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A Developmental Investigation Of Separation And Analysis Of Molecular Mass 302 Da Polyaromatic Hydrocarbons Using High Performance Liquid Chromatography And Chiral Stationary Phase, James Janesko

Electronic Theses and Dissertations, 2020-

High molecular weight – polycyclic aromatic hydrocarbons (HMW-PAH) are often found where air, water, and soil are subject to higher levels of industrial pollutants. These molecules are environmentally concerning due to their carcinogenic, mutagenic, and tumorigenic propensities. Furthermore, the isomers in this family are challenging to separate due to similar retention parameters, spectroscopic fingerprints, and mass spectral patterns. The primary purpose of this dissertation is to expand on the methodology for separation and analysis of the molecular mass 302 Da six-ring isomers using High Performance Liquid Chromatography. Retention behaviors of 21 commercially available isomers in synthetic mixture were collected via …

Impact On Infinite Asteroids: Analysis Of Ejecta Outcomes In Small Body Binary Systems, Jennifer Larson

Electronic Theses and Dissertations, 2020-

Binary asteroid systems make up roughly 15% of objects occupying near-Earth space, the Main Belt, and trans-Neptunian space. The impact history of asteroids in binary systems represents an interesting aspect of the general problem pertaining to the nature and evolution of surfaces for such objects. Specifically, the post-impact dynamics of ejecta and its relation to surface modification is a challenging question owing, in part, to the unusual gravitational field in a binary system and the subsequent capture and emplacement of debris on either binary component. Observable differences or similarities between the two bodies in the color, reflectance, thermal properties, and …

From Human Behavior To Machine Behavior, Zerong Xi

Electronic Theses and Dissertations, 2020-

A core pursuit of artificial intelligence is the comprehension of human behavior. Imbuing intelligent agents with a good human behavior model can help them understand how to behave intelligently and interactively in complex situations. Due to the increase in data availability and computational resources, the development of machine learning algorithms for duplicating human cognitive abilities has made rapid progress. To solve difficult scenarios, learning-based methods must search for solutions in a predefined but large space. Along with implementing a smart exploration strategy, the right representation for a task can help narrow the search process during learning. This dissertation tackles three …

Improving Deep Neural Network Training With Knowledge Distillation, Dongdong Wang

Electronic Theses and Dissertations, 2020-

Knowledge distillation, as a popular compression technique, has been widely used to reduce deep neural network (DNN) size for a variety of applications. However, in recent years, some research had found its potential for improving deep neural network performance. This dissertation focuses on further exploring its power to facilitate accurate and reliable DNN training. First, I explored data-efficient method for blackbox knowledge distillation where the specifics of the DNN for distillation is inaccessible. I integrated active learning and mixup to obtain significant distillation performance gain with limited data. This work reveals the competence of knowledge distillation to facilitate large foundation …

Towards Optimization And Robustification Of Data-Driven Models, Ehsan Kazemi Foroushani

Electronic Theses and Dissertations, 2020-

In the past two decades, data-driven models have experienced a renaissance, with notable success achieved through the use of models such as deep neural networks (DNNs) in various applications. However, complete reliance on intelligent machine learning systems is still a distant dream. Nevertheless, the initial success of data-driven approaches presents a promising path for building trustworthy data-oriented models. This thesis aims to take a few steps toward improving the performance of existing data-driven frameworks in both the training and testing phases. Specifically, we focus on several key questions: 1) How to efficiently design optimization methods for learning algorithms that can …

Analysis Of Polycyclic Aromatic Hydrocarbons In Tobacco Related Samples Via High Performance Liquid Chromatography And Laser Excited Time Resolved Shpol' Skii Spectroscopy, Ahmed Comas

Electronic Theses and Dissertations, 2020-

Human exposure to polycyclic aromatic hydrocarbons (PAHs) due to cigarette smoke is well known. It is also known that PAHs are not inherent components of tobacco. Their presence in cigarette smoke results from the curing process of tobacco leaves used for the fabrication of cigarettes and the incomplete combustion of tobacco during the smoking process. The two chromatographic versions of EPA method 610 are popular approaches for the analysis of PAHs in a wide variety of samples. This method, which is based either on High-Performance Liquid-Chromatography (HPLC) or Gas-Chromatography (GC) has shown the presence of Benzo[a]pyrene (B[a]P) in tobacco samples …

