Physical Sciences and Mathematics Commons^™

Unpacking Bias, Accountability, And Ethical Practices In Ai, Manya Chandra, Micol Hebron

Student Scholar Symposium Abstracts and Posters

This study is based on understanding how text-to-image generative AI platforms perpetuate biases such as racism and sexism and decoding how this bias is programmed within large language models and datasets. In this study, the results of generative AI are analyzed through the lens of affect and affect theory, as they are applied to investigate the machine learning and computer theory behind generative AI algorithms. The purpose of the study is to explain why generative AI is biased and whether this bias is generated due to current trends or to deficits and biases within the database that it draws information …

Vieta’S Formula, The Fabius Function And The Partition Function, Ahmed Sebbar

Mathematics, Physics, and Computer Science Faculty Articles and Research

We use an idea of Pólya and Szegö to give a common basis to Vieta’s formula, Fabius function and the partition function. Moreover our construction leads also to a function considered by Hallström, Bowen and Macintyre, which has, as a particular value, the Kepler-Bouwkamp constant, and to a function considered by Zondadari, that vanishes only at prime numbers.

Hydrogen And Carbon Dioxide Kinetic Adsorption And Diffusion Behavior Into Organic-Rich Shale: Implications Of Mineralogy And Organic Content, Amer Alanazi, Hussein Abid, Saleh A. Bawazeer, Norah Aljeban, Israa S. Abu-Mahfouz, Alireza Keshavarz, Stefan Iglauer, Hussein Hoteit

Research outputs 2022 to 2026

Geological storage of hydrogen (GSH) is a pivotal technology for advancing an industrial-scale hydrogen economy. Shale formations, known for their impermeable sealing and abundance, offer promising potential for secure GSH applications. However, the complex mineralogy and organic content of shale necessitate a detailed investigation. This study examines the potential of organic-rich shale samples from Jordanian oil source rocks for hydrogen (H2) storage and carbon dioxide (CO2) sequestration. Adsorption kinetics were measured at two different temperatures (303 and 333 K) and pressures (15 and 45 bar) using a volumetric experimental approach. Common mathematical models were applied to evaluate the adsorption data …

Electricity Generation From Air Movements For Microelectronics Applications, Rahul Nair, Kezang Choden

Australia-Bhutan Research Conference

This paper is about generating limited amount of electricity from natural air movements and air movements in a controlled environment . This is specifically applicable and useful in microelectronics application and as a pre charging . Air is composed of 71% Nitrogen and 21 % oxygen and rest of the gases comprising 8%. We understand that air also takes up from free radicals in the atmosphere due to various chemical reactions. The free radicals and ions have a random motion and movement in the air column. The controlled movement of air with charged particles which is essentially the free radicals …

Visionary Indigenous Training And Leadership For Natural Resources (Vital4nr), Peter D. Howe

Funded Research Records

No abstract provided.

Lstm-Transformer Based Robust Hybrid Deep Learning Model For Financial Time Series Forecasting, Md R. Kabir

Theses and Dissertations

The inherent challenges of financial time series forecasting demand advanced modeling techniques for reliable predictions. Financial data, belonging to the category of multimedia data, contains an extensive quantity of information that is widely used for data analysis and decision-making tasks. Effective financial time series forecasting is crucial for financial risk management and the formulation of investment decisions. Accurate prediction of stock prices is a subject of study in the domains of investing and national policy. This problem appears to be challenging due to the presence of multi-noise, nonlinearity, volatility, and chaotic natures in stocks. This paper proposes a novel financial …

Nonlinear Thomson Scattering In An Intense Tightly Focused Ultrashort Laser Pulse, Yance Sun

Theses and Dissertations

We investigate nonlinear Thomson scattering generated by intense laser pulses focused in noble gases. Electrons are ionized from low-density helium or argon early during the laser pulse and scatter light out the side of the focus. We measure fundamental, second, and third harmonic light focus over nearly the entire emission sphere. We investigate the influence of electron bunching, when individual atoms ionize multiple electrons sequentially as the laser field increases early during the laser pulse. Simulations suggest that correlation between electron positions for the ten electrons ionized from argon should distort the spatial pattern of nonlinear Thomson scattering relative to …

