistance. Cultural values may help explain this pushback, yet their role in shaping support for food policy remains poorly understood. This study is the first to apply cultural cognition theory to food policy by examining how cultural worldviews shape the acceptance of meat-reduction interventions in Singapore and Switzerland—two economically developed countries with contrasting cultural profiles. Design/methodology/approach – In an online survey, participants (Singapore: n = 357; Switzerland: n = 495) rated their acceptance of 11 meat-reduction interventions (e.g. taxes, subsidies, labelling). We then analysed to …

Deployment-Aware Deep Learning For Computer Vision: Efficient Architectures From 3d Segmentation To Mixed Reality, Bahar Uddin Mahmud

Dissertations

Deep learning has become the dominant approach for solving vision-centric problems; however, its successful deployment in real-world applications remains limited by high computational cost, data dependency, and insufficient integration with practical and human-centered environments. While state-of-the art deep learning models often achieve impressive performance in controlled settings, they frequently fail to generalize or operate efficiently under deployment constraints such as limited resources, complex data modalities, and real-time interaction requirements. These limitations motivate the need for a deployment-oriented deep learning framework that balances accuracy, efficiency, and practical usability.

This dissertation investigates the design and deployment of efficient deep learning architectures for …

Cfalr: Collaborative Filtering-Augmented Large Language Model For Personalized Fashion Outfit Recommendation, Yujuan Ding, Junrong Liao, Yunshan Ma, Yi Bin, Wenqi Fan, Tat-Seng Chua, Qing Li

Research Collection School Of Computing and Information Systems

Personalized outfit recommendation poses a significant challenge in e-commerce and social media platforms, requiring systems that balance user preferences with aesthetic compatibility. Collaborative filtering (CF) provides a traditional solution for this, but it struggles with data-sparse scenarios and complex user-item-outfit relationships. Meanwhile, existing template-based approaches are constrained by rigid pre-designed structures. To bridge these research gaps, we introduce CFALR (Collaborative Filtering-Augmented Large Language Model for Recommendation), a novel framework that synergizes collaborative filtering with large language models for personalized outfit recommendation. Specifically, CFALR describes user-outfit interactions in natural language and leverages LLMs to capture fashion semantics while employing CF-enhanced embeddings …

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 …

What's The Big Picture? Capturing All The Companions To The Lowest-Mass Stars, Eliot Vrijmoet, K. Ward-Duong, Susan Niu, Alette Matthews, Todd Henry, Lucy Williams

Astronomy: Faculty Publications

The M dwarfs are frequently orbited by low-mass stars and terrestrial planets, yet rarely by the brown dwarfs and Jovian planets between those mass regimes. The collective orbital architectures of those unusual substellar companions thus present a valuable opportunity to learn about those objects' formation, dynamical evolution, and original circumstellar environments. Accessing those parameter spaces, however, requires complementary observing techniques to truly map orbits and thoroughly assess the masses and mass ratios that occur. Here we present our pilot study of five M dwarfs with strong evidence of potentially substellar companions, combining 20+ years of astrometric monitoring from RECONS with …

A Systematic Review Of Intrusion Detection Systems For Internet Of Medical Things: Performance, Efficiency, Explainability, And Generalization, Oswald Adohinzin, Youssef Harrath

Research & Publications

The Internet of Medical Things (IoMT) has transformed health care delivery through medical devices, remote patient monitoring, and real-time clinical decision support. However, the proliferation of IoMT devices introduces security vulnerabilities that put patient safety and data privacy at risk. Intrusion Detection Systems (IDS) have emerged as essential components for protecting IoMT networks from cyberattacks. This article presents a systematic review of IoMT-IDS research, analyzing 53 high-quality papers published between 2020 and 2025, identified through database searches spanning 2016–2025 across IEEE Xplore, Springer, ScienceDirect, and ACM Digital Library. We organize the literature through a comprehensive taxonomy spanning classical machine learning …

A Machine Learning Framework For Residential District Cooling: Forecasting Consumption, Explaining Drivers, And Evaluating Decarbonization Pathways, Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan

All Works

District Cooling Systems (DCS) in the Middle East, while energy-efficient, are significant contributors to carbon emissions. This study introduces a novel framework to decarbonize DCS operations by integrating predictive machine learning, explainable AI (XAI), and renewable energy planning, all grounded in extensive real-world data. Leveraging a unique dataset from 59 residential buildings in the UAE—including energy consumption, climate variables, and building features—we developed a high-fidelity cooling load forecasting model. Following a rigorous chronological validation methodology, the Random Forest model was identified as the most robust, achieving a strong performance (R² = 0.8256, RMSE = 11,668.31). Outdoor temperature was confirmed …

Social Media Is A Juggernaut: Lagged Correlation Analysis Using Ngram Data On “Internet” And “Social Media” With Amplification By The Advent Of The “Iphone”, William Zywiak, Gao Niu, Nicolas Petrell, Victoria Nichele, Kirsten Hokeness

Mathematics and Economics Faculty Journal Articles

The amount of new information transmitted per day can be overwhelming. The data available through Ngram Viewer allows statistical examination to determine the most salient topics, as well as lagged correlation and lagged variance to support possible causal connections between concepts. Using this database, we determined that COVID, crypto, microplastics, and especially social media are important topics of the last few years. We also present results that suggest the development of the internet and the iPhone fueled the prominence of social media, and the access of the iPhone also increased access to the internet.

