Physical Sciences and Mathematics Commons^™

Educators’ Perspectives Of Using (Or Not Using) Online Exam Proctoring., David Balash, Elena Korkes, Miles Grant, Adam J. Aviv, Rahel A. Fainchtein, Micah Sherr

Department of Math & Statistics Faculty Publications

The onset of the COVID-19 pandemic changed the land- scape of education and led to increased usage of remote proc- toring tools that are designed to monitor students when they take assessments outside the classroom. While prior work has explored students’ privacy and security concerns regard- ing online proctoring tools, the perspective of educators is under explored. Notably, educators are the decision makers in the classrooms and choose which remote proctoring ser- vices and the level of observations they deem appropriate. To explore how educators balance the security and privacy of their students with the requirements of remote exams, we …

Studying The Stability Of Collagen/Heparin Coatings To Be Used In Cell Therapy Applications, Gavin Mussino

Biological Sciences Undergraduate Honors Theses

This honors thesis aims to investigate the reusability and performance of cell coatings for cell therapy applications. Cell therapy, which involves the use of human cells to repair or replace damaged tissues, holds immense potential for medical advancements. However, ensuring the survival and functionality of transplanted cells remains a significant challenge. We focused on studying the effectiveness of coatings applied to cells for improved cell growth and viability. The research project involved the preparation of the coatings using a layer-by-layer method and the subsequent seeding of cells. The coated cells were then subjected to a series of experiments to assess …

Spectral Broadening Effects On Pulsed-Source Digital Holography, Steven A. Owens, Mark F. Spencer, Glen P. Perram

Faculty Publications

Using a pulsed configuration, a digital-holographic system is setup in the off-axis image plane recording geometry, and spectral broadening via pseudo-random bit sequence is used to degrade the temporal coherence of the master-oscillator laser. The associated effects on the signal-to-noise ratio are then measured in terms of the ambiguity and coherence efficiencies. It is found that the ambiguity efficiency, which is a function of signal-reference pulse overlap, is not affected by the effects of spectral broadening. The coherence efficiency, on the other hand, is affected. As a result, the coherence efficiency, which is a function of effective fringe visibility, is …

Bayesian Optimization With Switching Cost: Regret Analysis And Lookahead Variants, Peng Liu, Haowei Wang, Wei Qiyu

Research Collection Lee Kong Chian School Of Business

Bayesian Optimization (BO) has recently received increasing attention due to its efficiency in optimizing expensive-to-evaluate functions. For some practical problems, it is essential to consider the path-dependent switching cost between consecutive sampling locations given a total traveling budget. For example, when using a drone to locate cracks in a building wall or search for lost survivors in the wild, the search path needs to be efficiently planned given the limited battery power of the drone. Tackling such problems requires a careful cost-benefit analysis of candidate locations and balancing exploration and exploitation. In this work, we formulate such a problem as …

Functional Nanocomposite Coatings For Use In Food Packaging, Camden N. Webb

Master's Theses

Plastics are a class of materials known for their cost and property advantages, increasing significantly in their usage worldwide. Unfortunately, these benefits come with an increasingly concerning environmental impact. A combination of inadequate disposal options and combinations of materials have led to environmental disasters that will impact generations. One of the worst areas for plastic waste is food packaging. Plastic as a material generally excels at durability and longevity, but as food packaging, it outlives its intended purpose by several orders of magnitude. This leads to plastic food packaging materials sitting in landfill or leading to the environment for hundreds …

Visual Complexity Of The Time-Frequency Image Pinpoints The Epileptogenic Zone: An Unsupervised Deep-Learning Tool To Analyze Interictal Intracranial Eeg, Sarvagya Gupta

Graduate Masters Theses

Epilepsy, a prevalent neurological disorder characterized by recurrent seizures, continues to pose significant challenges in diagnosis and treatment, particularly among children. Despite substantial advancements in medical technology and treatment modalities, localization of the part of brain that causes seizures (Epileptogenic Zone) remains a difficult task. Intracranial EEG (iEEG) is often used to estimate the epileptogenic zone (EZ) in children with drugresistant epilepsy (DRE) and target it during surgery. Conventionally, iEEG signals are inspected in the time domain by human experts aiming to locate epileptiform activity.

