Physical Sciences and Mathematics Commons^™

Intergenerational Classification Of Reddit Comments Based On Slang And Emoji Usage, James T. Dracup

West Chester University Master’s Theses

The rapid evolution of language, driven by technological advancements, has created notable cultural gaps between generations, particularly in how they communicate. This gap is most apparent in the growing use of slang and emojis among younger generations. This study aims to explore whether Reddit comments can be classified by generation based on the usage of slang and emojis, the frequency of their use across generations, and how such features (slang and emojis) might influence the meaning of traditional language. Using Reddit’s API, we collected comments from four generational subreddits and applied various machine learning models, Naïve Bayes, Neural Networks, and …

Fares On Fairness: Using A Total Error Framework To Examine The Role Of Measurement And Representation In Training Data On Model Fairness And Bias, Patrick Oliver Schenk, Christoph Kern, Trent D. Buskirk

Information Technology & Decision Sciences Faculty Publications

Data-driven decisions, often based on predictions from machine learning (ML) models are becoming ubiquitous. For these decisions to be just, the underlying ML models must be fair, i.e., work equally well for all parts of the population such as groups defined by gender or age. What are the logical next steps if, however, a trained model is accurate but not fair? How can we guide the whole data pipeline such that we avoid training unfair models based on inadequate data, recognizing possible sources of unfairness early on? How can the concepts of data-based sources of unfairness that exist in the …

Climate Change Effects On The 2022–2023 High Impact Series Of Atmospheric Rivers Along The United States West Coast, Hunter Martinez-Buehrer

Graduate Research Theses & Dissertations

Atmospheric rivers (ARs) are long, narrow bands of water vapor transport that are commonly associated with a low-level jet ahead of a cold front of an extratropical cyclone. When multiple ARs occur in succession of one another within a certain aggregation period, it is known as an AR family. ARs and AR families are important to the U.S. West Coast—and especially California’s—hydroclimate, providing both beneficial and hazardous precipitation to the region. Recent studies have suggested that not all ARs and, thus, AR families, respond similarly to a warming climate. Therefore, it is critical to better understand how climate change impacts …

Artificial Intelligence And Environmental Sustainability: Review And Research Directions, Troy Strader, Yu-Hsiang (John) Huang, Yu-Ju Tu

Journal of International Technology and Information Management

Environmental sustainability is one of the most important and complex issues currently facing our global society. One solution to some aspects of this problem could come from artificially intelligent systems and data analytics methods. The objective for this study is to identify the range of recently published research that addresses issues involving the convergence of artificial intelligence (AI) and environmental sustainability. A systematic literature review produced a sample of 62 journal articles from 2018-2024 that were each categorized into one of six research themes that included studies of AI and the ways in which it impacted natural resources, energy and …

Determining The Transient Electric Field And The Effect Of Pulse Repetition Frequency On The Field In A Repetitive 10-Ns Pulsed Discharge In A Quiescent Ch₄-Air Mixture, Chunqi Jiang

Bioelectrics Publications

The goal of this research is to understand the underlying physics enabled by nanosecond pulsed power in a discharge initiation and the following physicochemical processes that favor lean-fuel plasma ignition for combustion. The hypothesis of this project is that pulsed power waveforms such as the pulse repetition frequency (PRF), voltage amplitude, and dielectric surface alter the reduced electric field during the initiation of the discharge, resulting in different plasma properties, which will vary the physicochemical processes for efficient and selective radical productions. This is especially important for lean-burn combustion and reducing emission.

Ai And Tribal Court Practice, Matthew L.M. Fletcher

Articles

American Indian tribal court practice resides at the intersection of two difficult legal problems. First, because tribal justice systems are usually very young and dynamic, awareness and analysis of tribal law is underdeveloped. Second, because tribal nations are not governed by state or federal law, tribal law is culturally unique. Tribal court practitioners often find that even routine legal matters will involve questions of first impression in the jurisdiction. All of this is to say tribal court jurisprudence is intensely jurisgenerative.

