Digital Commons Network^™

Flooding Behavior Near The Us/Canada Border: Complications And Approaches, Maria T. Dodson

Honors College Theses

Flood forecasting remains a major challenge due to the nonlinear nature of hydrological systems and uncertainties in environmental data. This study aimed to address the prevalent challenges that arise from forecasting flooding behavior. To address the inherent complexity of hydrological forecasting, a machine learning framework was developed and trained on major contributing factors. To achieve an optimal balance between computational efficiency and predictive performance, a Gated Recurrent Unit (GRU) was selected as the optimal machine learning model. As the chosen dataset, North American Land Data Assimilation System Phase 2 (NLDAS2), is known to have inaccuracies in the important feature Relative …

Impacts Of Upgrading Gcc On The Srtuner Compiler Autotuning Algorithm, Jonathan D. Butterfield

Theses and Dissertations

An often-overlooked research gap is the applicability of research over time. The impact of updating the GNU Compiler Collection version was investigated for the SRTuner compiler optimization research. Versions 7 through 14 were tested using documented flags and recommended flag dependencies. Quality controls measured and enforced consistency across test runs and benchmarks. The performance of SRTuner was compared to a random control while the impact of enforcing flag dependencies was evaluated. The most influential flags were investigated by turning them off in isolation, but results were mixed. It was determined that enforcing flag dependencies resulted in improved performance, but the …

Rapid Kinetic Fluorogenic Quantification Of Malondialdehyde In Ground Beef, Keshav Raj Bhandari

Theses and Dissertations

Presented herein is rapid kinetic fluorogenic method to quantify malondialdehyde (MDA) in ground beef, utilizing 2-thiobarbituric acid (TBA) as the fluorogenic probe. This assay significantly shortens the total analysis time, from sample preparation to data acquisition, to just six minutes presenting a major advancement over traditional methods that typically require two hours and multiple instruments. The assay’s robustness against matrix interferences was validated using sample volume variation and standard addition calibration methods. Additionally, the effects of ambient exposure to air, washing, and cooking on MDA content in raw ground beef were quantified. While both ambient exposure to air and cooking …

A Trigger For The Autonomous Decommissioning Of Smart Devices, Ravindra Mangar, Jared Chandler, Jingyu Qian, Carl A. Gunter, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Smart devices are ubiquitous in modern environments, yet their decommissioning phase remains poorly studied and often overlooked in system design. We define secure decommissioning as the process by which a smart device securely disconnects from its environment and makes sensitive data inaccessible. If not decommissioned, devices may retain sensitive information – such as security credentials or user-behavior data that could be recovered by an adversary. Unfortunately, some users may forget to decommission a device when they dispose or sell it, and cannot decommission a device that is lost or stolen. This paper investigates a trigger mechanism for individual wireless smart …

Toward A Unified Network Flow Framework: From Conservation Principles To Fluid Dynamics Models, Zonghan Zhang

Theses and Dissertations

Network flows govern a wide range of critical systems, from tangible infrastructures like transportation and power grids to replicable processes such as information spread and epidemics. While tangible flows obey conservation laws and physical constraints, replicable flows, like rumors or viruses, can grow, decay, or vanish unpredictably. Despite their increasing interaction in real-world settings, these flow types are typically modeled in isolation, using disconnected mathematical frameworks. This dissertation presents a unified modeling approach that bridges the gap between conserved and replicable flows by embedding principles from fluid dynamics into graph-based propagation models. I introduce physically informed extensions to classical models, …

Modern Technology Addiction: Developer Duty Of Care, Jonah Hampton

Honors College Theses

Technology addiction includes any frequent use of technology which interferes in the user’s life. The subject continues growth as an epidemic and research field, yet prior literature does not often analyze the role of technology developers. This study performs a literature and legal synthesis to evaluate user and company responsibility, implications of responsibility, and promising solutions. Post 2020 literature was selected for coverage on context, addictive features, effects, solutions, or perspectives on law. Legal examples from different addiction industries were also selected for analysis to understand previous precedents. The study found a pattern of addictive traits, persuasive design, and recurring …