Visual scrutiny of the iEEG time-frequency (TF) images can be an alternative way to review …

Facial Expression Recognition Using Convolutional Neural Networks (Cnns) And Generative Adversarial Networks (Gans) For Data Augmentation And Image Generation, Shekhar Singh

UNLV Theses, Dissertations, Professional Papers, and Capstones

Facial expressions play a crucial role in human communication, serving as a powerful means to convey emotions. However, classifying facial expressions using artificial intelligence (AI) can be challenging, especially with small datasets and images. Facial Expression Recognition (FER) is an active area of research, with Convolutional Neural Networks (CNNs) being widely employed for classification. In this research, we propose a CNN-based approach for FER that utilizes both original and augmented datasets to enhance classification accuracy. Experimental results on the FER2013 dataset show test accuracies of 63.39% and 64.59% for the original and augmented datasets, respectively, in a seven-class classification task. …

Unsupervised Machine Learning Of Tornado-Producing Storms In The Southeastern United States, Morgan R. Steckler

Masters Theses

The east-southeastern US is uniquely affected by storm and tornado-related damages, costs, injuries, and deaths. Based on doppler radar, satellite, and modeled data, previous research sought to understand these different types of storms that produce strong tornadoes. Many approaches to storm classification are time intensive, complex, and vary significantly across the literature. The purpose of this work is to (1) explore the radar-derived data structure and spread of strong tornado-producing mesoscale storms in the east-southeastern US; (2) use K-Means unsupervised machine learning methods to elucidate clusters (storm types) and clustering attributes; and (3) assess the utility of K-Means as a …

Phosphatase Enzyme-Responsive Synthetic Lipids For Liposome Immolation Towards Enhanced Cargo Release, Justin Thomas Kirby

Masters Theses

Liposomal nanoscale delivery vehicles have been shown to aid in the delivery of therapeutic cargo due to their ability to encapsulate and improve the pharmacokinetic properties of a range of drug molecules. However, liposome therapeutic potential could be enhanced by exerting greater control over liposome cargo delivery and release. This is being pursued by designing lipids that are able to respond to specific stimuli, particularly those overexpressed in diseased cells. In this thesis, we describe stimuli-responsive liposomes in which the enzyme alkaline phosphatase is used as the stimulus. This trigger was selected since this enzyme is overexpressed in certain cancer …

Uav-Based Quantification Of Dynamic Lahar Channel Morphology At Volcán De Fuego, Guatemala, Jerry C. Mock, Jeffrey B. Johnson, Armando Pineda, Gustavo Bejar, Amilcar Roca

Geosciences Faculty Publications and Presentations

This study quantified erosional and depositional processes for secondary lahars in Las Lajas drainage at Volcán de Fuego, Guatemala, during the rainy season from May to October 2021. Abundant pyroclastic material from ongoing eruptive activity is remobilized seasonally during heavy precipitation, which can impact infrastructure and populations living near Fuego. Our region of focus was in an agricultural zone 6 to 10 km from the summit, surveyed with an unoccupied aerial vehicle (UAV) quadcopter at monthly intervals. Imagery was processed into overlapping time-lapse structure from motion digital elevation models (DEMs). DEMs were differenced to find volumetric changes as a function …

Whitewater Sound Dependence On Discharge And Wave Configuration At An Adjustable Wave Feature, Taylor A. Tatum, Jacob F. Anderson, Timothy J. Ronan

Geosciences Faculty Publications and Presentations

Stream acoustics has been proposed as a means of monitoring discharge and wave hazards from outside the stream channel. To better understand the dependence of sound on discharge and wave characteristics, this study analyzes discharge and infrasound data from an artificial wave feature which is adjusted to accommodate daily changes in recreational use and seasonal changes in irrigation demand. Monitorable sound is only observed when discharge exceeds ∼35 m³/s, and even above that threshold the sound-discharge relationship is non-linear and inconsistent. When sound is observed, it shows consistent dependence on wave type within a given year, but the …

Learning To Send Reinforcements: Coordinating Multi-Agent Dynamic Police Patrol Dispatching And Rescheduling Via Reinforcement Learning, Waldy Joe, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We address the problem of coordinating multiple agents in a dynamic police patrol scheduling via a Reinforcement Learning (RL) approach. Our approach utilizes Multi-Agent Value Function Approximation (MAVFA) with a rescheduling heuristic to learn dispatching and rescheduling policies jointly. Often, police operations are divided into multiple sectors for more effective and efficient operations. In a dynamic setting, incidents occur throughout the day across different sectors, disrupting initially-planned patrol schedules. To maximize policing effectiveness, police agents from different sectors cooperate by sending reinforcements to support one another in their incident response and even routine patrol. This poses an interesting research challenge …