Urban Sustainable Neighborhoods: Revitalization Of Sheppard Square Hope Vi In Louisville, Ky, Ramona Stone

Sustainability Research & Practice Seminar Presentations

Professor Ramona Stone, PhD, MPH, from West Chester University presents "Public Health Sciences Urban Sustainable Neighborhoods: HOPE VI Revitalization of Sheppard Square in Louisville, KY".

Applying Positive Unlabeled Learning Techniques And Using The Kullback-Leibler Divergence To Improve Geothermal Surveying Assessments, Martín Thomas Rodriguez

Dissertations and Theses

As we face the current climate crisis, the discovery of geothermal energy resources has the potential to greatly reduce our dependence on fossil fuels worldwide. However, the development of any new energy infrastructure is expensive and depends on the willingness of energy agencies and developers to make initial investments based on calculated risk measures. One such measure, called geothermal favorability, is the likelihood that a site has conditions favorable for geothermal systems containing recoverable energy potential. Its prediction from existing geophysical datasets proves to be a nontrivial task. The prediction of geothermal favorability can be framed as a binary classification …

Reconstructing Cosmic Filaments Around Dwarf Galaxies With The Rubin Observatory, Sarah E. Draves, Charlotte Welker, Charlotte Olsen

Publications and Research

The cosmic web is the largest structure in the universe, consisting of streams of gas and dust that connect galaxies made of stars, dark matter, and more gas and dust. Denser areas of the cosmic web tend to have more massive and redder galaxies, which implies a strong connection between cosmic structure and galaxy evolution. The degree to which galaxies are influenced by the cosmic web outside of relatively dense areas, particularly in the case of small filaments near galaxies, is still an area of active study. Low mass galaxies, known as dwarf galaxies, are particularly sensitive to the environment …

Statistical Analysis For Pre- And Post- Assessments Of Sdq And Idela Scores, Diego Murillo, Franceli L. Cibrian

Student Scholar Symposium Abstracts and Posters

This research aimed to assess the potential of Mazi Umntanakho ("Know Your Child") in tracking developmental milestones in young children. Mazi is a WhatsApp-based conversational agent that assists South African home visitors in evaluating and monitoring children's socio-emotional skills using the Strengths and Difficulties Questionnaire (SDQ) and the International Development and Early Learning Assessment (IDELA). A field study was conducted in low-income South African communities, where 95 home visitors assessed 1,208 children. This detailed analysis of the data was collected during that deployment, focusing on investigating whether assessment scores improved over time and whether the length of time between assessments …

Developing A Nearly Automated Open-Source Pipeline For Conducting Computational Fluid Dynamics Simulations In Anterior Brain Vasculature: A Feasibility Study, Mostafa Rezaeitaleshmahalleh, Nan Mu, Zonghan Lyu, Joseph Gemmete, Aditya Pandey, Jingfeng Jiang

Michigan Tech Publications

Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical management of patients with an IA. However, the current workflow of CFD simulations is time-consuming, complex, and labor-intensive and, thus, does not fit the clinical environment. To address these challenges, we have developed a semi-automated pipeline integrating multiple open-source software packages to streamline the CFD simulation process. Specifically, the study utilized medical angiography data from 18 patients. An in-house open-source DL image segmentation model …

The Computational Eye. Deconstructing Style In Digital Art History, Paul Guhennec, Ellen Charlesworth

Artl@s Bulletin

With the aim of grounding digital methods in the art historic tradition, this paper uses the discussions around style as a springboard to ask how digital art history can extend beyond providing quantitative confirmation of known trends to enrich our current understanding of visual cultures. Drawing from the examples throughout this issue, we explore how an analysis of computational ways of seeing—or the ‘computational eye’—can expose the underlying preoccupations and priorities of our own research.