Assessing Water Quality And Algae In Wetland Reserve Easements In The Alluvial Valleys Of Mississippi And Louisiana, Avery June Wissmueller

Theses and Dissertations

Wetlands in agricultural landscapes play a critical role in improving water quality by retaining and transforming nutrients and pollutants. In the Mississippi Alluvial Valley (MAV), widespread conversion of bottomland hardwood forests to row-crop agriculture has diminished this natural function. The Wetland Reserve Easement (WRE) program restores wetlands on marginal farmland to recover ecosystem services. In this study, I evaluated water quality and algal productivity in WREs compared to natural reference wetlands and crop sites. Restored wetlands showed improved water quality compared to crop sites and were often comparable to or intermediate between reference wetlands. Seasonal variation and hydrologic differences shaped …

Using Quantum Annealing For Sampling And Pattern Generation In Generative Machine Learning And Catastrophic Forgetting Mitigation, Abdelmoula El Yazizi

Theses and Dissertations

The first goal of this dissertation was to understand the reasons for the absence in previous investigations of significant and consistent improvements in the trainability of Restricted Boltzmann Machines (RBM) when the Quantum Annealer (QA) was used for sampling from the RBM probability distribution. The second goal was to address the shortcomings of those previous investigations, explore possibilities of improving RBM training, and identify other machine learning applications that could benefit from sampling or from generating patterns by the QA. The first part of this dissertation focused on a Local-Valley (LV) centered approach to assessing the quality of sampling. QA-based …

From Textbook To Classroom: Gaps In Mathematical Representation And Translation In Nepali Education, Deepak Basyal

Mathematics and Statistics

Translating real-world problem contexts into mathematical symbols is a key skill in curricula worldwide. This study examines Nepali students’ abilities to translate words into symbols and how Nepali textbooks from earlier grades support the development of these skills. To investigate this phenomenon, a sequential explanatory study was conducted with a test for 10th graders and an analysis of Grades 6—9 textbooks. Results show that students struggle to convert real-world contexts into mathematical symbols, while textbooks provide limited opportunities for practice. In particular, students have difficulty translating symbols back into real-world situations, suggesting a link between textbook opportunities and achievement. These …

Education In The Planetarium: A Practical Approach, Matthew Fyfe

Honors Projects

This project proposes live planetarium programming built within the 5E instructional model. It creates a practical application of this with lesson modules surrounding topics in observational astronomy. Specifically, there are investigations into instrumentation through CCD cameras and data collection and processing through spectroscopy and photometry with light curve folding with activities highlighting each. Each module is broken down into segments corresponding to the learning cycles of the 5E model, and as they are self contained in this way can be used piecemeal in different combinations.

Long-Term Calibration And Validation Of Stability Of The Auger Engineering Radio Array Using The Diffuse Galactic Radio Emission, A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, R. Aloisio, B. Fick, Et Al.

Michigan Tech Publications

The Auger Engineering Radio Array (AERA) measures radio emission from high-energy extensive air showers. Consisting of 153 autonomous radio-detector stations spread over 17 km^2, it detects radio waves in the frequency range of 30 to 80 MHz. Accurate characterization of the detector response is crucial for proper interpretation of the collected data. Previously, this was achieved through laboratory measurements of the analog chain and simulations and measurements of the antenna's directional response. In this paper, we perform an absolute calibration using the continuously monitored sidereal modulation of the diffuse Galactic radio emission. Calibration is done by comparing the average frequency …

Investigating The Effect Of Kcl Stress In Raphanus Sativus, Mason P. Oelke

ATU Honors Projects

Potassium is an essential macronutrient for plant growth and development, yet excessive potassium fertilization can induce salt stress with detrimental consequences for crop productivity and nutritional quality. Despite its agricultural relevance, potassium chloride induced stress remains significantly understudied compared to classical sodium-based salinity. This thesis investigates the physiological, biochemical, and molecular responses of Raphanus sativus to KCl stress using an integrated approach that combines germination assays, mineral profiling, and gene expression analysis.