Dna Self-Assembly Of Trapezohedral Graphs, Hytham Abdelkarim

Electronic Theses, Projects, and Dissertations

Self-assembly is the process of a collection of components combining to form an organized structure without external direction. DNA self-assembly uses multi-armed DNA molecules as the component building blocks. It is desirable to minimize the material used and to minimize genetic waste in the assembly process. We will be using graph theory as a tool to find optimal solutions to problems in DNA self-assembly. The goal of this research is to develop a method or algorithm that will produce optimal tile sets which will self-assemble into a target DNA complex. We will minimize the number of tile and bond-edge types …

Contactless Food Ordering System, Rishivar Kumar Goli

Electronic Theses, Projects, and Dissertations

Contactless food ordering has revolutionized the way a customer interacts with restaurants by allowing them to place orders and make transactions. Through these web-based platforms, customers can now browse menus, customize orders, and make payments seamlessly. By scanning the restaurant’s QR code, customers can reserve a table. If the table is available, then automatically it will be reserved. However, if the table is occupied the customer will be added to the waiting list. Once the customer selects desired food then they can securely make payments based on ordered food items. The food will be delivered straight to the customer's table. …

Genetic Programming To Optimize Performance Of Machine Learning Algorithms On Unbalanced Data Set, Asitha Thumpati

Electronic Theses, Projects, and Dissertations

Data collected from the real world is often imbalanced, meaning that the distribution of data across known classes is biased or skewed. When using machine learning classification models on such imbalanced data, predictive performance tends to be lower because these models are designed with the assumption of balanced classes or a relatively equal number of instances for each class. To address this issue, we employ data preprocessing techniques such as SMOTE (Synthetic Minority Oversampling Technique) for oversampling data and random undersampling for undersampling data on unbalanced datasets. Once the dataset is balanced, genetic programming is utilized for feature selection to …

Mathematics Behind Machine Learning, Rim Hammoud

Electronic Theses, Projects, and Dissertations

Artificial intelligence (AI) is a broad field of study that involves developing intelligent
machines that can perform tasks that typically require human intelligence. Machine
learning (ML) is often used as a tool to help create AI systems. The goal of ML is
to create models that can learn and improve to make predictions or decisions based on given data. The goal of this thesis is to build a clear and rigorous exposition of the mathematical underpinnings of support vector machines (SVM), a popular platform used in ML. As we will explore later on in the thesis, SVM can be implemented …

Enabling Affordances Of Blockchain In Agri-Food Supply Chains: A Value-Driver Framework Using The Q-Methodology, Pouyan Jahanbin, Stephen C. Wingreen, Ravishankar Sharma, Behrang Ijadi, Marlon M. Reis

All Works

The application of blockchain beyond cryptocurrencies has received increasing attention from industry and scholars alike. Given predicted looming food crises, some of the most impactful deployments of blockchains are likely to concern food supply chains. This study outlined how blockchain adoption can result in positive affordances in the food supply chain. Using Q methodology, this study explored the current status of the agri-food supply chain and how blockchain technology could be useful in addressing existing challenges. This theorization leads to the proposition of the 3TIC value-driver framework for determining the enabling affordances of blockchain that would increase shared value for …

Statistical Inference On Lung Cancer Screening Using The National Lung Screening Trial Data., Farhin Rahman

Electronic Theses and Dissertations

This dissertation consists of three research projects on cancer screening probability modeling. In these projects, the three key modeling parameters (sensitivity, sojourn time, transition density) for cancer screening were estimated, along with the long-term outcomes (including overdiagnosis as one outcome), the optimal screening time/age, the lead time distribution, and the probability of overdiagnosis at the future screening time were simulated to provide a statistical perspective on the effectiveness of cancer screening programs. In the first part of this dissertation, a statistical inference was conducted for male and female smokers using the National Lung Screening Trial (NLST) chest X-ray data. A …

Penalized Bayesian Exponential Random Graph Models., Vicki Modisette

Electronic Theses and Dissertations

Networks have the critical ability to represent the complex interconnectedness of social relationships, biological processes, and the spread of diseases and information. Exponential random graph models (ERGM) are one of the popular statistical methods for analyzing network data. ERGM, however, struggle with computational challenges and degeneracy issues, further exacerbated by their inability to handle high-dimensional network data. Bayesian techniques provide a promising avenue to overcome these two problems. This paper considers penalized Bayesian exponential random graph models with adaptive lasso and adaptive ridge penalties to perform variable selection and reduce multicollinearity on a variety of networks. The experimental results demonstrate …