Afin de mieux ancrer les méthodes numériques dans la tradition de l’histoire de l’art, cet article se sert des discussions récentes autour du concept de …

Visualization Of Paleocurrents On A Web Application Using Gplates, Anjan Sapkota

MS in Computer Science Theses

Paleocurrents are flow directions derived from features of sedimentary rocks that reveal the direction of the current of wind or water that deposited the sediment. In 2015, Brand et al. created a global database of paleocurrents, which contains over 1,000,000 measurements worldwide: North America, South America, Australia, Great Britain, parts of Western Europe, China, Africa are fairly well represented; Antarctica, Eastern Europe, and Asia are modestly represented and Russia is poorly represented. The contribution of this thesis is a web application that uses the GPlates’ Application Programming Interface (API) to visualize global paleocurrents through time in an interactive way based …

A Fourth Planet In The Kepler-51 System Revealed By Transit Timing Variations, Kento Masuda, Jessica E. Libby-Roberts, John H. Livingston, Kevin B. Stevenson, Peter Gao, Shreyas Vissapragada, Guangwei Fu, Te Han, Michael Greklek-Mckeon, Suvrath Mahadevan, Eric Agol, Aaron Bello-Arufe, Zachory Berta-Thompson, Caleb I. Cañas, Yayaati Chachan, Leslie Hebb, Renyu Hu, Yui Kawashima, Heather A. Knutson, Caroline V. Morley, Catriona A. Murray

Pacific Faculty Work

Kepler-51 is a ≲1 Gyr old Sun-like star hosting three transiting planets with radii ≈6-9 R ⊕ and orbital periods ≈45-130 days. Transit timing variations (TTVs) measured with past Kepler and Hubble Space Telescope (HST) observations have been successfully modeled by considering gravitational interactions between the three transiting planets, yielding low masses and low mean densities (≲0.1 g cm⁻³) for all three planets. However, the transit time of the outermost transiting planet Kepler-51d recently measured by the James Webb Space Telescope 10 yr after the Kepler observations is significantly discrepant from the prediction made by the three-planet TTV …

Artificial Creativity: How Artificial Intelligence Will Impact Creativity Via Post-Production, Nicole Dwyer

Honors Thesis

My thesis lives in the world of Post-Production, and it contains both a creative and written component. I was the editor for four Undergraduate thesis projects. Seeking to gain experience in editing various genres, I worked in drama, sports, period piece, coming of age, and adventure. My biggest takeaways from these projects are the importance of organization, communication, time management, and editing with a sense of imagination. I became a more confident, resilient, and prepared editor through these experiences.

Along with the hands-on filmmaking element of my thesis, I also conducted research on how artificial intelligence will impact conceptions of …

Investigating The Efficacy Of Prompt Engineering Techniques For Research Survey Paper Generation Using Large Language Models, Innocent Obed Awidi

Theses and Dissertations

The recent advancements in large language models (LLMs), such as ChatGPT, offer promising potential for automating academic writing tasks. This study investigates the efficacy of prompt engineering techniques in guiding LLMs to generate high-quality research survey papers, specifically exploring their application in the fields of artificial intelligence (AI) in drug development and large language model customization for classification. Using a mixed-methods approach, this research assessed the impact of prompt engineering on the coherence, relevance, and overall quality of generated content through quantitative and qualitative analyses. Techniques including prompt refinement, contextual prompting, and iterative prompting were systematically applied to enhance the …

Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor

Faculty Publications

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …

Graph Neural Networks Powered Scientific Paper Recommendation, Junhao Shen

Computer Science and Engineering Theses and Dissertations

Scientific paper recommendation systems aim to help researchers discover relevant papers amidst the vast and ever-growing body of literature. With the exponential yearly increase in scientific publications, the demand for effective paper recommendation solutions has become both critical and increasingly challenging. In recent years, deep learning techniques have revolutionized recommender systems, and scientific paper recommendations have naturally integrated these advancements. In this dissertation, we address these challenges through three progressive contributions.