Radish seeds were exposed to increasing KCl concentrations (0–400 mM) with or without melatonin, TEA, or EDTA. Germination percentage, fresh and dry biomass, and early seedling vigor were …

A Fault Tolerant Honeybee Behaviour Load Balancing Algorithm, Charmaine Adegbite

Tennessee State University Alumni Theses and Dissertations

Cloud computing enables flexible, scalable access to virtualised infrastructure but remains challenged by maintaining performance in fault-prone environments. Faults such as virtual machine failures can degrade task allocation and system reliability. However, traditional load balancing algorithms and bio-inspired strategies, including the Honeybee Behaviour Load Balancing algorithm, assume fault-free conditions. This thesis introduces a Fault-Tolerant Honeybee Behaviour Load Balancing algorithm that enhances the original Honeybee Behaviour Load Balancing algorithm by integrating fault detection. The proposed algorithm monitors the health of VMs and dynamically reallocates workloads when faults are detected which improves stability and reliability. The proposed fault tolerant algorithm was implemented …

Book Of Abstracts, Seton Hall University

2025 Augustine Undergraduate Research Symposium

No abstract provided.

Bayesian Alignment Prior To Connectionist Temporal Classification Loss, Lawry Sorenson

Theses and Dissertations

We propose revisions of Connectionist Temporal Classification (CTC) loss and forced alignment to support longer input sequences. CTC loss is normally used for training in speech and handwriting recognition tasks when the labels are not fully aligned with the data, while forced alignment is a downstream task that finds the optimal path for segmentation purposes. The current implementations consider all possible alignments between the input and label, which grows exponentially with the size of the input. We show that in cases when silence is removed and speaking rate is consistent, the true alignment is a mostly straight line across time …

Implementing Dataops: A Scalable Framework For Modern Data Warehousing, Dmytro Valiaiev

Theses and Dissertations

DataOps has been coined as a novel term that emerged as a synthesis of data management practices with software engineering concepts, such as DevOps and Agile, with the goal of improving data quality and governance in enterprises. The proliferation of scratch table use and transformation tools, such as dbt, has led to an exponential increase in the number of data models, which complicates standardization efforts and increases maintenance overhead. Although the market is saturated with various flavors of text-to-SQL engines that promote increased productivity and self-service use in organizations, there are limited tools available to optimize individual queries, enforce consistency, …

Towards Fair Sequential Resource Allocation: Algorithmic Designs, Interventions, And Evaluations, Ashwin Kumar

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis develops a comprehensive framework for fair sequential resource allocation in multi-agent systems where a centralized allocator coordinates actions under global feasibility constraints, while satisfying preferences of different agents. Ranging from ridesharing platforms and homelessness intervention programs to power grid management, such systems play a critical role in shaping access to essential resources. Yet, existing approaches to resource allocation often prioritize aggregate utility, leading to systematic inequities across individuals and groups, particularly in sequential settings where decisions unfold over time. To address this challenge, we introduce the Distributed Evaluation, Centralized Allocation (DECA) framework, which unifies a broad class of …

My First Conversation With Chatgpt (February 22, 2023): Origins Of A Generative Dialogue, David Smith

Publications and Research

This working paper presents the first recorded interaction between the author and the generative AI system ChatGPT, written on February 22, 2023 during the initial weeks of a faculty sabbatical in Boston. The document preserves a complete and unedited transcript of an exploratory conversation conducted without predetermined research aims, marking the author’s first encounter with a large-language-model conversational interface. Although the exchange includes creative experimentation—including musical and poetic prompts—the discussion remains informal and wide-ranging, and no theoretical framework is articulated at this stage. Rather, this transcript is published as primary-source material documenting the moment of discovery and experimentation that precedes …

Prism (Proxy Recognition And Inclusion Scoring Method), Destiny Raburnel, Crystal Tubbs, Md Abdullah Al Hafiz Khan