Exploring Regenerative Vegetable Systems On The Central Coast Of California, Una S. O'Connell

Master's Theses

As climate change and current agricultural practices place pressure on the long term sustainability and resilience of food production systems, there is growing interest in whether existing agricultural systems can adapt to maintain productivity while improving environmental outcomes.

This study evaluated the effects of regenerative versus standard organic vegetable production systems on yield, insect communities, and weed suppression across three field trials conducted on California's Central Coast. In addition, I collected baseline soil health data for all trials. Trials 1 and 2 were carried out at the Cal Poly San Luis Obispo Organic Farm using cabbage and broccoli as cash …

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 …

Western Kentucky University Stormwater Utility Survey 2026, Warren Campbell

SEAS Faculty Publications

In the U.S., more than 2200 stormwater utilities have been enacted. This year, we have expanded the survey to include stormwater utilities in other countries. Many of these stormwater assessments are called taxes, but if the assessment is recurring, is not an ad valorem tax, and is dedicated to stormwater purposes, we call it a stormwater utility. With the help of ChatGPT we have been able to identify 25 stormwater fees in Australia. We were also able to identify 3 in New Zealand, and some in Europe as well.

Updates To The Caniform Fauna (Carnivora, Caniformia) Of The John Day Formation, Oregon, Usa, John D. Orcutt, Kevin C. Talbott, Michael J. Monroe, Nicholas A. Famoso

Biology Faculty Scholarship

The John Day Formation of central Oregon preserves a diversity of Oligo-Miocene caniform carnivorans, many of which were first described from the formation. However, many historically important specimens lack detailed locality or stratigraphic information, complicating any analysis of faunal change through time. Here, we describe 16 new specimens of caniforms from the John Day Formation, most with precise stratigraphic information. We report multiple specimens of the amphicyonids Daphoenus Leidy, 1853, Paradaphoenus cuspigerus (Cope, 1878), and Temnocyon altigenis (Cope, 1878), all previously known from the formation. We also report the first definitive occurrence of the hesperocyonine canid Osbornodon Wang, 1994 from …

Ms110 Syllabus: Introduction To Computers, Information Systems, And Artificial Intelligence, Wei Zhang

Management Science and Information Systems Faculty Publication Series

This is a syllabus for Professor Wei Zhang's MS110: Introduction to Computers, Information Systems and Artificial Intelligence Course within UMass Boston's College of Management. This is an Open Educational Resource and can be remixed, copied, redistributed, altered and reused as long as permission is given to the original creator.

Identifying Textual Predictors Of Early Termination In Clinical Trials In Medicine: An Explainable Machine-Learning Study, Rohan Ramnarain

Dissertations, Theses, and Capstone Projects

About one in five clinical trials in medicine ends early, wasting valuable resources and reducing the evidence available for developing life-saving medical treatments. This project uses a method called Trial2Vec, which is a self-supervised machine-learning method that converts clinical trial documents into dense numerical representations that capture their key design and clinical characteristics, to turn each proposed clinical trial’s written protocol into a compact numerical profile (a process referred to as embedding). These profiles are then paired with a predictive machine learning models to identify the words and phrases in the trial documents that can signal a higher risk of …

Ppg-Sport: A Dataset For Reliable Heart Rate Monitoring From Wrist Ppg Under Dynamic Sports Conditions, Changshuo Hu, Hung Manh Pham, Yiming Zhang, Guanru Yan, Xiao Ma, Yuezhong Wu, Thivya Kandappu, Archan Misra, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) has become a cornerstone of physiological sensing in wearable devices, enabling non-invasive monitoring of heart rate and related biomarkers. However, its reliability deteriorates sharply under dynamic, high-intensity, or non-periodic motions such as those in sports, where existing datasets fail to capture realistic wrist dynamics. To address this gap, we introduce PPG-Sport, the first large-scale dataset designed for heart rate monitoring from wrist-worn PPG under real sports conditions. The PPG-Sport dataset includes synchronized PPG, inertial measurement unit (IMU), and electrocardiography (ECG) recordings from both wrists of 30 participants across six representative activities: stationary, walking, running, badminton, table tennis, and …

