Physical Sciences and Mathematics Commons^™

Populations Digitally Excluded From Education: Issues, Factors, Contributions And Actions For Policy, Practice And Research In A Post-Pandemic Era, Don Passey, Jean Gabin Ntebutse, Manal Yazbak Abu Ahmad, Janet Cochrane, Simon Collin, Asmaa Ganayem, Elizabeth Langran, Sadaqat Mulla, Ma. Mercedes T. Rodrigo, Toshinori Saito, Miri Shonfeld, Saunand Somasi

Department of Information Systems & Computer Science Faculty Publications

This conceptual paper draws on a wide range of research and policy literature, providing a contemporary view of issues, factors and practices that affect education for digitally excluded populations. Concern for how education for digitally excluded populations can be supported is focal to this paper, with different sections offering key related perspectives. From an analysis of issues, factors and practices, actions for policy, practice and research are identified. Given a key finding that power issues can have major effects on plans, implementation processes and outcomes when addressing needs of education for digitally excluded populations, the paper concludes by offering frameworks …

Understanding The Influence Of Traffic And Noise On The Wildlife Community Surrounding Fm106 And Sh100 In South Texas, Anna Rose Mehner

Theses and Dissertations

In South Texas, highways create landscape fragmentation, habitat degradation, and result in wildlife vehicle collisions. Vehicle collisions are the highest known cause of mortality of the endangered ocelot (Leopardus pardalis), which led Texas Department of Transportation to install nine wildlife crossing structures (WCS) on Farm-to-Market 106 and five on State Highway 100. These highways are along Laguna Atascosa National Wildlife Refuge, which is the location of the southernmost breeding population of ocelots in the United States. Many other wildlife species including bobcat (Lynx rufus) and coyote (Canis latrans), are present along these highways and …

Structure Modifications And Alternative Monitoring Designs Of Wildlife Road Mitigation Structures, Madison T. Nadler

Theses and Dissertations

Wildlife mitigation structures are designed to keep animals off roadways while providing them safe passage to the other side and not impeding traffic flow. Camera traps are commonly used to assess the success of these mitigation structures, but there are downfalls to both the methods and structures. Alternative mitigation structure designs are needed to better prevent wildlife from accessing roadways in areas where they should be deterred. Additionally, traditional camera trapping methods do not accurately capture the full wildlife communities that may be utilizing these structures and other survey methods are needed, specifically aimed at small mammals, amphibians, and reptiles. …

Technical Potential And Challenges For Agrivoltaic Development In Nigeria, Ifeoluwa Ezekiel Babarinde

Theses and Dissertations

The co-location of agriculture and solar photovoltaic (PV) infrastructure, known as agrivoltaics, is an increasingly popular practice that offers co-benefits like reduced plant drought stress and improved yields of shade-tolerant crops, particularly in water-scarce agricultural regions. Despite its global growth, knowledge on the technical potential, opportunities, and challenges for agrivoltaic development remains limited in the Global South. Here we address this knowledge gap for Nigeria, Africa’s most populous country, by identifying high-potential regions based on the premise that agrivoltaic co-benefits are generally most pronounced in arable lands with both high solar irradiation and water stress. We find that northern regions, …

Guiding Wildlife: Evaluating Wildlife Exit Designs And Sensor Lights For Safer Highways In South Texas, Rupesh Maharjan

Theses and Dissertations

Roadside exclusionary fencing is more prevalent on highways to prevent wildlife-vehicle collisions. Although it can mitigate wildlife road mortality by limiting their access to the road, it can also create a barrier for wildlife stranded within the right-of-way. In State Highway 100 of Texas, the Texas Department of Transportation installed ten wildlife exits to allow wildlife to escape the fenced roadway, and a pair of sensor lights on 13 wildlife guards (WGs) to scare off target species (bobcats and coyotes) from crossing the guards and accessing the roadway. In this study, the effectiveness of three wildlife exit (WE) designs were …

Implementing Organic Fertilization Practices To Improve Aloe Vera Growth And Soil Health In The Lower Rio Grande Valley, Isaiah Edward Jaramillo

Theses and Dissertations

Aloe vera (L.) (Aloe) Burm. f., is valued for its applications across the cosmetic, medicinal, and food industries due to its leaf gel. In the aloe industry, the extraction of gel from leaves generates significant quantities of organic waste, which presents an opportunity to repurpose this material as an amendment in aloe cultivation. While Aloe is renowned for its resilience, understanding the feasibility of using these organic shavings as a soil fertility amendment in aloe production is critical. This research aims to identify sustainable fertilization methods for Aloe that can maintain and/or improve crop yield while enhancing soil health. This …