First, we enhance traditional content-based methods using Graph Neural Networks (GNNs) by introducing a Graph Convolutional Network-strengthened Topic Modeling (GCN-TM) approach. This method improves upon conventional topic modeling techniques …

Butte Priority Soils Operable Unit (Bpsou) Final Bpsou Insufficiently Reclaimed Sites Belle Of Butte (Bres No. 8 & Ur-39) Remedial Action Work Plan (Rawp) Request For Change Ir- 2024-Ra-01, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Intraspecific Variability Of Rice Root Knot Nematodes Across Diverse Agroecosystems For Sustainable Management, Sandip Mondal, Arnab Purohit, Anjan Hazra, Sampa Das, Manohar Chakrabarti, Matiyar Rahaman Khan, Horacio Lopez-Nicora, Dipankar Chakraborti, Abhishek Mukherjee

School of Integrative Biological & Chemical Sciences Faculty Publications

In the rice agroecosystems of Southeast Asia, rice root knot nematode (Meloidogyne graminicola) significantly impairs yield, representing a major species within the ‘graminis-group’ known for its morphological similarities with other root knot nematodes (RKNs). This study delves into the variations in reproductive potential, morphology, morphometrics, and genetic diversity among thirty RKN populations in rice across three distinct agroecological zones in Jharkhand, India. Despite notable differences in reproductive potential among the populations, morphological and morphometric correlations to reproductive potential were inconclusive. However, male and juvenile morphometrics were crucial for identifying intraspecific variability. Genetic analysis utilizing five molecular markers (ITS, …

Source Anisotropies And Pulsar Timing Arrays, Bruce Allen, Deepali Agarwal, Joseph D. Romano, Serena Valtolina

Physics & Astronomy Faculty Publications

Pulsar timing arrays (PTAs) hunt for gravitational waves (GWs) by searching for the correlations that GWs induce in the time-of-arrival residuals from different pulsars. If the GW sources are of astrophysical origin, then they are located at discrete points on the sky. However, PTA data are often modeled, and subsequently analyzed, via a “standard Gaussian ensemble.” That ensemble is obtained in the limit of an infinite density of vanishingly weak, Poisson-distributed sources. In this paper, we move away from that ensemble, to study the effects of two types of “source anisotropy.” The first (a), which is often called “shot noise,” …

Rings Of Power: Controlling Sod Mimic Activity By The Addition Of Pyridine Rings Within The Pyridinophane Scaffold, Katherine J. Smith, Timothy M. Schwartz, David M. Freire, Cameron Bowers, Sarah K. Dunn, Jackson F. Bonnell, Magy A. Mekhail, Giridhar Akkaraju, Kayla N. Green

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Superoxide dismutase enzymes are a major defense against superoxide, which is a potent reactive oxygen species. Misregulation of reactive oxygen species and subsequent neuronal damage are etiological hallmarks of neurodegenerative disease. Macrocyclic small molecules have offered inroads toward functional SOD1 mimics. Herein, we report a series of five tetra-aza macrocyclic ^RPy₂N₂ ligands, varied by 4-position substitution of the pyridine ring with both electron-donating (R = OMe) and withdrawing groups (R = Cl, I, and CF₃) to offer the first comparison to well-studied ^RPyN₃ congeners and other mimics in the literature. New ligands …

Mathematics In Amusement Parks, Kacey Laumann

Honors Projects

This project focuses specifically on the Walt Disney World Park, Magic Kingdom. I started by collecting data through the MyDisneyExperience app. By recording the data, I was then able to create polynomial functions to the fifth the degree. Each attraction received a function which allowed me to predict the wait times for that attraction. Then, by graphing the functions and analyzing the graph using calculus the “best time” and “worst time” to go to the attraction were found. After the analysis the information is used to build a unique schedule for a guest. Then the guest receives this schedule after …

Does A Name Make A Difference? Teaching Random Selection In The Classroom, Venessa Singhroy, Rommel Robertson, Kostas Stroumbakis