High-Pressure Studies Of Magnetic Topological Materials, Greeshma Chireckal Jose

ETDs from 2020-2029

Quantum technology leverages the principles of quantum mechanics to transform emerging fields such as quantum computing, spintronics, and next-generation electronics. A crucial step in advancing this frontier is the detailed understanding of fundamental quantum phenomena in materials that can drive quantum innovation. This research aims to systematically investigate quantum phase transitions and unconventional emergent behaviors in magnetic topological materials subjected to external pressure. This study focuses on three representative systems: EuCd2As2, EuMnBi2, and FeSn, each serving as a model for exploring intrinsic magnetic topological states. EuCd2As2, a candidate Weyl semimetal (WSM), is expected to exhibit pressure-induced topological phase transitions, making …

Iowa Waste Reduction Center News, June 2026, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Thank you, Leslie
--- Zane joins the IWRC
--- DNR Air Fee changes
--- What does MSEI assistance look like?
--- P2 Green Brewery Certification webinars
--- Energy Efficiency resources
--- Industry News

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 …

2026 Cyber-Resilient Health Care Workshop Report, Malcolm Schongalla, Sergey Bratus

Computer Science Technical Reports

The ISTS and the Dartmouth College Cybersecurity Cluster hosted the successful, inaugural Cyber-Resilient Health Care (CRHC) Workshop, March 5th & 6th, 2026. The event theme was "Innovation and Implementation," in response to the need to shift from reactive to proactive resiliency measures in the healthcare sector. Approximately 30 experts in clinical health care, cybersecurity, medical technology, policy, and innovation met to discuss solution-focused innovations addressing hard, cyber-related problems in health care. The agenda featured keynotes, an expert panel, innovation pitches, small group discussions, and a tabletop infrastructure disaster exercise. Participants gained insights into the obstacles and solutions involved in supporting …

Cloud Tank: Virtual Reality Performance Instrument For Embodied Audiovisual Remixing, Asya Ulger

Computer Science Senior Theses

Traditionally, live audiovisual performances are made behind a desk using a laptop and an audio controller. This setup restricts the performer’s movements and separates the artist from their work. Moreover, it narrows what counts as the performance to the output alone — the audience is preconditioned to treat the projected image and sound as the whole event, and not the artist producing it. Cloud Tank challenges this by positioning the performer’s body as the instrument, using virtual reality. As the performer, I mix spatialized audio and drive beat-aligned, reactive video layers through hand movement and hand-pose recognition. The audiovisual output …

Introduction To Mathematical Analysis Ii, Beatriz Lafferriere, Gerardo Lafferriere, Mau Nam Nguyen

PDXOpen: Open Educational Resources

These lecture notes complement the book Introduction to Mathematical Analysis I, Third Edition, with sections on integration, numerical series, series of functions, and selected advanced topics. Together, both volumes support a one semester or two-quarter course on introductory mathematical analysis.

Adopt/Adapt

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Ai Interview Helper: A Tool For Assisting Search And Rescue Long-Profile Interviews, Dylan P. Starink

Master's Theses

In Search and Rescue (SAR) operations, time pressure and limited interviewer experience can lead to missed opportunities when interviewing a missing person’s friends and family. This thesis presents a real-time, end-to-end system that provides context-aware follow-up question suggestions as interviews unfold. Leveraging large language models (LLMs) and agentic design patterns, the system is intended to support interviewers by helping them identify relevant follow-up questions and pursue potentially overlooked lines of inquiry.

The system was evaluated through three mock interviews with two SAR interviewer participants across two events. Given the limited sample size, the results provide early insights into the feasibility …

Flood Risk Assessment And Water Diversion Scenarios For Terre Haute, Indiana Based On Time-Series Remote Sensing And In-Situ Measurements, Hung Q. Ha

2026 Spring Reports (Terre Haute)

The City of Terre Haute has faced growing concerns over the increasing frequency and intensity of riverine flooding along the Wabash River, alongside risks associated with urban inundation. To create more safely floodable areas – specifically by locating wetland areas using GIS and researching government ordinances on development in those areas – the City of Terre Haute sought to better understand flood patterns and identify viable floodwater diversion strategies. The project was formally titled as “Pattern of Flooding along the Wabash River in Vigo County and Scenarios for Floodwater Diversion”. Faculty and students from Geospatial Intelligence Lab, Department of Earth …

Utah Growing Water Smart: The Water-Land Use Integration Guidebook For Central Utah, Kelly Kopp, Joanna Endter-Wada

Utah Growing Water Smart

The Utah Growing Water Smart workshop brings together key staff and water and land use planning decision makers to help communities build a more resilient and sustainable water future. The workshop uses a range of public engagement, planning, communication, and policy implementation tools to help community teams realize their water efficiency, smart growth, watershed health, and water resiliency goals.

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.