Proof Of Concept: Simulating Drone Tracking In A Border Security Context, Jose Ruben Espinoza

Theses and Dissertations

Worldwide availability of drone technology has risen to unprecedented levels within the past century due to its commercial availability. While there has been various positive applications of such technology, it has additionally found usage within security critical contexts. Specifically, there have been reports of illegal drug smuggling along the Mexico-United States border in which quadrocopter based drones have been used. Within our research we aim to showcase, as a proof of concept, that autonomous drone technology can be leveraged within a defensive approach via the usage of reinforcement learning and object detection for security critical contexts. To promote the importance …

Evaluation Of Polymerization Condition Reactions Of Methyl Vinyl Ketone For Hydrogen Storage, Rituborna Ghosh

Theses and Dissertations

Hydrogen is widely regarded as one of the most promising clean alternative fuel sources; however, its widespread adoption has been hindered by significant challenges related to storage and transportation. Various storage methods have been proposed and developed, with continuous advancements being made to address these issues. Among the most effective solutions is the utilization of polymers, which serve as safe and efficient hydrogen storage media. This work investigated the polymerization of methyl vinyl ketone using different ratio of monomer: initiator and monomer: crosslinker using N,N′-methylenebisacrylamide (MBA) as crosslinker and ammonium persulfate (APS) as initiator in a free radical polymerization mechanism. …

Theoretical Insights And Analysis Into Luneburg Lens, Aram Flores

Theses and Dissertations

Advancements in wireless communications necessitate innovative antenna designs for radar systems and satellite communications. The Luneburg lens, theorized by Rudolf Luneburg in 1944, is a gradient-index lens capable of focusing electromagnetic waves onto a point on its surface, offering potential improvements in antenna gain and performance. Access to the lenses, courtesy of Assured Space Access Incorporated, enabled me to research the lenses response, and specific design details remain confidential. Practical assessments of 3D-printed Luneburg lenses of varying sizes are limited, including factors such as lens alignment and focal point offset. This study investigates the performance of 6-inch and 13.25-inch Luneburg …

Bayesian Lasso Regularized Quantile Regression And Its Applications, Priscilla Kissi-Appiah

Theses and Dissertations

Since the pioneering work of (Koenker and Bassett Jr 1978), quantile regression has been a popular regression technique that helps researchers investigate a whole distribution of the response variable. In addition, due to the quantile check loss function, it is robust against outliers and heavy-tailed distributions of the response variable and can provide a more comprehensive picture of modeling via exploring the conditional quantiles of the response variable. In this research, we study the lasso regularized quantile regression from a Bayesian perspective. We develop an efficient sampling algorithm to generate posterior samplings for making posterior inference by using a location-scale …

Examining Hispanic Beginning Farmers And Ranchers In The Rio Grande Valley Through A Community Capitals Framework, Perla Kimberly Schrock

Theses and Dissertations

While existing literature addresses the experiences of beginning farmers and ranchers (BFR), there is a notable gap in research focused on Hispanic beginning farmers and ranchers (HBFR). This study aimed at exploring the unique experiences of HBFR in a predominantly Hispanic region, the Rio Grande Valley (RGV), employed the Community Capitals Framework (Flora et al., 2016). I conducted 16 semi-structured interviews with HBFR and local nonprofit organizations and federal employees, complemented by participant observations. Through thematic and content analysis of the interview transcripts, findings revealed valuable insights into the livelihoods of HBFR. Despite HBFR facing significant challenges, this study demonstrated …

Thermal Conductivity Characterization Of High Oleic Vegetable Oils Based Hybrid Nanofluids Formulated Using Gnp, Tio2, Mos2, Al2o3 Nanoparticles For Mql Machining, Anthony Chukwujekwu Okafor, Tobechukwu Kingsley Abor, Saidanvar Esanjonovich Valiev, Ignatius Echezona Ekengwu, Abiodun Saka, Monday Uchenna Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper presents the results of thermal conductivity characterization of six high oleic soybean oil (HOSO) and four high oleic canola oil (HOCO)-based hybrid nanofluids formulated with four types of nanoparticles (Graphene nanoplatelet (xGnP), TiO2, MoS2, and Al2O3) at nanoparticles wt.% concentration from 1 % to 7 % in 1 % increment using the two-step method for use in MQL machining of difficult-to-cut metals. Thermal conductivity of the formulated hybrid nanofluids were measured using Thermtest Transient Hot Wire Liquid Thermal Conductivity Meter at temperatures from 25 °C to 75 °C in increment of 10 °C. Obtained results showed that thermal …