Asymptotic Regularity Estimates For Diffusion Processes, David Hernandez

Honors Undergraduate Theses

A fundamental result in the theory of elliptic PDEs shows that the hessian of solutions of uniformly elliptic PDEs belong to the Sobolev space ��^2,ε. New results show that for the right choice of c, the optimal hessain integrability exponent ε* is given by

ε* = ������ ����(1−������) / ����(1−��), �� ∈ (0,1)

Through the techniques of asymptotic analysis, the behavior and properties of this function are better understood to establish improved quantitative estimates for the optimal integrability exponent in the ��^2,ε-regularity theory.

Development Of A Screening Methodology For The Analysis Of Rhodamine B In Foodstuffs, George T. Knecht

Honors Undergraduate Theses

Synthetic dyes that are used as color additives in foodstuffs are regulated by the Food and Drug Administration (FDA) under the Food, Drug, and Cosmetic Act (FD&C). The use of synthetic dyes not approved by the FDA, or the addition of dyes approved by the FDA above their maximum concentration limits in foodstuffs necessarily constitutes illegal food adulteration. Recently, rhodamine B (RhB), a bright-pink synthetic dye not approved for use in foodstuffs, has become an adulterant of interest due to its discovery in a large variety of food samples, and its identity as a potential carcinogen. Numerous chromatographic and spectroscopic …

Compact And High Optical Efficiency Near-Eye Displays With Liquid Crystal Flat Optics, Junyu Zou

Electronic Theses and Dissertations, 2020-

Since the concepts of augmented reality (AR) and virtual reality (VR) were introduced, they have attracted people's attention worldwide, both in the industry and research areas. As the most promising hardware architecture that can bring AR/VR into daily life, near eye displays (NEDs) have been studied and investigated heavily over the past half-century, especially the concept of "Metaverse" introduced by some top companies in recent years. However, the form factor and optical efficiency are two major bottlenecks for the current NEDs before they can become the major platform. Liquid crystal (LC) flat optics have several advantages, including compact, high diffraction …

Physical Properties And Chemical Composition Of Comets, Olga Harrington

Electronic Theses and Dissertations, 2020-

Comets and Centaurs are icy remnants from the formation of the solar system. Analyzing the physical properties of their nuclei and their production rates can serve as powerful tools for tracing primitive solar system material. The four research projects in this dissertation examine these properties in comets and Centaurs. The first project focuses on observations of main belt comet 176P/LINEAR that were obtained with the Kepler space telescope. Optical lightcurves were used to constrain models of the nucleus's spin pole axis, shape and activity level. The second project used millimeter-wavelength spectra from the Arizona Radio Observatory Submillimeter Telescope and infrared …

Automated Machine Learning: Intellient Binning Data Preparation And Regularized Regression Classfier, Jianbin Zhu

Electronic Theses and Dissertations, 2020-

Automated machine learning (AutoML) has become a new trend which is the process of automating the complete pipeline from the raw dataset to the development of machine learning model. It not only can relief data scientists' works but also allows non-experts to finish the jobs without solid knowledge and understanding of statistical inference and machine learning. One limitation of AutoML framework is the data quality differs significantly batch by batch. Consequently, fitted model quality for some batches of data can be very poor due to distribution shift for some numerical predictors. In this dissertation, we develop an intelligent binning to …

Machine Learning Algorithms For Molecular Signature Identification With High-Throughput Genome Sequencing Data, Jiao Sun

Electronic Theses and Dissertations, 2020-

Powered by the high-throughput genomic technologies, the RNA sequencing (RNA-Seq) method is capable of measuring transcriptome-wide mRNA expressions and molecular activities in cells. Elucidation of gene expressions at the isoform resolution enables the detection of better molecular signatures for phenotype prediction, and the identified biomarkers may provide insights into the functional consequences of disease. This dissertation research focuses on developing advanced machine learning algorithms for mining large-scale RNA-Seq data in cancer transcriptome analysis. A platform-integrated model for transcript quantification (IntMTQ) is developed to improve the performance of RNA-Seq on isoform expression estimation. IntMTQ provides more precise RNA-Seq-based isoform quantification, and …

