Physical Sciences and Mathematics Commons^™

Enhancing And Securing Wireless Medical Technology For Diagnosis And Treatment Of Lower Urinary Tract Dysfunction, Farhath Zareen

USF Tampa Graduate Theses and Dissertations

Lower urinary tract dysfunction (LUTD) is a debilitating medical condition that affects millions of individuals worldwide. Urodynamics is the current gold standard for diagnosing LUTD but uses non-physiologically fast, retrograde cystometric filling to obtain a brief snapshot of bladder function. Current state-of-the-art research in bladder monitoring includes ambulatory urodynamics using wireless implantable devices to evaluate bladder function during natural filling for long-term monitoring. However, there are various challenges and limitations to this multi-sensor approach. This research focuses on developing frameworks for automated event detection, data analysis, and optimization of long-term bladder recordingsto improve the diagnosis and treatment of LUTD. In …

Edge Covers Of Joined Cycle And Path Graphs, Rowan Kennedy

Mathematics Undergraduate Research

A graph is a mathematical structure consisting of vertices, representing objects, and edges that connect pairs of vertices, representing relationships between objects. When a specific graph structure can be extended in a consistent pattern we get a graph family, such as the families of path and cycle graphs. An edge cover of a graph is a subset of the graph's edges chosen so that each vertex is an endpoint of at least one edge in this subset. The edge cover counts of certain graph families, such as the path and cycle graphs, correspond to known sequences, the Fibonacci and Lucas …

Mentoring Experiences Of Undergraduate Students And Faculty Members In Science, Technology, Engineering, And Mathematics, Pamela Martínez Oquendo

School of Natural Resources: Dissertations, Theses, and Student Research

I present a comprehensive view of mentoring experiences of undergraduate students and faculty members in science, technology, engineering, and mathematics (STEM). In Chapter 1, I describe a brief outline of this dissertation. In Chapter 2, I present an interpretative phenomenological analysis of the lived experiences of former STEM undergraduate mentors of the Nebraska STEM For You (NE STEM 4U) afterschool mentoring program. In Chapter 3, I describe how the ramifications of faculty mentorship influence the science pipeline using a qualitative synthesis. In Chapter 4, I describe how the STEM faculty-student mentoring engagement involves a strong psychological support component using a …

The Effects Of Temperature And Flooding Duration On The Structure And Magnitude Of A Floodplain Prey Subsidy, Ryan J. Rezek, Jordan A. Massie, James A. Nelson, Rolando O. Santos, Natasha M. Viadero, W. Ryan James, Ross E. Boucek, Jennifer S. Rehage

Marine Science

Riverine floodplains serve as an important link between terrestrial and aquatic systems, as the rising and falling of water drive spatial food web subsidies that are critical to the functioning and stability of ecosystems. As these systems are increasingly impacted by hydrological alterations and climate change, it is important to understand how floodplain spatial food web subsidies may respond to changing environmental conditions.

Here, we examine the interannual variation in the structure of a sunfish (Lepomis spp.) prey subsidy from freshwater marshes into the mangrove-lined creeks of Rookery Branch in the Florida Coastal Everglades that occurs during seasonal dry downs. …

On The Variability Of In Situ Surface Layer Refractivity Measurements, Douglas M. Pastore, Ryan T. Yamaguchi, Qing Wang, Erin E. Hackett

Marine Science

Direct measurements of profiles of atmospheric properties near the ocean surface and within the marine atmospheric surface layer often contain a large degree of variability. The variability observed can be explained by numerous technical and natural reasons such as the temporal variability over the time span a profile is measured (unsteadiness in the mean), spatial variations (inhomogeneity), turbulent fluctuations, and measurement uncertainty. In this study, we explored the observed variability in vertical distributions of refractive index measured with a tethered-balloon-based marine atmospheric profiling system (MAPS). MAPS profiled the atmosphere from approximately 0.5 to 50 m, with instantaneous (order 1 s) …

Freestanding Graphene Heat Engine Analyzed Using Stochastic Thermodynamics, J. Durbin, J. M. Mangum, M. N. Gikunda, F. Harerimana, P. Kumar, L. L. Bonilla, P. M. Thibado