Physicochemical Property Effects On Immune Modulating Polymeric Nanoparticles: Potential Applications In Spinal Cord Injury, Daniel J. Kolpek, Jaechang Kim, Hisham Mohammed, John C. Gensel, Jonghyuck Park

Markey Cancer Center Faculty Publications

Nanoparticles (NPs) offer promising potential as therapeutic agents for inflammation-related diseases, owing to their capabilities in drug delivery and immune modulation. In preclinical studies focusing on spinal cord injury (SCI), polymeric NPs have demonstrated the ability to reprogram innate immune cells. This reprogramming results in redirecting immune cells away from the injury site, downregulating pro-inflammatory signaling, and promoting a regenerative environment post-injury. However, to fully understand the mechanisms driving these effects and maximize therapeutic efficacy, it is crucial to assess NP interactions with innate immune cells. This review examines how the physicochemical properties of polymeric NPs influence their modulation of …

A Comparative Study Of Patterns, Causes, And Impacts Of Data Breaches Across Geographical Regions And Time Frames, Bhavish Balsara

Electronic Theses, Projects, and Dissertations

The rise of digital technologies and interconnected systems has made data breaches a growing global concern. This culmination project explores the patterns, causes, and impacts of data breaches across various countries with varying levels of economic development and cybersecurity infrastructure from 2020 to 2023. This research aims to provide insights into the global landscape of data breaches and how they have evolved in recent years. The research questions are: (Q1) How do data breach patterns differ between countries with different levels of economic development and cybersecurity infrastructure? (Q2) What patterns and trends can be identified in data breaches when analyzing …

Interactive Known-Item Search In Large Video Corpora, Zhixin Ma

Dissertations and Theses Collection (Open Access)

The surge in video volume makes it challenging to locate a specific target with a single query using automatic video retrieval systems. The interactive video retrieval offers a solution by enabling users to iteratively refine a search. Nevertheless, existing systems often present users with an overwhelming number of similar videos, which can lead to mental fatigue while inspecting results and increase difficulty in providing feedback. This dissertation studies known-item video search and addresses four key challenges. First and foremost, as the link between users and the system, the interaction must be both efficient and effective. To ensure effectiveness, the user’s …

Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey

All Theses

This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …

Real-Time Network Simulations For Ml/Dl Ddos Detection Using Docker, Luis D. Garcia

Master's Theses

As the integration of artificial intelligence (AI) within cybersecurity continues to

grow, machine learning (ML) and deep learning (DL) models are increasingly used to

detect cyber attacks. However, these models are rarely evaluated in real-time attack

scenarios to see how subtle changes from the real networking environment can affect

their predictions. To address this issue, we propose a scalable, platform-independent

Docker testbed specifically designed for simulating real-time Distributed Denial of

Service (DDoS) attack scenarios that allows researchers to deploy and evaluate their

pre-trained, ML and DL detection models. Our framework is simple to configure

and can run across Intel and …

An Investigation Into The Use Of Amateur Astronomy Equipment For Optical Orbit Determination Using A Mobile Telescope Platform, Johan C. Govaars

Master's Theses

The process of optical orbit determination has long been in the domain of large organizations and stationary observatories with highly specialized scientific equipment. This thesis seeks to determine not only if satellites can be captured regularly using purely commercial-off-the-shelf (COTS) equipment, but also if initial orbit determinations can be made using that data. Moreover, the use of a mobile telescope platform allows users to circumvent the restrictions of fixed observatories such as low horizon viewing restrictions or existing light pollution.

A completely COTS setup was utilized that included an 8-inch Celestron NextStar 8SE telescope with an f/6.3 focal reducer and …

Fortifying Ai-Iot Food Supply Chains: Addressing Third-Party Cybersecurity Vulnerabilities, Ashwin Chudasama

Electronic Theses, Projects, and Dissertations

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) technologies within food supply chains has led to significant operational efficiencies but has also introduced cybersecurity vulnerabilities, especially from third-party vendors supplying critical software and hardware. This study explores these vulnerabilities and evaluates multi-layered defense strategies to mitigate the cybersecurity risks they introduce. The research questions guiding this study are: (Q1) How do third-party vendors contribute to cybersecurity vulnerabilities within AI-IoT systems in the food industry? (Q2) How can multi-layered defense strategies effectively mitigate the cybersecurity risks introduced by these vendors?

