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Articles 16681 - 16710 of 18310
Full-Text Articles in Physical Sciences and Mathematics
An Assessment Of Scientific Claim Verification Frameworks: Final Presentation, Ethan Landers, Jian Wu (Mentor)
An Assessment Of Scientific Claim Verification Frameworks: Final Presentation, Ethan Landers, Jian Wu (Mentor)
Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics
No abstract provided.
Variability And Dynamics Of Along‐Shore Exchange On The West Antarctic Peninsula (Wap) Continental Shelf, Xin Wang, Carlos Moffat, Michael S. Dinniman, John M. Klinck, David A. Sutherland, Borja Aguiar-Gonzáles
Variability And Dynamics Of Along‐Shore Exchange On The West Antarctic Peninsula (Wap) Continental Shelf, Xin Wang, Carlos Moffat, Michael S. Dinniman, John M. Klinck, David A. Sutherland, Borja Aguiar-Gonzáles
CCPO Publications
The continental shelf of the West Antarctic Peninsula (WAP) is characterized by strong along-shore hydrographic gradients resulting from the distinct influences of the warm Bellingshausen Sea to the south and the cold Weddell Sea water flooding Bransfield Strait to the north. These gradients modulate the spatial structure of glacier retreat and are correlated with other physical and biochemical variability along the shelf, but their structure and dynamics remain poorly understood. Here, the magnitude, spatial structure, seasonal-to-interannual variability, and driving mechanisms of along-shore exchange are investigated using the output of a high-resolution numerical model and with hydrographic data collected in Palmer …
Machine Learning In Fiber Optics, Xiaowen Hu
Machine Learning In Fiber Optics, Xiaowen Hu
Electronic Theses and Dissertations, 2020-2023
Recent burgeoning machine learning has revolutionized our ways of looking at the world. Being extraordinarily good at pattern recognition, machine learning has been widely applied to many fields to solve challenging problems. This dissertation demonstrates the applications of machine learning on scanning-free fiber-optic imaging systems (FOISs), and on the design of anti-resonant fibers. In the first part, we propose a semi-supervised learning framework called the adaptive inverse mapping (AIP) to stabilize the imaging performance through multimode fibers (MMFs). We show that if the state of the MMF is traced closely, the output images can be used as probes to correct …
Control Of Coherence In Attosecond Atomic Ionization, Saad Mehmood
Control Of Coherence In Attosecond Atomic Ionization, Saad Mehmood
Electronic Theses and Dissertations, 2020-2023
The motion of electrons in atoms, molecules, and in condensed matter unfolds on a time scale from the attosecond (1 as = 10-18 s) to several femtoseconds (1 fs= 10-15 s). The advent of attosecond light pulses has opened the way to the time-resolved study of electronic motion and of ionization processes using pump-probe spectroscopy. In this thesis, we examine three aspects of the ionization dynamics in poly-electronic atoms: i) the coherence of the emerging charged fragments, ii) two-photon ionization pathways, and iii) the reconstruction of photoionization amplitudes from experimental observable. We focus on the role of autoionizing states and …
Uncooled Microbolometer Imaging Systems For Machine Vision, Robert Grimming
Uncooled Microbolometer Imaging Systems For Machine Vision, Robert Grimming
Electronic Theses and Dissertations, 2020-2023
Over the last 20 years, the cost of uncooled microbolometer-based imaging systems has drastically decreased while performance has increased. In the simplest terms, the figure of merit for these types of thermal detectors is given in terms of the τ-NETD product, the combination of the thermal time constant and the noise equivalent temperature difference. Considering these factors, optimal system design parameters are investigated to maximize visual information content. This dissertation focuses on improving scene information in the longwave infrared (LWIR) spectrum that has had its validity and quality degraded by noise, blur, and reflected radiance. Taken together, noise and blur …
Identifying Challenges And Opportunities For Designing Social Media Nudges For Adolescents, Oluwatomisin Obajemu
Identifying Challenges And Opportunities For Designing Social Media Nudges For Adolescents, Oluwatomisin Obajemu
Electronic Theses and Dissertations, 2020-2023
With the prevalence of online risks encountered by youth online, strength-based approaches such as nudges have been recommended as a potential solution to subtly guide teens toward safer decisions. However, most nudging interventions to date have not been designed to cater to teens’ unique needs and online safety concerns. To address this gap, this study aimed to better understand adolescents’ perceptions and feedback on online safety nudges to inform the design of more effective online safety interventions. We conducted 12 semi-structured interviews and 3 focus group sessions with 21 teens (13 – 17 years old) to get their feedback on …
Algorithms For The Detection Of Resolved And Unresolved Targets In The Infrared Bands, Bruce Mcintosh
Algorithms For The Detection Of Resolved And Unresolved Targets In The Infrared Bands, Bruce Mcintosh
Electronic Theses and Dissertations, 2020-2023
This dissertation proposes algorithms for the detection of both resolved and unresolved targets in the infrared bands. Recent breakthroughs in deep learning have spurred major advancements in computer vision, but most of the attention and progress has been focused on RGB imagery from the visual band. The infrared bands such as Long Wave Infrared (LWIR), Medium Wave Infrared (MWIR), Short Wave Infrared (SWIR) and Near Infrared (NIR) each respond differently to physical phenomena, providing information that can be used to better understand the environment. The first task addressed is that of detecting vehicles in heavy clutter in MWIR imagery. A …
Testing The Influence Of Water Depth In Design Of Created Oyster Reef For Living Shoreline Applications, Peter Vien
Testing The Influence Of Water Depth In Design Of Created Oyster Reef For Living Shoreline Applications, Peter Vien
Electronic Theses and Dissertations, 2020-2023