Because tribal law is often unsettled or indeterminate, the costs of discovering and applying this law are occasionally high. …

Clinicians In The Loop Of Medical Ai, W. Nicholson Price Ii

Articles

As medical AI begins to mature as a health-care tool, the task of governance grows increasingly important. Ensuring that medical AI works, works where it’s used, and works for the patient in the moment is a challenging, multifaceted task. Some of this governance can be centralized—in review by FDA or by national accreditation labs, for instance. Some must be local, performed by the hospital or health system about to use the product in their own, unique environment. But a large amount of governance is left to the individual provider in the room, the human in the loop who presumably knows …

Tedvil: Leveraging Transformer-Based Embeddings For Vulnerability Detection In Lifted Code, Gary Mccully, John Hastings, Shengjie Xu

Research & Publications

Ransomware and other malware inflict devastating financial and operational damage on organizations worldwide by exploiting deeply embedded, hard-to-detect vulnerabilities in their systems. Detecting these vulnerabilities in compiled code before malicious actors exploit them remains a critical challenge in cybersecurity. This research introduces TEDVIL (Transformer-based Embeddings for Discovering Vulnerabilities in Lifted Code), a novel framework which uses transformer-based embeddings to train neural networks to detect vulnerabilities in lifted code. The framework was implemented using bidirectional (BERT and RoBERTa) and unidirectional (GPT-1 and GPT-2) transformer-based models to generate embeddings for training Long Short-Term Memory (LSTM) neural networks to detect stack-based buffer overflows …

Solar Flare Forecasting Multiple Ml And Curation Technique Study Hour-By-Hour Sharp Parameter Data Archive, Timothy S. Newman

Open Data

Hour-by-hour AR parameter data as a series of .csv files in a zip archive. Contains the "filtered" data described in the "Solar Flare Forecasting using Machine Learning (ML) and SDO/HMI Data: Multiple ML Model and Data Curation Technique Comparison Study" paper of Newman, Hall, Farris, Singh, Pogorelov, Benson, Raza, and Trital paper, 2025 submission date, for ApJS. Each file in the zip has data for one class of flares at a timepoint a certain number of hours in advance of flare onset. The first letter of such file names indicates flare class and the number before "hrs" in the title …

The Sustainability Of The Outdoor Recreation Industry: Studied Through Mountaineering In Teton County, Wy, Samantha Olstein

Student Research and Publications

No abstract provided.

Verification Of Real-Time Smoke Simulations: A Case Study On Early Summer North American Wildfire Events, Daniel Bonilla

Pitzer Senior Theses

As wildfire intensity and frequency escalate in times of unprecedented climate change and severe droughts, it is important to enhance forecasting models that accurately and efficiently predict wildfire smoke movement. NOAA’s experimental Rapid-Refresh Forecasting System with Smoke and Dust (RRFS-SD) aims to improve upon the High-Resolution Rapid Refresh- Smoke (HRRR-Smoke), by extending the domain to include all of North America and incorporating new developments in physics and wildfire parameterizations. Our work explores the process of adding satellite Aerosol Optical Depth (AOD) data, through AERONET, as an additional method of verification of the RRFS-SD experimental model. Using a case study on …

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

Addressing The Computer Science Teacher Shortage: A Case Study Of Wisconsin Public High Schools, Sujeeth Goud Ramagoni, Dennis Brylow

Computer Science Faculty Research and Publications

Technology is evolving rapidly worldwide, making computational knowledge integral across virtually every field. Consequently, broadening access and promoting equity in computer science (CS) education at the high school level is crucial. Certified CS teachers are critical in creating opportunities to provide equitable CS access to high school students. In recent years, Code.org reports have highlighted a significant increase in student access to CS content across the U.S., particularly in high schools. Therefore, this paper provides a high-level overview of Wisconsin (WI) public high school CS education, examining CS teacher certification and course enrollment data from 2017 through 2023 academic years. …

Causal Discovery On The Effect Of Antipsychotic Drugs On Delirium Patients In The Icu Using Large Observational Ehr Dataset, Riddhiman Adib, Md. Osman Gani, Sheikh Iqbal Ahamed, Mohammad Adibuzzaman

Computer Science Faculty Research and Publications

Delirium occurs in about 80% of cases in the Intensive Care Unit (ICU) and is associated with an extended hospital stay, increased mortality, and other complications. Delirium lacks biomarker-based diagnosis and is frequently treated with antipsychotic drugs (APD), despite numerous studies debating its efficacy. Since randomized controlled trials (RCT) are expensive and time-consuming, we approach the research question of estimating the efficacy and safety outcomes of APD in treating delirium through retrospective cohort analysis. We employed the Causal inference framework to explore the underlying causal model for Delirium patient cohort. We focus on building a structural causal model for delirium …

