Physical Sciences and Mathematics Commons^™

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 …

Implicit Neural Representation For Image Reconstruction, Canyu Zhang

Theses and Dissertations

Image reconstruction seeks to restore corrupted images and recover visual content that has been lost or degraded. Such degradation may result from low resolution, occlusion, masking, or shadow interference. This problem has become an increasingly significant research topic, as visual information plays a central role in almost every aspect of modern life. Neural network based approaches have recently emerged as highly effective solutions for this task. In particular, convolutional neural networks and transformer based architectures have demonstrated remarkable success in producing visually convincing reconstructions. However, these models remain constrained in several important ways, one of the most critical being that …

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 …

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 …

Explainabledetector: Exploring Transformer-Based Language Modeling Approach For Sms Spam Detection With Explainability Analysis, Mohammad Amaz Uddin, Muhammad Nazrul Islam, Leandros Maglaras, Helge Janicke, Iqbal H. Sarker

Research outputs 2022 to 2026

Short Message Service (SMS) is a widely used and cost-effective communication medium that has unfortunately become a frequent target for unsolicited messages - commonly known as SMS spam. With the rapid adoption of smartphones and increased Internet connectivity, SMS spam has emerged as a prevalent threat. Spammers have recognized the critical role SMS plays in today's modern communication, making it a prime target for abuse. As cybersecurity threats continue to evolve, the volume of SMS spam has increased substantially in recent years. Moreover, the unstructured format of SMS data creates significant challenges for SMS spam detection, making it more difficult …

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 …

Enhancing Llm Code Generation: A Systematic Evaluation Of Multi-Agent Collaboration And Runtime Debugging For Improving Accuracy, Reliability, And Latency, Nazmus Ashrafi

Theses

The use of large language models (LLMs) for automated code generation has emerged as a significant focus within AI research. As these pretrained models continue to evolve, their ability to understand and generate complex code structures has opened up new possibilities for automating intricate programming tasks with greater accuracy. Although contemporary foundational models demonstrate promising results, researchers continue to explore optimal post-training strategies to enhance code quality. These include supervised fine-tuning, retrieval-augmented generation (RAG), debugging, and many others. In this thesis, I combine two such widely used post training approaches—namely (1) multi agent collaboration and (2) runtime execution of information-based …

“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.

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, …

Competition Of Light-And Phonon-Dressing In Microwave-Dressed Bose Polarons, G. M. Koutentakis, S. I. Mistakidis, F. Grusdt, H. R. Sadeghpour, P. Schmelcher

Physics Faculty Research & Creative Works

We theoretically investigate the stationary properties of a spin-1/2 impurity immersed in a one-dimensional confined Bose gas. In particular, we consider coherently coupled spin states with an external field, where only one spin component interacts with the bath, enabling light dressing of the impurity and spin-dependent bath-impurity interactions. Through detailed comparisons with ab-initio many-body simulations, we demonstrate that the composite system is accurately described by a simplified effective Hamiltonian. The latter builds upon previously developed effective potential approaches in the absence of light dressing. It can be used to extract the impurity energy, residue, effective mass, and anharmonicity induced by …

Effective Two- And Three-Body Interactions Between Dressed Impurities In A Tilted Double-Well Potential, F. Theel, A. G. Volosniev, D. Diplaris, F. Brauneis, S. I. Mistakidis, P. Schmelcher

Physics Faculty Research & Creative Works

We explore the impact and scaling of effective interactions between two and three impurity atoms, induced by a bosonic medium, on their density distributions. To facilitate the detection of mediated interactions, we propose a setup where impurities are trapped in a tilted double-well potential, while the medium is confined to a ring. The tilt of the potential breaks the spatial inversion symmetry allowing us to exploit the population of the energetically elevated well as a probe of induced interactions. For two impurities, the interaction with the medium reduces the impurity population at the energetically elevated well, which we interpret as …

Bound Deuteron-Antideuteron System (Deuteronium): Leading Radiative And Internal-Structure Corrections To Bound-State Energies, Gregory S. Adkins, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We evaluate the energy levels of the deuteronium bound system, which consists of a deuteron and an antideuteron, with a special emphasis on states with nonvanishing orbital angular momenta. The excited atomic bound states of deuteronium constitute probes for the understanding of higher-order quantum electrodynamic corrections for spin-1 particles in a bound system where the typical field strength of the binding Coulomb field (at a distance of the generalized Bohr radius) exceeds Schwinger's critical field strength. For states with nonvanishing angular momenta, effects due to the internal structure of the deuteron and virtual annihilation contributions are highly suppressed. Relevant transitions …

The Heart Of The Crab: Analyzing The Vhe Emission From The Crab Pulsar, Adi Empie, Thao Nguyen, Avery Archer

Annual Student Research Poster Session

The Crab Nebula is one of the most studied astrophysical objects at very-high-energies (VHE) and is one of the brightest sources of VHE gamma-rays. The Crab Nebula is a pulsar wind nebula with the Crab pulsar providing the energy and particles to power the nebula. The gamma-ray emission from the nebula and pulsar are understood to come from relativistic particles but the processes that are responsible for accelerating these particles is not well understood. Studying the highest energy emission from the Crab Nebula can provide valuable insight into the underlying emission mechanisms at work. This project was intended to examine …

Energetic Particle Detection In The Pfotzer Maximum Methods And Equipments, Scott Anderson, Jason Benyousky, Walae Dahmany, Tri Duong, Minh Mai

Annual Student Research Poster Session

The Balloon Assisted Stratospheric Experiments (BASE) measures atmospheric muons using an array of instruments carried by weather balloons. We seek to spend extended time in the region of highest intensity, the Regener-Pfotzer Maximum (Pfotzer Maximum) at 20 kilometers high. Using a set of Geiger Counters attached to a balloon, we can measure the secondary particles produced by atmospheric cascades at high altitudes. With risk of losing the balloon and the need to collect more data, we improved our payload with data-collecting components and experimented with a long-range data sender and receiver.