Symposium of Student Scholars

AI-driven automated hiring tools are reshaping how companies find talent, but they often reproduce the hidden biases embedded in their training data. Our project, PRISM (Proxy Recognition and Inclusion Scoring Method), investigates how subtle demographic signals, specifically first names associated with gender and race, influence AI resume screening even when candidates have identical qualifications. We built a controlled dataset of resumes that are identical in every way except for the applicant's first name, with each resume using a racially neutral surname to isolate how first names alone affect scoring. We tested these resumes against job postings in technology, healthcare, and …

Artificial Intelligence In Insurance Fraud Detection: Applications And Implications For Internal Audit, Maria Davis

Honors Projects

Artificial Intelligence (AI) is being used in accounting and the insurance industry to assist with auditing and fraud detection. The Big Four public accounting firms have invested heavily in AI implementation efforts. Across these firms, AI has been used to reallocate auditors’ time from mundane tasks to more complex tasks that require human judgement. Within the insurance industry, machine learning, deep learning, and natural language processing, among other AI tools, have proven helpful in fraud detection efforts. While the positive impacts of AI usage are clear, concerns surrounding the replacement of human jobs, a lack of transparency in auditing, heavy …

Water Circulation Beneath A Hovering Suas For Water Quality Monitoring Applications, Erin E. Hackett, Boone Fleenor, Jensine C. Coggin, Duvall Dickerson-Evans, Nikolaos Vitzilaios, Whitney E. Schuler, Paige K. Williams, Michael L. Myrick

Marine Science

Water quality has traditionally been measured via in situ sensors and satellites. The latter has limited applicability for smaller inland water bodies, while the former requires significant logistics, labor, and expense for routine sampling, and reactive/spurious sampling is often not feasible as a result (e.g., sampling pre-/post-storm). Consequently, small uncrewed aircraft system-based (sUAS-based) sampling has emerged as a potential solution to bridge these sampling gaps and challenges. But sampling from an sUAS is complicated by the need to pump water from depth, rather than suspending a sensor from the sUAS, due to concern over sampling sUAS-impacted waters. Here, we measure …

Predicting Skin Concern Severity From Genetic And Lifestyle Factors: A Comparative Multi-Output Machine Learning Framework, Yassine Benachour, Lina Maloukh, Sadok Bouamama, Barbara Geusens

All Works

Personalized dermatology increasingly leverages both genetic predispositions and lifestyle behaviors to model individual skin health outcomes. This study proposes a multi-output machine learning framework to predict the severity of six dermatological phenotypes—acne, redness, dryness, sensitivity, scarring, and pigmentation—using a multimodal dataset of 5,254 individuals. Input features include mutation profiles for six skin-related genes (FLG, MMP1, MMP3, AQP3, SOD2, GPX) and 22 lifestyle variables such as sun exposure, stress, and hydration. We train and evaluate LightGBM models under independent, multi-output, and chained configurations. Performance is assessed using Mean Absolute Error (MAE) and average Quadratic Weighted Kappa (QWK). The proposed ordinal-aware independent …

Nsf Convergence Accelerator Track (H): Automating Transportation Affordances For People Living With Disabilities Using A Machine Learning Approach, Brent Chamberlain

Funded Research Records

No abstract provided.

Smart Pireps: Leveraging Technology To Simplify Pilot Weather Reporting In General Aviation, Emma Hellwege

Honors Projects

This honors project examines how emerging aviation technologies can support or automate components of Pilot Weather Reports (PIREPs) to improve reporting accuracy, reduce pilot workload, and increase participation within the general aviation (GA) community. PIREPs provide essential real-time weather observations—such as turbulence, icing, and visibility—that supplement automated systems and enhance situational awareness for pilots, air traffic control, and meteorologists. However, reports are vastly underutilized due to workload constraints, inconsistent training, voice-only submission methods, and technological disparities across the GA fleet.