Embedding With Large Language Models For Classification Of Hipaa Safeguard Compliance Rules, Md Abdur Rahman, Md Abdul Barek, Abm Kamrul Islam Riad, Md Mostafizur Rahman, Bajlur Rashid, Md Raihan Mia, Hossain Shahriar, Guillermo Francia, Fan Wu, Alfredo Cuzzocrea, Sheikh Iqbal Ahamed

Computer Science Faculty Research and Publications

Although software developers of mHealth apps are responsible for protecting patient data and adhering to strict privacy and security requirements, many of them lack awareness of HIPAA regulations and struggle to distinguish between HIPAA rules categories. Therefore, providing guidance of HIPAA rules patterns classification is essential for developing secured applications for Google Play Store. In this work, we identified the limitations of traditional Word2Vec embeddings in processing code patterns. To address this, we adopt multilingual BERT (Bidirectional Encoder Representations from Transformers) which offers contextualized embeddings to the attributes of dataset to overcome the issues. Therefore, we applied this BERT to …

Fine-Tuned Large Language Models (Llms): Improved Prompt Injection Attacks Detection, Md Abdur Rahman, Hossain Shahriar, Guillermo Francia, Fan Wu, Alfredo Cuzzocrea, Sheikh Iqbal Ahamed

Computer Science Faculty Research and Publications

Large language models (LLMs) are becoming a popular tool as they have significantly advanced in their capability to tackle a wide range of language-based tasks. However, LLMs applications are highly vulnerable to prompt injection attacks, which poses a critical problem. These attacks target LLMs applications through using carefully designed input prompts to divert the model from adhering to original instruction, thereby it could execute unintended actions. These manipulations pose serious security threats which potentially results in data leaks, biased outputs, or harmful responses. This project explores the security vulnerabilities in relation to prompt injection attacks. To detect whether a prompt …

Secure Ios Mhealth Apps Development: An Ide-Embedded Framework For Hipaa-Aware Coding, Bajlur Rashid, Md Abdul Barek, Mostafizur Rahman, Sharmin Yeasmin, Hossain Shahriar, Sheikh Iqbal Ahamed

Computer Science Faculty Research and Publications

With the rapid growth of technology, accessing digital health records has become increasingly easier. Especially mobile health technology like mHealth apps help users to manage their health information, as well as store, share and access medical records and treatment information. Along with this huge advancement, mHealth apps are increasingly at risk of exposing protected health information (PHI) when security measures are not adequately implemented. The Health Insurance Portability and Accountability Act (HIPAA) ensures the secure handling of PHI, and mHealth applications are required to comply with its standards. But it is unfortunate to note that many mobile and mHealth app …

Voice-Activated Self-Monitoring Application (Vois): User Acceptance And Satisfaction In The Field, Hyunkyoung Oh, Li Yang, Tala Abu Zahra, Shiyu Tian, Min Sook Park, Jake Luo, Sheikh Iqbal Ahamed, Evelyn Chan, Jeffrey Whittle

Computer Science Faculty Research and Publications

This paper illustrates the processes and results of user acceptance and satisfaction tests for the voice-activated self-monitoring (VoiS) application conducted in the field. VoiS was designed and developed for individuals with diabetes (DM) and hypertension (HTN) to support their routine and convenient self-management using a smart speaker platform. VoiS is also accessible on users’ mobile devices to visualize user-generated data. A total of nine adults with DM and HTN participated and were asked to use the VoiS system at home for a week to identify its acceptability in real-world conditions. Participants completed phone interviews to report operational errors and a …

Vulnerability To Stability: Scalable Large Language Model In Queue-Based Web Service, Md Abdul Barek, Bajlur Rashid, Mostafizur Rahman, A.B.M. Kamrul Islamc Riad, Guillermo Francia, Hossain Shahriar, Sheikh Iqbal Ahamed

Computer Science Faculty Research and Publications

Large Language Models (LLMs) have demonstrated exceptional capabilities in the field of Artificial Intelligence (AI) and are now widely used in various applications globally. However, one of their major challenges is handling high-concurrency workloads, especially under extreme conditions. When too many requests are sent simultaneously, LLMs often become unresponsive which leads to performance degradation and reduced reliability in real-world applications. To address this issue, this paper proposes a queue-based system that separates request handling from direct execution. By implementing a distributed queue, requests are processed in a structured and controlled manner, preventing system overload and ensuring stable performance. This approach …