Using a systematic literature review (SLR) approach …

Personal Exposure To Black Carbon: Impact Of Time-Activity Patterns And Environmental Factors On Exposure Levels, Sai Deepak Pinakana, Johnathan R. Gonzalez, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Black carbon (BC) is a critical environmental pollutant with significant implications for human health. This study aims to quantify personal exposure to BC by focusing on the influence of microenvironments and time-activity patterns in the Rio Grande Valley (RGV) region of South Texas, USA. Over eight days in March and April 2023, a portable aethalometer and GPS tracking instruments were used to measure BC exposure among a study participant, alongside recording the time spent in various microenvironments. The BC measurements were correlated to the time activity patterns to calculate BC inhaled dosage values thereby elucidating its impact on human health. …

Unsupervised Moving Object Segmentation With Atmospheric Turbulence, Dehao Qin

All Theses

Moving object segmentation in the presence of atmospheric turbulence is a highly challenging task due to the irregular and time-varying distortions induced by the atmospheric turbulence. This thesis presents an unsupervised approach for segmenting moving objects in videos affected by such atmospheric turbulence. The proposed methodology is grounded in a detect-then-grow scheme: the algorithm begins by identifying a small set of moving object pixels (seed points) with high confidence and progressively expanding a foreground mask from these seed points to segment all moving objects. The proposed approach capitalizes on rigid geometric consistency across video frames to disentangle different types of …

Shifting Perspectives With Procedural Modeling Techniques And Vertex Animated Textures For Real-Time Interactive Morphing, Stephanie Schulze

All Theses

As humans experience reality, they intake external stimuli using sensory receptors to process information, forming a perception. Perceptions are subjective and shape each individual’s reality. Naturally then, by changing one’s perceptions, their experience of reality is altered, for better or worse. To emphasize the idea that perception is malleable and encourage a mindset of questioning alternative ways to look at a situation, an interactive experience in Unreal Engine is developed where a dull cityscape morphs and transforms into a surreal oversized nature scene. Procedural modeling techniques are used to create a variety of morphing assets, while Vertex Animated Textures are …

Geoflood: Computational Model For Overland Flooding, Brian Kyanjo

Boise State University Theses and Dissertations

Overland flooding, a critical environmental phenomenon, poses significant challenges for computational modeling due to its complex hydrodynamics and the need for high-resolution data. This thesis presents GeoFlood, a new open-source software package for overland flooding simulations. The computational model solves shallow water equations (SWE) on a quadtree hierarchy of mapped, logically Cartesian grids managed by the parallel, adaptive library ForestClaw (Calhoun & Burstedde, 2017). The model is validated using standard benchmark tests from Neelz & Pender (2013) and against results from the GeoClaw software (George, 2011; Clawpack Development Team, 2020) for the historical Malpasset dam break problem. The benchmark test …

Single-Shot Mev-Resolution Hard X-Ray Spectrograph For Cavity-Based X-Ray Free Electron Laser, Keshab Kauchha

Dissertations

The Cavity-Based X-ray Free Electron Laser (CBXFEL) is a possible future direction in the development of fully coherent hard X-ray sources of high spectral brilliance, a narrow spectral bandwidth of ≃ 1 − 100 meV, and a high repetition rate of ≃ 1 MHz. A diagnostic tool is required to measure CBXFEL spectra with a meV resolution on a shot-to-shot basis.

The CBXFEL hard X-ray spectrograph is designed to image 9.831 keV X-rays in a ≃ 200 meV spectral window and with a spectral resolution of a few meV using an LCLS XFEL (Linac Coherent Light Source X-ray Free Electron …

Experimental Evaluation Of A Recrosslinkable Co2-Resistant Micro-Sized Preformed Particle Gel For Co2 Sweep Efficiency Improvement In Reservoirs With Super-K Channels, Adel Alotibi, Tao Song, Ali Al Brahim, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

A recross linkable CO₂-resistant branched preformed particle gel (CO₂-BRPPG) was developed for controlling CO₂ injection conformance, particularly in reservoirs with super-permeable channels. Previous work focused on a millimeter-sized CO₂-BRPPG in open fractures, but its performance in high-permeability channels with pore throat networks remained unexplored. This study used a sand pack model to evaluate a micro-sized CO₂-BRPPG under varying conditions of salinity, gel concentration, and pH. at ambient conditions, the equilibrium swelling ratio (ESR) of the gel reached 76 times its original size. This ratio decreased with increasing salinity but remained stable …