Physics Faculty Publications and Presentations

We present an Ito-Langevin model for freestanding graphene connected to an electrical circuit. The graphene is treated as a Brownian particle in a double-well potential and is adjacent to a fixed electrode to form a variable capacitor. The capacitor is connected in series with a battery and a load resistor. The capacitor and resistor are given separate thermal reservoirs. We have solved the coupled Ito-Langevin equations for a broad range of temperature differences between the two reservoirs. Using ensemble averages, we report the rate of change in energy, heat, and work using stochastic thermodynamics. When the resistor is held at …

The Large Deficit Of Hmxb Emission From Luminous Infrared Galaxies: The Case Of The Circumnuclear Starburst Ring In Ngc 7552, Lacey West, Kristen Garofali, Bret D. Lehmer, Andrea Prestwich, Rafael Eufrasio, Wasutep Luangtip, Timothy P. Roberts, Andreas Zezas

Physics Faculty Publications and Presentations

Luminous infrared galaxies (LIRGs), the most extreme star-forming galaxies in the nearby (D < 30 Mpc) universe, show a notable X-ray emission deficiency (up to a factor of ∼10) compared with predictions from scaling relations of galaxy-wide high-mass X-ray binary (HMXB) luminosity with star formation rate. In the nearby (≈20 Mpc) LIRG NGC 7552, the majority of the IR emission originates in a circumnuclear starburst ring, which has been resolved into several discrete knots of star formation. We present results from recent Chandra observations of NGC 7552, which reveal significant deficits in the 2–7 keV X-ray luminosities from two of the most powerful star-forming knots. We hypothesize that the expected luminous HMXB populations in these knots are either (1) obscured by very large column densities or (2) suppressed due to the knots having relatively high metallicity and/or very young ages (≲5 Myr). We distinguish between these possibilities using data from recent NuSTAR observations, whose sensitivity above 10 keV is capable of uncovering heavily obscured HMXB populations, since emission at these energies is more immune to absorption effects. We find no evidence of a heavily obscured HMXB population in the central region of NGC 7552, suggesting suppressed HMXB formation. We further show that metallicity-dependent scaling relations cannot fully account for the observed deficit from the most powerful star-forming knots or the central region as a whole. Thus, we suggest that recent bursts in local star formation activity likely drive the high L_IR within these regions on timescales ≲5 Myr, shorter than the timescale required for the formation of HMXBs.

An Ml Based Digital Forensics Software For Triage Analysis Through Face Recognition, Gaurav Gogia, Parag H. Rughani

Journal of Digital Forensics, Security and Law

Since the past few years, the complexity and heterogeneity of digital crimes has increased exponentially, which has made the digital evidence & digital forensics paramount for both criminal investigation and civil litigation cases. Some of the routine digital forensic analysis tasks are cumbersome and can increase the number of pending cases especially when there is a shortage of domain experts. While the work is not very complex, the sheer scale can be taxing. With the current scenarios and future predictions, crimes are only going to become more complex and the precedent of collecting and examining digital evidence is only going …

Characterization And Estimation Of Musculoskeletal Pain Using Machine Learning, Boluwatife Faremi

Master's Theses

Traditional scales utilized for recording pain are known to be highly subjective and biased due to inaccuracies in recollecting actual pain intensities. As a result, machine learning (ML) models that are trained using these scores as ground truth are reported to have low performance for objective pain classification because of the huge disparity between what was felt in moments of pain and the scores recorded afterward.

In the present study, two devices were designed for gathering real-time, continuous in-session subjective pain scores and the recording of the autonomic nervous system (ANS) altered endodermal (EDA) activity. 24 participants were recruited to …

Iowa Waste Reduction Center Newsletter, July 2023, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Registration Now Open for the IRA/ISOSWO Conference
--- 20 Years of STAR4D
--- Industry News

South Shore Of Long Island Reef Gis Data, Robert M. Cerrato, Matthew Sclafani

SoMAS Research Data

High-resolution backscatter and bathymetric maps created by multibeam sonar surveys were used to identify different seafloor bottom types within existing, potentially expanded, and newly proposed reef areas in New York waters. Existing sites included Smithtown in Long Island Sound (LIS), and Rockaway, Atlantic Beach, Hempstead, Yellowbar, Kismet, Fire Island, Twelve Mile along the South Shore. Potential expansions are proposed on the South Shore for McAllister, Moriches, and Shinnecock reefs in addition to a new site called Sixteen Fathom. In Long Island Sound, new sites are proposed for Huntington/Oyster Bay, Port Jefferson/Mount Sinai, and Mattituck. Grab samples were collected within these …