The Future Of Shipping At The Biodiversity-Climate Nexus : Round Table Report, Mary S. Wisz, Fabio Berzaghi, Mikaela Gomez, Maud C. Quinzin, Renis Auma Ojwala, Emily Nuckolls

Reports

This report presents the outcomes of a cross-disciplinary Round Table hosted by the World Maritime University (WMU) from May 13-15, 2024, in Malmö, Sweden. The event brought together 51 experts from academia, industry, NGOs, and international organizations, including the IMO, to explore shipping’s role at the biodiversity-climate nexus. The Round Table had a particular focus on the impacts of shipping that are currently unregulated or under-regulated, and opportunities to address biodiversity loss and pollution as the sector decarbonizes. The report highlights the need to apply comprehensive, ecosystem-based approaches to effectively manage shipping's impacts, including cumulative impacts, on the environment, people, …

Fault Tree Analysis For Robust Design, Jonathan Degroff, Gene Jean-Win Hou

Mechanical & Aerospace Engineering Faculty Publications

The objective of this research is to incorporate system failure into a robust design formation and solution process. The system failure referred to here will be built using fault tree analysis (FTA), which will take all lower-level failure events into consideration. Two examples are investigated here. One will directly treat the probabilities of the basis events as design variables, The other will be formulated in five different models: deterministic design optimization, the reliability index-based, the “and” gate-based, the “or” gate-based and the “inhibit” gate-based robust design. Their corresponding optimization solutions will be compared with each other. The post-optimality analysis of …

Polarized Positrons At Ce⁺Baf, A. Ushakov, J. Benesch, M. Bruker, L. Cardman, J. Conway, S. Covrig Dusa, P. Degtiarenko, Y. Enomoto, S. Gessner, P. Ghoshal, S. Gopinath, J. Grames, C. Gulliford, S. Habet, G. Hays, C. Hernández-García, A. Hofler, R. Kazimi, M. Kostin, V. O. Kostroun, F. Lin, V. Lizárraga-Rubio, K. Mahler, Y. Morikawa, S. Nagaitsev, S. Ogur, G. Palacios-Serrano, N. Raut, B. Rimmer, Y. Roblin, A. Seryi, K. Smolenski, M. Stutzman, R. Suleiman, A. Sy, N. Taylor, D. Turner, A. Ushakov, C. Valerio-Lizarraga, E. Voutier, S. Wang, Y. Zhang

Mechanical & Aerospace Engineering Faculty Publications

A baseline concept for a continuous wave (CW) polarized positron injector was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab [1]. This concept is based on positron beam generation by a high current polarized electron beam (1 mA, 120 MeV, >85% polarization) irradiating a rotating water-cooled tungsten target or liquid metal target. The update on the development of the Ce⁺BAF injector concept including the polarized electron source, the development of high power targets, simulations of positron capture, the design of the transport line from the positron injector to the CEBAF North Linac and the planned experiment …

Revealing Spatiotemporal Neural Activation Patterns In Electrocorticography Recordings Of Human Speech Production By Mutual Information, Julio Kovacs, Dean Krusienski, Minu Maninder, Willy Wriggers

Mechanical & Aerospace Engineering Faculty Publications

Background

Spatiotemporal mapping of neural activity during continuous speech production has been traditionally approached using correlation coefficient (CC) analysis between cortical signals and speech recordings. A prior study employed this approach using electrocorticography (ECoG) data from participants who underwent invasive intracranial monitoring for epilepsy. However, CC cannot detect nonlinear relationships and is dominated by the correspondence between periods of silence and of non-silence.

New Method

We introduce the mutual information (MI) measure, which can capture both linear and nonlinear dependencies. We validated CC and MI on the sub-second spatiotemporal brain activity recorded during continuous speech tasks. To refine the results, …

Mass-Adaptive Admittance Control For Robotic Manipulators, Hossein Gholampour, Jonathon E. Slightam, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

Handling objects with unknown or changing masses is a common challenge in robotics, often leading to errors or instability if the control system cannot adapt in realtime. In this paper, we present a novel approach that enables a six-degrees-of-freedom robotic manipulator to reliably follow waypoints while automatically estimating and compensating for unknown payload weight. Our method integrates an admittance control framework with a mass estimator, allowing the robot to dynamically update an excitation force to compensate for the payload mass. This strategy mitigates end-effector sagging and preserves stability when handling objects of unknown weights. We experimentally validated our approach in …