Dormant Propagules In Demographic Studies: A Recurrent Bias And Potential Solutions, Federico Borghesi

Graduate Thesis and Dissertation 2023-2024

In the face of unprecedented anthropogenic change, we increasingly turn to emergent technologies and extensive data sets for solutions that complement much needed systemic changes in our societies. These technological solutions, however, must be approached with care. We must recognize and address biases in the way data has been accumulated. In demographic studies, dormant life stages, such as seed banks, and other cryptic factors have often been neglected. The potential consequences of these omissions have been extensively described in the literature. In the first chapter, I analyze patterns of seed bank omissions in demographic models, finding unjustified omissions are widespread …

Multi-Kilowatt Fiber Laser Amplifiers And Hollow-Core Delivery Fibers, Matthew Cooper

Graduate Thesis and Dissertation 2023-2024

High-power fiber lasers have emerged as a cornerstone in the realm of laser technology. Characterized by their exceptional efficiency, ruggedness, and versatility, fiber lasers are experiencing widespread use in manufacturing, medical, defense, science, and in long range sensing. Unfortunately, high-power applications require strict spatial and spectral performance characteristics to be maintained, which has yet to be perfected.

This dissertation discusses the power scaling of ytterbium-doped fiber laser amplifiers, presenting three significant advancements. First, a novel photonic lantern-based method is introduced for real-time monitoring of laser beam modal content and beam quality. Initial tests highlight the photonic lantern's efficiency in predicting …

A Theoretical Study Of Elementary Processes In Interstellar Plasma, Joshua Forer

Graduate Thesis and Dissertation 2023-2024

Interstellar plasma — interstellar clouds in particular — play an important role in determining the structure and evolution of galaxies. Understanding the time evolution of such plasmas requires knowledge of the chemical processes that drive their dynamics. Two processes are studied in this dissertation: radiative electron attachment (REA) via dipole-bound states (DBSs) and dissociative recombination (DR). Of the several hundred molecules detected in the interstellar medium, only eight anions have been detected: CN-, C3N-, C5N-, C7N-, C4H-, C6H-, C8H-, and C10H-. Their production mechanism is not well known; REA was suggested as a possible formation pathway, but previous theoretical studies …

Deep Learning Approaches For Automatic Colorization, Super-Resolution, And Representation Of Volumetric Data, Sudarshan Devkota

Graduate Thesis and Dissertation 2023-2024

This dissertation includes a collection of studies that aim to improve the way we represent and visualize volume data. The advancement of medical imaging has revolutionized healthcare, providing crucial anatomical insights for accurate diagnosis and treatment planning. Our first study introduces an innovative technique to enhance the utility of medical images, transitioning from monochromatic scans to vivid 3D representations. It presents a framework for reference-based automatic color transfer, establishing deep semantic correspondences between a colored reference image and grayscale medical scans. This methodology extends to volumetric rendering, eliminating the need for manual intervention in parameter tuning. Next, it delves into …

Low Energy Photon Detection, Tianyi Guo

Graduate Thesis and Dissertation 2023-2024

Detecting long wave infrared (LWIR) light at room temperature has posed a persistent challenge due to the low energy of photons. The pursuit of an affordable, high-performance LWIR camera capable of room temperature detection has spanned several decades. In the realm of contemporary LWIR detectors, they can be broadly classified into two categories: cooled and uncooled detectors. Cooled detectors, such as MCT detectors, excel in terms of high detectivity and fast response times. However, their reliance on cryogenic cooling significantly escalates their cost and restricts their practical applications. In contrast, uncooled detectors, exemplified by microbolometers, are capable of functioning at …

A Systematic Review Of Cryptocurrencies Use In Cybercrimes, Kieran B D Human

Graduate Thesis and Dissertation 2023-2024

Cryptocurrencies are one of the most prominent applications of blockchain systems. While cryptocurrencies promise many features and advantages, such as decentralization, anonymity, and ease of access, those very features can be abused. For instance, as documented in various recent works, cryptocurrencies have been frequently abused in many different forms of cybercrime. Despite the plethora of works on measuring and understanding the abuse of cryptocurrencies in the digital space, there has been no work on systemizing this knowledge by comprehensively understanding those contributions, contrasting them based on their merit, and understanding the gap in this research space.