On The Chemistry Of Aqueous Ammonium Acetate Droplets During Native Electrospray Ionization Mass Spectrometry, Lars Konermann, Zeyuan Liu, Yousef Haidar, Methew J. Willians, Nicholas A. Bainbridge

Chemistry Publications

Ammonium acetate (NH₄Ac) is a widely used solvent additive in native electrospray ionization (ESI) mass spectrometry. NH₄Ac can undergo proton transfer to form ammonia and acetic acid (NH₄⁺ + Ac^- → NH₃ + HAc). The volatility of these products ensures that electrosprayed ions are free of undesired adducts. NH₄Ac dissolution in water yields pH 7, providing “physiological” conditions. However, NH₄Ac is not a buffer at pH 7 because NH₄⁺ and Ac^- are not a conjugate acid/base pair (L. Konermann, J. Am. Soc. Mass Spectrom. 2017 …

The Effect Of Package Types On Fresh Peaches In The Direct-To-Consumer Distribution Environment, Brennan Lytle

All Theses

The direct-to-consumer (DTC) shipping mode presents new opportunity for fresh peach sales in North America where demand over the past four decades has steadily declined. The hazards in this distribution mode are severe, and fresh peaches are fragile emphasizing the need for proper protection. A full analysis that not only encompasses the effects of the direct-to-consumer distribution environment, but also incorporates analyses of the environmental and economic impact of the packages utilized for transit of peaches is necessary. In this study, we use the metrics of peach grade, firmness, soluble solids concentration, and percent softness before and after the distribution …

A Hybrid Lateral Flow Sand Filter Wastewater Treatment System: An Evaluation On The Treatment And Disposal Capabilities Of A Modified Sand Filter, Harry Mccaskill Iv

<strong> Theses and Dissertations </strong>

Decentralized wastewater treatment exists primarily in suburban and rural areas where centralized treatment is not an option. Traditional on-site treatment systems usually include the use of a septic tank and a drain field. This orthodox method works well when implemented into environments that are accommodating for the infiltration of effluents, and thus allowing for soil treatment. Unfortunately, there are some circumstances that prevent traditional systems from working such as impermeable soil conditions. The Wastewater Treatment System analyzed in this thesis was created to overcome such inhospitable environments. More specifically, this system is catered towards the rural residences of The Alabama …

Epileptic Seizure Classification Using Image-Based Data Representation, Amber Surles

<strong> Theses and Dissertations </strong>

Epilepsy is a recurrence of seizures caused by a disorder of the brain in over 3.4 million people nationwide. Some people are able to predict their seizures based off prodrome, which is an early sign or symptom that usually resembles mood changes or a euphoric feeling even days to an hour before occurrence. Consequently, the natural instincts of the body to react to an upcoming attack lends credence to the existence of a pre-ictal state that precedes seizure episodes. Physicians and researchers have thus sought for an automated approach for predicting or detecting seizures.

In this research, we evaluate the …

Leveraging Eco-Evolutionary Models For Gene Drive Risk Assessment, Matthew A. Combs, Andrew J. Golnar, Justin M. Overcash, Alun L. Lloyd, Keith R. Hayes, David A. O'Brochta, Kim M. Pepin

United States Department of Agriculture Wildlife Services: Staff Publications

Engineered gene drives create potential for both widespread benefits and irreversible harms to ecosystems. CRISPR-based systems of allelic conversion have rapidly accelerated gene drive research across diverse taxa, putting field trials and their necessary risk assessments on the horizon. Dynamic processbased models provide flexible quantitative platforms to predict gene drive outcomes in the context of system-specific ecological and evolutionary features. Here, we synthesize gene drive dynamic modeling studies to highlight research trends, knowledge gaps, and emergent principles, organized around their genetic, demographic, spatial, environmental, and implementation features. We identify the phenomena that most significantly influence model predictions, discuss limitations of …

Paradox Diapir Inclusions As A Window Into Diapiric Processes In Proximity To The Uncompahgre Uplift And The Early History Of The Paradox Basin, Utah And Colorado, Madison Clare Woelfel