Advanced Prognostic Modeling For Breast Cancer Patients: Leveraging Data-Driven Approaches For Survival Analysis, Theophilus Gyedu Baidoo

Theses and Dissertations

Breast cancer is the second most prevalent form of cancer in women in the United States. Each year, about 264,000 cases of breast cancer are diagnosed in women and of this number, about 42,000 women lose their lives as reported by the Centers for Disease Control and Prevention. Early detection and effective treatment are crucial for improving survival rates and reducing mortality. This study aimed to explore the influential factors that may risk the survival of women with the disease and compare their predictive abilities using several error and performance metrics. The study uses a dataset from the National Cancer …

Current Vehicle Fleet Inventory And Future Implementation Of A Centralized Electric Fleet At Portland State University, Dane Kovaleski

Environmental Science and Management Professional Master's Project Reports

As the effects of climate change continue to impact the world, many institutions have developed climate action goals to reduce their effects on the environment. Portland State University (PSU) has committed to an 80% reduction of greenhouse gas emissions by 2030 and carbon neutrality by 2040. A part of this commitment must include looking at the contributions of transportation on campus to reduce carbon emissions. According to a greenhouse gas emissions report done by the Campus Planning and Sustainability Office in 2016, transportation contributed to 12% of total greenhouse gas emissions on campus.

This project aims to evaluate the management …

Dynamic Fallowing In The Middle Rio Grande: A Look At The Environmental Water Leasing Program, Jared Wood

Water Resources Professional Project Reports

The Environmental Water Leasing Program (EWLP) is a federally-funded collaborative effort of the Middle Rio Grande Conservancy District and the U.S. Bureau of Reclamation that has paid irrigators in the Middle Rio Grande to temporarily lease water rights and forgo their water use so that it may be used to provide environmental flows for the endangered Rio Grande Silvery Minnow. The program operates in a sometimes socially contentious context, in a region with an overallocated, legally constrained water system, to offer much needed water management flexibility. While dynamic fallowing payments for ecosystem services programs like the EWLP are common policy …

Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein

All Works

The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone’s life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale. There are limited reliable researches that study microdroplets spread and transmissions from human sneeze or cough in the airborne space. In this paper, we propose an intelligent technique to visualize, detect, measure the distance …

Applications Of Environmental Dna (Edna) To Detect Subterranean And Aquatic Invasive Species: A Critical Review On The Challenges And Limitations Of Edna Metabarcoding, Sakib Tahmid Rishan, Richard Kline, Md Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

The world is struggling to solve a devastating biodiversity loss that not only affects the extinction of treasured species and irreplaceable genetic variation, but also jeopardizes the food production, health, and safety of people. All initiatives aimed to conserve biodiversity rely heavily on the monitoring of both species and populations to get accurate spatial patterns and overall population assessments. Conventional monitoring techniques, such as visual surveys and counting individuals, are problematic due to challenges in identifying cryptic species or immature life stages. Environmental DNA (eDNA) is a relatively new technology that has the potential to be a faster, non-invasive, and …

Prompt To Be Consistent Is Better Than Self-Consistent? Few-Shot And Zero-Shot Fact Verification With Pre-Trained Language Models, Fengzhu Zeng, Wei Gao

Research Collection School Of Computing and Information Systems

Few-shot or zero-shot fact verification only relies on a few or no labeled training examples. In this paper, we propose a novel method called ProToCo, to Prompt pre-trained language models (PLMs) To be Consistent, for improving the factuality assessment capability of PLMs in the few-shot and zero-shot settings. Given a claim-evidence pair, ProToCo generates multiple variants of the claim with different relations and frames a simple consistency mechanism as constraints for making compatible predictions across these variants. We update PLMs by using parameter-efficient fine-tuning (PEFT), leading to more accurate predictions in few-shot and zero-shot fact verification tasks. Our experiments on …

A Data-Driven Approach For Scheduling Bus Services Subject To Demand Constraints, Brahmanage Janaka Chathuranga Thilakarathna, Thivya Kandappu, Baihua Zheng