This thesis initiates the …

Material Appearance Modeling For Physically Based Rendering, Alexis Benamira

Graduate Thesis and Dissertation 2023-2024

Photorealistic rendering focuses on creating images with a computer that imitates pictures of reallife scenes as faithfully as possible. To achieve this, rendering algorithms require incorporating accurate modeling of how light interacts with various types of matter. For most objects, this model needs to account for the scattering of the light rays. However, this model falls short when rendering objects of sizes smaller or comparable to the wavelength of the incident light. In this case, new phenomena such as diffraction or interference are observed and have been characterized in optics. Digital rendering of those phenomena involve different light representations than …

Exploring The Feasibility Of Machine Learning Techniques In Recognizing Complex Human Activities, Shengnan Hu

Graduate Thesis and Dissertation 2023-2024

This dissertation introduces several technical innovations that improve the ability of machine learning models to recognize a wide range of complex human activities. As human sensor data becomes more abundant, the need to develop algorithms for understanding and interpreting complex human actions has become increasingly important. Our research focuses on three key areas: multi-agent activity recognition, multi-person pose estimation, and multimodal fusion.

To tackle the problem of monitoring coordinated team activities from spatio-temporal traces, we introduce a new framework that incorporates field of view data to predict team performance. Our framework uses Spatial Temporal Graph Convolutional Networks (ST-GCN) and recurrent …

Optical Characterization Of Liquids: Refractive Index And Raman Gain Coefficient Measurements, Cesar A. Lopez-Zelaya

Graduate Thesis and Dissertation 2023-2024

Novel technologies capable of generating wavelengths not accessible with typical laser gain media have been among the primary drivers of the field of nonlinear optics. Here, we are interested in the linear and nonlinear properties of liquids beyond the visible spectrum, motivated in part by their use as core materials in optical fibers. Given their dispersion, nonlinearities, transparency, and ability to be mixed, liquids show potential for exploiting in-fiber nonlinear phenomena for developing the new generation of low cost, size, weight, and power wavelength-agile fiber-laser sources. For the design, modeling, and experimental realization of these liquid-core fiber laser sources, proper …

Exploring A Lab-Scale Cascade Upflow Bioreactor System For Nitrogen Removal Via Biosorption Activated Media, Alejandra Robles Lecompte

Graduate Thesis and Dissertation 2023-2024

Many Best Management Practices (BMPs) have been developed to reduce excessive nutrients in stormwater runoff and mitigate harmful algal blooms in downstream receiving water bodies. This study demonstrates a new BMP by comparing two green sorption media (i.e., specialty adsorbents) for nutrient removal in cascade upflow biofiltration systems operated in parallel. The proposed filtration technology can control hydraulic gradients, prevent clogging and settlements, and increase hydraulic loading while removing more nutrients in an integrated physicochemical and microbiological treatment process. The two green sorption media being tested in this study include zero-valent-iron and perlite-based green sorption media (ZIPGEM) and biochar, iron, …

Optimizing Deep Neural Networks Performance: Efficient Techniques For Training And Inference, Ankit Sharma

Graduate Thesis and Dissertation 2023-2024

Recent advances in computer vision tasks are mainly due to the success of large deep neural networks. The current state-of-the-art models have high computational costs during inference and suffer from a high memory footprint. Therefore, deploying these large networks on edge devices remains a serious concern. Furthermore, training these over-parameterized networks is computationally expensive and requires a longer training time. Thus, there is a demand to develop techniques that can efficiently reduce training costs and also be able to deploy neural networks on mobile and embedded devices. This dissertation presents practices like designing a lightweight network architecture and increasing network …

Dna Capture And Translocation Through Nanopore, Swarnadeep Seth

Graduate Thesis and Dissertation 2023-2024

This thesis investigates DNA dynamics and translocation through nanopores using Brownian dynamics (BD) simulations, offering insights into sequencing technologies, DNA marker detection, and accurate barcoding utilizing solid-state nanopore platforms. First, we in silico study the intricate process of capture and translocation in a single nanopore. Our simulation reveals a high probability of hairpin loop formation during the capture process. However, attaching a charged tag to one end of DNA improves multi-scan rates and enhances unidirectional translocations. We use modulating voltage biases to multi-scan a lambda-phage dsDNA with oligonucleotide flap markers (tags) through a single and double nanopore system. Our study …