Open Access Theses & Dissertations

Layered evaporite sequences, cyclic, kilometer-thick deposits of salt, are among the most unusual and fascinating lithologies that geologists encounter. There is no recent analogue to their formation, and their ability to flow when subject to differential pressure makes them unique. Salt structures serve as sources for halite, bittern salts, metals, and hydrocarbons and can be used for storage of materials, including hydrocarbons, carbon dioxide, hydrogen, and nuclear waste. Basins in which layered evaporite sequences are deposited receive detrital input sporadically from adjacent areas, depositing inclusions of non-evaporite lithologies that are entrained when salt flows. These inclusions are exposed in a …

Performance Evaluation Of A Coupled Photovoltaic-Thermal Solar Powered Desalination Pilot System, Martin Chavarin

Open Access Theses & Dissertations

A pilot scale coupled photovoltaic-thermal solar powered desalination system was evaluated at the Brackish Groundwater National Desalination Research Facility (BGNDRF). The pilot system consisted of a 3-kW photovoltaic-thermal (PVT) solar panel array and a 2.3 kW photovoltaic (PV) array coupled with a 4 gal/min single-stage 4 membrane reverse osmosis (RO) desalination system. A heat exchange system was in place to provide simultaneous cooling for the PVT system and heating to the RO system feed water. This system was evaluated with three objectives in mind. The first objective was to identify whether cooling of the PVT panels resulted in a significant …

How Active Rainwater Harvesting May Help Reduce Nuisance Flooding: Flood Analysis And Social Barriers To Adoption, Isabel Lopez

Open Access Theses & Dissertations

As urbanization continues to expand, fewer pervious surfaces are available to help reduce stormwater runoff from rainfall. The impacts of urbanization are becoming evident through sunny day flooding - flooding that occurs in areas not designated by the Federal Emergency Management Agency (FEMA) as flood zones. Nevertheless, water accumulates in low-lying areas and compromises street intersections and other parts of neighborhoods. Some methods can help alleviate the impacts of unexpected heavy rains, such as passive and active rainwater harvesting. As a pilot study, in a selected area in the northeast of El Paso, the level of adoption (e.g., what percentage …

Comparative Study Of Supervised Classification Techniques With A Modified Knn Algorithm, Noah Owusu

Open Access Theses & Dissertations

The goal of classification is to develop a model that can be used to accurately assign new observations to labeled classes based on the patterns learned from the training data. K-nearest Neighbors algorithm (KNN) is a popular and widely used algorithm for classification, however, its performance can be adversely affected by the presence of outliers in a dataset. In this study we have modified this existing KNN algorithm that can alleviate the effect of outliers in a dataset, thereby improving the performance of the KNN algorithm. We compared the performances of the Modified KNN method and the Existing KNN algorithm …

Origin Of The Mega-Streamlined Morphology In Ne Africa And Arabia: Remote Sensing And Field-Based Investigations, Mohamed Samy Mohamed Elhebery

Dissertations

Mega-streamlined landforms on Earth and Mars have been attributed to aeolian, glaciogenic, fluvial, and tectonic processes. Identifying the forces that shaped these landforms is paramount for understanding landscape evolution and constraining paleo-climate models and ice sheet reconstructions. Exhumed Late Ordovician glacial deposits and landscape of the North Gondwana are reported here for the first time from SE Egypt. Using field and remote sensing (Advanced Land Observing Satellite [ALOS], Phased Array L-band Synthetic Aperture Radar (PALSAR) radar, multispectral Landsat TM datasets, and digital elevation models (DEMs) I mapped the distribution of the Late Ordovician glacial features (i.e. deposits and landforms) in …

Azimuthal Correlations Within Exclusive Dijets With Large Momentum Transfer In Photon-Lead Collisions, A. Tumasyan

Department of Physics and Astronomy: Faculty Publications

The structure of nucleons is multidimensional and depends on the transverse momenta, spatial geometry, and polarization of the constituent partons. Such a structure can be studied using high-energy photons produced in ultraperipheral heavy-ion collisions. The first measurement of the azimuthal angular correlations of exclusively produced events with two jets in photon-lead interactions at large momentum transfer is presented, a process that is considered to be sensitive to the underlying nuclear gluon polarization. This study uses a data sample of ultraperipheral lead-lead collisions at √s_NN = 5.02 TeV, corresponding to an integrated luminosity of 0.38 nb⁻¹, collected with …