Iowa Waste Reduction Center Newsletter, October 2025, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Joe Bolick named NPPR Chair
--- Open House Party Recap
--- Green Brewery Certification has come to Missouri
--- Clear guidance, real results: IAEAP
--- AI training for Waste Partners

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 …

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 …

A Comprehensive Pipeline For Autonomous Surface Vehicle Navigation In Challenging Aquatic Environments, Mingi Jeong

Dartmouth College Ph.D Dissertations

The primary objective of this thesis is to develop and validate innovative and robust navigation methods for autonomous surface vehicles (ASVs) in challenging scenarios. These efforts aim to establish a complete autonomy pipeline for robotic decision-making systems, enabling high-level tasks such as environmental monitoring and autonomous transportation with broader impacts. The ocean economy contributes over 1.5 trillion USD annually, supporting diverse cultures and economies through tourism, fisheries, shipping, and renewable energy. The global marine industry handles over 90% of the world’s cargo transportation, underscoring its critical importance. Despite this significance, current maritime navigation relies heavily on human decision-making, which is …

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.

Use Of Modified Z-Domain Peptides To Specifically Label The Constant Region Of Immunoglobulin G And Vegf, Madeline Allen

Department of Chemistry: Dissertations, Theses, and Student Research

Antibodies are increasingly being used in medicinal therapies due to their ability to specifically bind to a target antigen. This fundamental behavior of antibodies has been used as a key component in drug development to address common problems with traditional drug molecules such as off-targeting, fast drug clearance, and low efficacy. This thesis provides some background into how antibodies can be used as potential treatments for a few diseases. Chapter 1 begins with an overview of the human immune system, and the role antibodies play within it. Then, the variety of ways in which antibodies can be used as medicinal …

Ge0.95sn0.05 On Si Avalanche Photodiode With Spectral Response Cutoff At 2.14 Μm, Justin Michael Rudie, Xiaoxin Wang, Rajesh Kumar, Grey Abernathy, Sylvester Amoah, Steven Akwabli, Hryhorii Stanchu, Perry C. Grant, Bao-Hua Li, Wei Du, Jifeng Liu, Shui-Qing Yu

Electrical Engineering and Computer Science Faculty Publications and Presentations

GeSn-based avalanche photodiode operating in shortwave infrared wavelength was demonstrated in this work. A separate absorption and charge multiplication structure was employed to take advantage of long wavelength absorption in GeSn and low impact ionization ratio of Si. Due to lattice mismatch between Si and GeSn that would degrade GeSn material quality if with direct growth, a 240-nm-thick Ge buffer was utilized, which simultaneously allows for the transporting photo generated electrons from the GeSn absorber to Si multiplication layer. Spectral response showed the cutoff wavelength beyond 2.1 mu m at room temperature. Dark current and capacitance-voltage measurements indicated a punch-through …

Insect-Foundation: A Foundation Model And Large Multimodal Dataset For Vision-Language Insect Understanding, Thanh-Dat Truong, Hoang-Quan Nguyen, Xuan-Bac Nguyen, Ashley Dowling, Xin Li, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Multimodal conversational generative AI has shown impressive capabilities in various vision and language understanding through learning massive text-image data. However, current conversational models still lack knowledge about visual insects since they are often trained on the general knowledge of vision-language data. Meanwhile, understanding insects is a fundamental problem in precision agriculture, helping to promote sustainable development in agriculture. Therefore, this paper proposes a novel multimodal conversational model, Insect-LLaVA, to promote visual understanding in insect-domain knowledge. In particular, we first introduce a new large-scale Multimodal Insect Dataset with Visual Insect Instruction Data that enables the capability of learning the multimodal foundation …

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 …

Leveraging Machine Learning And Causal Inference For Loan Default Prediction, Luca Guida

Doctoral Dissertations and Master's Theses

This research explores a systematic application of machine learning techniques combined with causal inference to predict loan defaults in peer-to-peer lending. Accurately forecasting loan defaults is crucial for mitigating financial risk and optimizing lending strategies. This analysis is based on multiple datasets of loan applications spanning over a decade, containing detailed financial and credit information about borrowers. Beginning with extensive Exploratory Data Analysis (EDA) coupled with scaling strategies, the research identifies key trends in loan performance across a large number of factors, such as interest rates or borrower creditworthiness, and one objective is to determine from the many available predictors …

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 …

Unresolved Image Simulation For Space Situational Awareness Applications, Fox Coniglario

Doctoral Dissertations and Master's Theses

The knowledge of what lies in orbit around Earth is at best a guess. Decades of spaceflight, debris buildup, and vehicle collisions have contributed to a large number of objects that are simply not able to be catalogued. Ongoing efforts to catalog debris in orbit have reached limits by conventional measures and as such, research is active in the field of in-orbit space situational awareness. This thesis intends to help fill a hole in the development of such orbital platforms by assisting the development of image processing software pipelines though the simulation of unresolved space imagery. The simulation uses accurate …