Optimal Manipulation Motion Action Planner Enabled By Physics Informed Neural Networks, Jonathon E. Slightam, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

Autonomous robotic manipulation in unstructured environments faces many challenges and is hindered by capabilities that bridge the gap between perception and acting on the world. Action plans that are centric to object motion rather than end-of-arm tooling behavior may aid this. This paper presents an autonomous action planner for a feedback linearizeable system comprised of three base motions that can be leveraged on their own or in combination to give custom motion plans. The optimization routine for the three different types of motion are presented, which are integrated into physics informed neural networks. A component of this is the autonomy …

Transient Transmembrane-Electrostatically Localized Protons And Transmembrane Potential In A Laser Flashed Bacteriorhodopsin Purple Membrane Open Flat Sheet - Summary, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

The transmembrane-electrostatically localized protons/cations charges (TELCs, also known as TELPs) model may serve as a unified framework to explain a wide range of bioenergetic phenomena. Transient transmembrane-electrostatically localized protons (TELPs) and transmembrane potential in a laser flash-energized bacteriorhodopsin (bR) purple membrane (PM) open flat sheet are now better analyzed. Under the Heberle et al. (1994) experimental conditions, the number of bR molecules is now calculated to be 8200 per PM open flat sheet with a diameter of 600 nm. With a single-turnover laser flash intensity of 3 mJ/cm² to photoexcite 10% of the bR molecules, the laser flash-induced peak TELCs …

Experimental Absorption Cross Sections For Zro, Léo Lavy, Peter F. Bernath, Manish Bhusal, Jacques Liévin

Chemistry & Biochemistry Faculty Publications

Absorption cross sections for ZrO are provided and can be used as a template to interpret spectra of S-type stars. The ZrO spectrum was measured in emission from a carbon furnace at 2700 K and calibrated using synthetic spectra of ⁹⁰Zr¹⁶O. A set of nearly isolated molecular lines has been used for the calibration. We also thoroughly review the literature on the spectroscopy of ZrO. Comparison of the experimental spectrum with currently available line lists revealed issues in ZrO spectral simulation. (a) Within band systems, the relative intensities are not always well reproduced. (b) We identify yet unreported band systems, …

From Walking To Parkour: A Structured Survey Of Rl For Dynamic Skills In Legged Robots, Christopher Allred, Chandler Justice, Rosario Scalise, Yan Gu, Jonathan Clark, Mario Harper, Jason Pusey

Computer Science Student Research

This survey reviews recent advances in applying reinforcement learning (RL) to enable dynamic and ballistic motions in legged robots, including running, jumping, stair climbing, and parkour. Focusing on high-agility behaviors that challenge traditional control frameworks, we categorize foundational locomotion tasks and highlight the RL methods, such as Proximal Policy Optimization, curriculum learning, and hybrid model-based strategies that have proven effective. We discuss the key challenges in transferring learned policies to real-world robots, managing uncertainty, and integrating perception and proprioception. Drawing from over 150 recent works, we provide a structured taxonomy of objectives, algorithms, and platforms, and identify trends in simulation …

Into Thick Air: Adapting Cultural Practices Into Solutions For Modern Wicked Problems, Syed Muhammad Erzum Naqvi

Theses and Dissertations

Into Thick Air argues that cultural practices can inspire solutions

to challenging modern problems. This project employs the Basant

festival as a case study to critically reimagine kite flying as a

collective practice with the potential to contribute to the reduction

of air pollution in Lahore, a city consistently ranked among those

with the poorest air quality globally. By building kites from fabric

treated with nanoparticle coatings, Into Thick Air transforms a

traditional community activity into an accessible, citizen-driven

method for removing pollutants from the air. The treated kites

empower Lahoris to take charge of their environment while

encouraging collective …

An Ecofeminist Approach To Climate Risks, Angela Hefti

Michigan Journal of International Law

Climate change poses significant risks to the human right to life. However, international adjudicators have either neglected to examine right to life claims in the context of climate risks or dismissed them as prospective and speculative. International human rights bodies have long applied the standard of imminence to determine whether a threat to the right to life exists and the extent to which it constitutes a violation. In climate change cases, this standard has hardened, requiring a tight temporal connection between climate risks and a violation of the right to life. This article argues that failing to recognize the impact …