Anomaly Detection Using Unsupervised Machine Learning Algorithms: A Simulation Study, Edmund F. Agyemang

School of Mathematical & Statistical Sciences Faculty Publications

This study presents a comprehensive evaluation of five prominent unsupervised machine learning anomaly detection algorithms: One-Class Support Vector Machine (One-Class SVM), One-Class SVM with Stochastic Gradient Descent (SGD), Isolation Forest (iForest), Local Outlier Factor (LOF), and Robust Covariance (Elliptic Envelope). Through systematic analysis on a synthetically simulated dataset, the study assessed each algorithm’s predictive performance using accuracy, precision, recall, and F1 score specifically for outlier detection. The evaluation reveals that One-Class SVM, Isolation Forest, and Robust Covariance are more effective in identifying outliers in the synthetic simulated dataset, with Isolation Forest slightly outperforming the other algorithms in terms of balancing …

Nature-Based Solutions For Flood Risk Mitigation: Mapping And Hydrological Modeling In An Under-Resourced Urban Area On The Mississippi Gulf Coast, Jennifer Makenzie Holifield

Master's Theses

Flooding is the most frequent and costly disaster in the United States, affecting people disproportionately based on environmental, societal, and economic limitations. Through stakeholder engagement, open-access research, and nature-based solutions (NBS), ecology and hydrology can be bridged with local-scale politics to raise awareness of local issues and form strong interdisciplinary bonds. I approached nature-based equity from a ground front, in which I engaged with local stakeholders and city officials to gain insight and calibration on flooding experiences and flooding presence within Moss Point, MS. This engagement helped calibrate GIS models, from which, I found that the flooding hazards of Moss …

Modeling Hourly Storm Surges Using Deep Learning Techniques, Md Abu Zafor

Master's Theses

Storm surges cause coastal flooding, one of the most devastating coastal hazards. Accurate modeling of storm surges is essential for predicting and mitigating these impacts. Traditional approaches model surges at individual tide gauges and often focus on daily time scales, leading to data redundancy and limiting their ability to capture sub-daily variability. This study addresses these limitations using deep learning (DL) algorithms to model hourly surges simultaneously at multiple tide gauges along the U.S. East Coast and Gulf of Mexico. Three algorithms, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and a hybrid ConvLSTM are employed to model surges using …

Array Of Graphene Solar Cells On 100 Mm Silicon Wafers For Power Systems, Syed M. Rahman, Md R. Kabir, Tamzeed B. Amin, James M. Mangum, Ashaduzzaman, Paul M. Thibado

Physics Faculty Publications and Presentations

High electrical conductivity and optical transparency make graphene a suitable candidate for photovoltaic-based power systems. In this study, we present the design and fabrication of an array of graphene-based Schottky junction solar cells. Using mainstream semiconductor manufacturing methods, we produced 96 solar cells from a single 100 mm diameter silicon wafer that was precoated with an oxide layer. The fabrication process involves removing the oxide layer over a select region, depositing metal contacts on both the oxide and bare silicon regions, and transferring large-area graphene onto the exposed silicon to create the photovoltaic interface. A single solar cell can provide …

An Empirical Framework Characterizing The Metallicity And Star-Formation History Dependence Of X-Ray Binary Population Formation And Emission In Galaxies, Bret D. Lehmer, Erik B. Monson, Rafael T. Eufrasio, Amirnezam Amiri, Keith Doore, Antara Basu-Zych, Kristen Garofali, Lidia Oskinova, Jeff J. Andrews, Vallia Antoniou, Robel Geda, Jenny E. Greene, Konstantinos Kovlakas, Margaret Lazzarini, Chris T. Richardson

Physics Faculty Publications and Presentations

We present a new empirical framework modeling the metallicity and star formation history (SFH) dependence of X-ray luminous (L ≳ 10³⁶ erg s⁻¹) point-source population X-ray luminosity functions (XLFs) in normal galaxies. We expect that the X-ray point-source populations are dominated by X-ray binaries (XRBs), with contributions from supernova remnants near the low luminosity end of our observations. Our framework is calibrated using the collective statistical power of 3731 X-ray detected point sources within 88 Chandra-observed galaxies at D ≲ 40 Mpc that span broad ranges of metallicity (Z ≈ 0.03–2 Z_⊙), SFH, …