Research Collection School Of Computing and Information Systems

Passenger satisfaction is extremely important for the success of a public transportation system. Many studies have shown that passenger satisfaction strongly depends on the time they have to wait at the bus stop (waiting time) to get on a bus. To be specific, user satisfaction drops faster as the waiting time increases. Therefore, service providers want to provide a bus to the waiting passengers within a threshold to keep them satisfied. It is a two-pronged problem: (a) to satisfy more passengers the transport planner may increase the frequency of the buses, and (b) in turn, the increased frequency may impact …

Maximum Activation 3d Cube Transition System For Virtual Emotion Surveillance, Taewoo Lee, Jalel Ben-Othman, Hyunbum Kim

All Works

The concept of barrier coverage has been utilized for with various applications of surveillance, object tracking in smart cities. In barrier coverage, it is desirable to have large number of active barriers to maximize lifetime of UAV-assisted application. Because existing studies primarily focused on the formation of barriers in two-dimensional area with limited applicability, it is indispensable to extend the barrier constructions in three-dimensional area. In this letter, a cube transition barrier system using smart UAVs is designed for three-dimensional space. Then, we formally define a problem whose goal is to maximize the number of cube transition barriers by applying …

Suspicious Behavior Detection With Temporal Feature Extraction And Time-Series Classification For Shoplifting Crime Prevention, Amril Nazir, Rohan Mitra, Hana Sulieman, Firuz Kamalov

All Works

The rise in crime rates in many parts of the world, coupled with advancements in computer vision, has increased the need for automated crime detection services. To address this issue, we propose a new approach for detecting suspicious behavior as a means of preventing shoplifting. Existing methods are based on the use of convolutional neural networks that rely on extracting spatial features from pixel values. In contrast, our proposed method employs object detection based on YOLOv5 with Deep Sort to track people through a video, using the resulting bounding box coordinates as temporal features. The extracted temporal features are then …

Forecasting >100 Mev Sep Events And Intensity Based On Cme And Other Solar Activities Using Machine Learning, Daniel Lee Griessler

Theses and Dissertations

There is a severe risk for astronauts and machinery from high intensity Solar Energetic Particle (SEP) events which can be mitigated through accurate forecast of their presence and peak intensity. By using characteristics of CME and other space weather phenomena, machine learning techniques have the potential to classify and predict the peak intensity of SEP events. The extreme scarcity of SEP events in current datasets poses a challenge to traditional machine learning techniques. In this work, we first demonstrate classifier machine learning techniques that can achieve an F1 score of 0.800 in forecasting SEP events. We then propose techniques for …

Lessening Student Anxiety With Docker, Kourtnee Fernalld

Theses and Dissertations

Remote learning during the COVID-19 pandemic transformed the educational landscape for hands-on Computer Science courses. This paradigm shift accelerated the transition from traditional in-person programming labs to decentralized student-provided resources. Even as students returned to in-person learning, many continued to rely on their personal computers rather than embracing university-provided labs. However, this shift to decentralized, heterogeneous environments introduces various information technology and instructional challenges. The recent emergence of lightweight, container-based virtualization presents a unique opportunity to address these challenges by offering standardized environments on decentralized platforms. To investigate this opportunity, we implemented lightweight virtualization for three undergraduate computer science courses …

Artificial Intelligence-Based Smarter Accessibility Evaluations For Comprehensive And Personalized Assessment, Sayeda Farzana Aktar

Dissertations (1934 -)

The research focuses on utilizing artificial intelligence (AI) and machine learning (ML) algorithms to enhance accessibility for people with disabilities (PwD) in three areas: public buildings, homes, and medical devices. The overarching goal is to improve the accuracy, reliability, and effectiveness of accessibility evaluation systems by leveraging smarter technologies. For public buildings, the challenge lies in developing an accurate and reliable accessibility evaluation system. AI can play a crucial role by analyzing data, identifying potential barriers, and assessing the accessibility of various features within buildings. By training ML algorithms on relevant data, the system can learn to make accurate predictions …

Designing Human-Centered Algorithms For The Public Sector: A Case Study Of The U.S. Child Welfare System, Devansh Saxena

Dissertations (1934 -)