Numeracy

In Statistics education, it is crucial to emphasize the foundational significance of random selection, which underpins statistical methodologies and ensures unbiased representation of populations in samples. However, students often struggle to grasp the concept’s complexities, leading to challenges in applying random selection methods effectively. This paper examines the gap between students’ theoretical understanding of randomness and their practical application of this concept. Using an Explanatory Sequential Design, this study presents an instructional activity aimed at teaching the concept of randomness in the selection process and proposes modifications to enhance student comprehension. The activity, implemented in undergraduate Statistics and Psychology courses, …

D101n: A Unique And Ill-Understood Familial Als-Related Sod1 Mutant, Analisa Lott

Honors Program Theses and Research Projects

Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease, with 90% of documented cases considered sporadic and about 10% showing a hereditary link; such cases are deemed as familial ALS (fALS). Superoxide dismutase (SOD), a copper-zinc binding enzyme that protects cells from damaging free radicals, has been linked to fALS with certain toxic gain of function mutations, such as the D101N mutant. The human SOD1 D101N mutant has been shown to be associated with rapidly progressing neurodegeneration yet is less prone to aggregation than similar mutants, but its deviation from wild-type (WT) SOD1 remains misunderstood.

Objective: Although the D101N …

Website Portfolio, Thomas Roch

Honors Program Theses and Projects

No abstract provided.

Applications Of Neural Networks In Parkinson’S Disease Diagnosis, Saladin Minhaaj

Theses

Parkinson's disease (PD) is a complex and debilitating neurodegenerative disorder that affects millions of people worldwide. Early and accurate diagnosis is crucial for effective treatment and management of PD. This thesis explores the application of neural networks in PD diagnosis, leveraging their ability to learn patterns from large datasets and make accurate predictions.

Thesis provides an overview of PD, including its symptoms, diagnosis, and current challenges in diagnosis. We then delve into the fundamentals of neural networks, including supervised learning, mathematical interpretations, and parametric models. This research focuses on the development of neural network models that can accurately diagnose PD …

A Latent Class Assessment Of Healthcare Access Factors And Disparities In Breast Cancer Care Timeliness, Matthew Dunn, Didong Li, Marc Emerson, Caroline Thompson, Hazel Nichols, Sarah Van Alsten, Mya Roberson, Stephanie Wheeler, Lisa Carey, Terry Hyslop, Jennifer Elston Lafata, Melissa Troester

Kimmel Cancer Center Faculty Papers

BACKGROUND: Delays in breast cancer diagnosis and treatment lead to worse survival and quality of life. Racial disparities in care timeliness have been reported, but few studies have examined access at multiple points along the care continuum (diagnosis, treatment initiation, treatment duration, and genomic testing).

METHODS AND FINDINGS: The Carolina Breast Cancer Study (CBCS) Phase 3 is a population-based, case-only cohort (n = 2,998, 50% black) of patients with invasive breast cancer diagnoses (2008 to 2013). We used latent class analysis (LCA) to group participants based on patterns of factors within 3 separate domains: socioeconomic status ("SES"), "care barriers," and …

Screensafefuture: A Parent-Empathetic And Pragmatic Mhealth Application For Toddlers' Brain Development Addressing Screen-Addiction Challenges, Nafisa Anjum, Md. Mehedi Hasan, Syeda Umme Salma, Liang Zhao, Maria Valero, Nazmus Sakib

Faculty Articles

The surging incidents of infants and toddlers screen addiction in the United States are becoming a pressing concern, given its compound impact on cognitive, mental, and physical growth. To address this era's critical child health and development problem, in this paper an innovative mHealth application—ScreenSafeFuture—is proposed. ScreenSafeFuture provides practical solutions that seamlessly fit into parents' busy lifestyles, acknowledging the effectiveness and convenience of smartphones as a healthcare tool. The solution includes essential features designed to enhance the experience between parents and their children under 3 years old encompassing an alternative activity advocator for a personalized parent-offspring scenario, screen time tracking …