Reconstructing 3d Humans From Visual Data, Ce Zheng

Graduate Thesis and Dissertation 2023-2024

Understanding humans in visual content is fundamental for numerous computer vision applications. Extensive research has been conducted in the field of human pose estimation (HPE) to accurately locate joints and construct body representations from images and videos. Expanding on HPE, human mesh recovery (HMR) addresses the more complex task of estimating the 3D pose and shape of the entire human body. HPE and HMR have gained significant attention due to their applications in areas such as digital human avatar modeling, AI coaching, and virtual reality [135]. However, HPE and HMR come with notable challenges, including intricate body articulation, occlusion, depth …

Towards A Robust And Efficient Deep Neural Network For The Lidar Point Cloud Perception, Zixiang Zhou

Graduate Thesis and Dissertation 2023-2024

In recent years, LiDAR has emerged as a crucial perception tool for robotics and autonomous vehicles. However, most LiDAR perception methods are adapted from 2D image-based deep learning methods, which are not well-suited to the unique geometric structure of LiDAR point cloud data. This domain gap poses challenges for the fast-growing LiDAR perception tasks. This dissertation aims to investigate suitable deep network structures tailored for LiDAR point cloud data, and therefore design a more efficient and robust LiDAR perception framework. Our approach to address this challenge is twofold. First, we recognize that LiDAR point cloud data is characterized by an …

Towards A Holistic And Comparative Analysis Of The Free Content Web: Security, Privacy, And Performance, Abdulrahman Alabduljabbar

Electronic Theses and Dissertations, 2020-

Free content websites that provide free books, music, games, movies, etc., have existed on the Internet for many years. While it is a common belief that such websites might be different from premium websites providing the same content types in terms of their security, a rigorous analysis that supports this belief is lacking from the literature. In particular, it is unclear if those websites are as safe as their premium counterparts. In this dissertation, we set out to investigate the similarities and differences between free content and premium websites, including their risk profiles. Moreover, we analyze and quantify through measurements …

Using Wastewater-Based Epidemiology To Study Chlamydia Occurrence On A College Campus, Jessie E. Chin Quee

Honors Undergraduate Theses

Chlamydia is a sexually transmitted disease caused by Chlamydia trachomatis, commonly affecting sexually active college-aged adults. Presently, opportunistic testing, self-testing, and information campaigns are methods to screen vulnerable populations and raise awareness about chlamydia. Chlamydia remains underdiagnosed and undertested due to a lack of participation by individuals who may have been exposed to it. Wastewater-based epidemiology is a rising biomonitoring tool that detects the presence of disease- and drug-specific biomarkers in a community's wastewater. In this study, wastewater-based epidemiology was used to detect the presence of C. trachomatis on the University of Central Florida campus. Wastewater samples were collected …

Understanding The Pressure-Sinkage Relationship For Simulated Lunar Regolith And Implications On Bearing Capacity And Trafficability, Catherine A. Millwater

Honors Undergraduate Theses

The intent of this thesis is to explore the pressure-sinkage relationship for simulated lunar regolith (simulant). The simulants used in this experiment emulate the lunar highlands (LHS-1) and the lunar mare (LMS-1). The ultimate ability of a terrain or regolith to support a load without shear failure is vital to the planning and construction of permanent infrastructure. This relationship can be measured by applying a normal load to the regolith until shear failure, from which allowable and ultimate bearing capacity can be deduced. An understanding of the pressure-sinkage of lighter loads on the higher ‘fluffy' layer of regolith is of …

Observation Of Gapless Nodal-Lines In A Rare-Earth-Based Compound, Robert Smith

Honors Undergraduate Theses

This thesis aims to contribute to the understanding of quantum materials by employing a combination of experimental techniques, such as angle-resolved photoemission spectroscopy and magnetic and transport measurements. Further collaborative support in the form of first-principles calculations is included and discussed in tandem. In this thesis, a lanthanide-based semimetal of the ZrSiS type, is investigated. Multiple nodal lines which remain gapless are observed along the X-R direction of the Brillouin zone. We also present a nodal line that is observed further below the Fermi level and aligned in the G-M direction; this nodal line appears to be sensitive to light …