Through a structured analysis of federal aviation documentation, sensor capabilities, human factors research, and recent advancements in automation, this study …

Adaptive Image Acquisition Algorithms For Resource-Constrained Single-Photon Cameras, Yeganeh Jalalpour, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Emerging single-photon camera (SPC) technologies have unique challenges in data acquisition and processing. Unlike conventional sensors that produce a single 8- to 16-bit brightness value per pixel, SPCs record photon arrivals with many more samples per pixel, using high floating-point precision for each photon collected. This means that they must handle potentially millions of timestamps, especially at higher spatial resolutions and in the presence of ambient light, creating bottlenecks within the pixel circuitry. To address these challenges associated with SPCs, this paper proposes adaptive algorithms designed to efficiently distribute hardware resources among groups of pixels. By selectively subsampling the data …

A (Mini) Mathematics Research Experience In A Math Teachers’ Circle Session, Michelle Manes, Linda Venenciano, Seanyelle Yagi

Journal of Math Circles

We describe a single Math Teachers’ Circle session during which a group of teachers collectively engaged in a “mini mathematics research experience.” This provides a model for providing research experiences for mathematics teachers through content-based professional development programs. We conjecture that these experiences will have many of the same benefits as research experiences for teachers in lab sciences.

Environmental Risk Assessment Of Textile Waste From Bio-Engineered Fibers In The Fashion Industry, Aayush Pankaj Agarwal, Harshit Soral, Irmak Aktan, Karol Montserrat Gonzalez Saad, Maria Daniela Saa Espinosa, Sheetal Suhas Dhanuka, Yi Yang

Harrisburg University Dissertations and Theses

The global fashion industry generates over 92 million tons of textile waste annually, a figure projected to increase significantly by 2030. Bio-engineered fibers, including bacterial cellulose, mycelium-based leather, and recombinant protein textiles emerge as sustainable alternatives to conventional fibers. Despite their promise, recent evidence suggests that these fibers may pose environmental risks at the end-of-life stage, such as incomplete biodegradation in landfills, microfiber shedding, and chemical leaching from dyes and coatings. The purpose of this study is to examine how these risks are represented through scientific literature, corporate sustainability reports, and policy frameworks, and to identify strategies for integrating risk …

Toward Understanding Multi-Agent Decision Making In Complex Societies, Jonathan Skaggs

Theses and Dissertations

This dissertation investigates Multi Agent Decision Making (MADM) within Complex Societies (CS), systems of interdependent agents whose collective behaviors emerge from local interactions. Such emergent dynamics are nonlinear and difficult to predict, posing significant challenges towards understanding how individual decisions scale to societal outcomes. Existing approaches often fall short of capturing the combined attributes of CS, including asymmetry, decentralization, and adaptivity. To address this gap, we introduce new models and analyses of agent strategies that explain how cooperation and stability can arise in CS. Structured around three interrelated projects, this dissertation enhances our comprehension of MADM in CS. The research …

Facility Usage On The International Space Station, Justin St. P. Walsh, Rao Hamza Ali, Ryan Shihabi, Erik Linstead

Art Faculty Articles and Research

Science experiments on the International Space Station (ISS) and in future space habitats require “facilities,” as they are known to space agencies, as the core building blocks of the research capabilities they provide. Facilities are experimental apparatus that enable research, often (but not always) used for more than one experiment, such as centrifuges, furnaces, gloveboxes, freezers, and more. The US Orbital Segment of the ISS has been home to 191 such facilities, belonging to four of the five ISS international partner agencies as well as private companies, in its 25 years of continuous operation. Until now, there has been no …

Developing A Waste-To-Energy Assessment Framework Integrating Engineering And Policy Dimensions Using A Triple Bottom Line Approach, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The management of municipal solid waste (MSW) in swiftly urbanizing Philippine cities has emerged as a critical concern in both energy and governance. Dependence on landfills is approaching critical thresholds as disposal sites near saturation, transportation costs escalate, and host communities increasingly resist garbage transfers. In response, this study proposes a comprehensive Waste-to-Energy (WtE) assessment framework that integrates engineering evaluation with policy and stakeholder analysis to support sustainable decision- making.

Using Baguio City as a case study, the framework applies a Triple Bottom Line (TBL) approach to evaluate three waste management scenarios: (1) current landfill-dominated practices, (2) engineered landfill with …