Public sector agencies in the United States are increasingly seeking to emulate business models of the private sector centered in efficiency, cost reduction, and innovation through the adoption of algorithmic systems. These data-driven systems purportedly improve decision-making; however, the public sector poses its own unique challenges where policies, practices, and organizational constraints mediate all decisions. Algorithms that do not account for these pertinent aspects of professional practice frustrate practitioners, diminish the quality of human discretionary work, and amplify biases in decision-making. A human-centered research agenda can help us develop algorithms centered in social-ecological theories that support the decision-making processes of …

Optimizing Convolutional Neural Networks For Transient Detection In Optical Astronomy With Augmented Datasets, Wendy Mendoza

Theses and Dissertations

We present a technique for optical transient detection using artificial neural networks, particularly a Convolutional Neural Network (CNN), a deep learning algorithm. This method analyzes images of the same area of the sky captured by several telescopes, with one image serving as a reference for a probable transient’s epoch and the other as an image from a previous epoch. We train the CNN on simulated sources and test it on actual image data samples using data from the Dr. Cristina V. Torres Memorial Astronomical Observatory and Sloan Digital Sky Survey. This autonomous detection method replaces the standard procedure, which involves …

Using Deep Learning For Encrypted Traffic Analysis Of Amazon Echo, Surendra Pathak

Theses and Dissertations

The adoption of the Amazon Echo family of devices in modern homes has become very widespread at the current time, with hundreds of millions of devices sold. Moreover, the global smart speaker market size is growing vigorously and is projected to continue to bigger. Smart speakers allow users hands-free interaction by allowing voice control, promoting human-computer interaction to greater avenues. Though smart speaker can be useful assistant, it has some serious security concerns that need to be studied. In this study, an analysis of the security and privacy concerns of smart speakers is presented along with a passive attack, namely …

Identification Of Heart Disorders With Symbolic Aggregate Approximation, Moses K. Owusu

Theses and Dissertations

This project is an application of the Symbolic Aggregate Approximation (SAX) to 1000 fragments of ECG signals for 45 patients (42% females aged between 23 and 89 years and 58% males aged 32 to 89 years) using data obtained from the MIH-BIH Arrhythmia database to recognize cardiac health disorders. Data include a normal sinus rhythm, pacemaker rhythm and ECG readings for 15 heart disorders, making 17 in total. The aim is to use SAX to classify heart disorders using ECG signal, that analyzes QRS-complexes by first splitting the time series into smaller equally sized segments using the Piecewise Aggregate Approximation …

Defect-Based Approaches To Achieving Robust Modes In Hermitian And Non-Hermitian Systems, Fargol Seifollahi

Theses and Dissertations

A hallmark of topological physics has been its ability to facilitate wave propagation control and confinement. This thesis will be focused on wave localization and the existence of robust modes for one of the earliest and most important models of topological insulators, known as the Su-Schrieffer-Heeger (SSH) model. The first chapter covers some of the fundamental topics including the general SSH Hamiltonian, as well as the concept of bulk-boundary correspondence, winding number and distinction between the topologically trivial and non-trivial phases. We investigate the existence of two almost-zero energy states for a finite-sized topologically non-trivial SSH array which are exponentially …

Analyzing The On Source Window Of Supernova Sn2019ejj With A Multi Layered Signal Enhancement Algorithm With Coherent Waveburst And A Convolutional Neural Network, Michael Gale Benjamin

Theses and Dissertations

Core collapse supernovae (CCSN) are highly anticipated sources of gravitational waves during the fourth observation run (O4). CCSN signals are weak and unmodeled and the rate of occurrence in our galaxy is very low. Because of this, they provide a greater challenge to detect than previously detected GW sources. CCSN simulations are used to test the detection pipeline in the event a CCSN is detected. CCSN GW signals are often indistinguishable from the noise sources present in GW data. We present a multi layered signal enhancement pipeline which we have applied Machine Learning (ML) techniques. We have used a Convolutional …

Exploring The Localization Of Light In Discrete Systems With Conducted Symmetries, Aria Hajikhani

Theses and Dissertations

Controlling the localization of light has been studied through many approaches and has become a subject matter of interest due to potential applications in various fields. In this thesis, we will explore discrete systems with conducted symmetries, in both quantum and classical aspects, to establish a deeper understanding of light localization. First, we investigate atom-light interactions through exploring the Jaynes-Cummings model. We then introduce coupled cavity arrays (CCAs) where photons can hop between neighboring cavities and each cavity in the array may interact with one or more atoms. Specifically, we focus on systems in which one two-level atom is connected …