Living shoreline stabilization has become a popular practice in shoreline restoration and bank protection; however, there are still many uncertainties regarding effective site design using living materials. For example, natural wave-breaks may be formed of created reefs, but the optimum water depth for hydrodynamic influence may differ from the preferred depth to ensure organism recruitment. The objective of this research is to understand how water depth relative to the crest of submerged artificial oyster reef structures influences nearshore hydrodynamic processes and sediment transport or retention in nearshore areas. A field study, sited in a microtidal estuary on the Atlantic coast …
Visual Question Answering: Exploring Trade-Offs Between Task Accuracy And Explainability, Aisha Urooj
Visual Question Answering: Exploring Trade-Offs Between Task Accuracy And Explainability, Aisha Urooj
Electronic Theses and Dissertations, 2020-2023
Given visual input and a natural language question about it, the visual question answering (VQA) task is to answer the question correctly. To improve a system's reliability and trustworthiness, it is imperative that it links the text (question and answer) to specific visual regions. This dissertation first explores the VQA task in a multi-modal setting where questions are based on video as well as subtitles. An algorithm is introduced to process each modality and their features are fused to solve the task. Additionally, to understand the model's emphasis on visual data, this study collects a diagnostic set of questions which …
Analysis And Characterization Of Smokeless Powders And Smokeless Powder Residues, Emily Lennert
Analysis And Characterization Of Smokeless Powders And Smokeless Powder Residues, Emily Lennert
Electronic Theses and Dissertations, 2020-2023
The ability to associate a smokeless powder, smokeless powder residue, or organic gunshot residue (OGSR) to one another may be helpful in determining the origin of a suspected sample and aid in linking a suspect to a crime scene. In this study, smokeless powders were extracted and analyzed via gas chromatography – mass spectrometry (GC-MS) and direct analysis in real time – high resolution mass spectrometry (DART-HRMS). Subsequently, group definition was performed using hierarchical cluster analysis and principal component analysis followed by internally validated classification models. Then, smokeless powder residues were generated in-lab and extracted. Resulting residue data from each …
Characterizing The Particle Size Distribution In Saturn's Rings Using Cassini Uvis Stellar Occultation Data, Stephanie Eckert
Characterizing The Particle Size Distribution In Saturn's Rings Using Cassini Uvis Stellar Occultation Data, Stephanie Eckert
Electronic Theses and Dissertations, 2020-2023
NASA's Cassini mission to Saturn revolutionized modern understanding of the planet's vast and intricate ring system. We use stellar occultation data from Cassini's UVIS High Speed Photometer (HSP) to characterize the particle size distribution in the rings with two methods. First, we discern the sizes of the smallest particles at ring edges by forward-modeling observed diffraction signatures which appear as spikes in the signal, the shape and amplitude of which depends on the size and abundance of the smallest particles. We then probe the upper end of the size distribution using occultation statistics. Although the distribution of photon counts in …
Leveraging Human-Centered Insights And Vision Transformers To Understand And Detect Online Risks In Teens' Private Social Media Conversations On Instagram, Joshua Gracie
Electronic Theses and Dissertations, 2020-2023
With the growing ubiquity of the internet and internet enabled devices, the issue of online risk and the need for safety measures against such risks has grown paramount. Many researchers have analyzed the scope and characteristics of online risk, especially with respect to demographics, yet few have studied the risky media itself. This work sets out to move the conversation from surveys and interviews to content analysis and automation through a comprehensive thematic analysis of online multi-media risks (images and videos) sent to and from teens in private messages on Instagram. These messages, along with demographic information such as age …
Deep Learning Anomaly Detection Using Edge Ai, William Holdren
Deep Learning Anomaly Detection Using Edge Ai, William Holdren
Electronic Theses and Dissertations, 2020-2023
Deep learning anomaly detection is an evolving field with many real-world applications. As more and more devices continue to be added to the Internet of Things (IoT), there is an increasing desire to make use of the additional computational capacity to run demanding tasks. The increase in devices and amounts of data flooding in have led to a greater need for security and outlier detection. Motivated by those facts, this thesis studies the potential of creating a distributed anomaly detection framework. While there have been vast amounts of research into deep anomaly detection, there has been no research into building …
Multivariate Cognitive Walkthrough Of Qubitvr: An Educational Quantum Computing, Virtual Reality Application, Pauline Johnson
Multivariate Cognitive Walkthrough Of Qubitvr: An Educational Quantum Computing, Virtual Reality Application, Pauline Johnson
Electronic Theses and Dissertations, 2020-2023
Quantum computing is a promising field but understanding how it works can be challenging for a beginner. There are also not many educational resources to visualize and learn about quantum computing. To advance knowledge in this area, we have created QubitVR, which employs a Bloch sphere representation of a qubit, and supports trajectory visualizations and state equations in a virtual reality (VR) setting. We also conducted a multivariate cognitive walkthrough with subject matter experts (SMEs) on QubitVR to assess the effectiveness of trajectory visualizations and state equations in learning about quantum gates. The results were that trajectory visualizations aided users …
Cholera Transmission Dynamic Model With Environmental Impacts Of Plankton Reservoirs, Sweety Sarker
Cholera Transmission Dynamic Model With Environmental Impacts Of Plankton Reservoirs, Sweety Sarker
Electronic Theses and Dissertations, 2020-2023
Cholera is an acute disease that is a global threat to the world and can kill people within a few hours if left untreated. In the last 200 years, seven pandemics occurred, and, in some countries, it remains endemic. The World Health Organization (WHO) declared a global initiative to prevent cholera by 2030. Cholera dynamics are contributed by several environmental factors such as salinity level of water, water temperature, presence of plankton especially zooplankton such as cladocerans, rotifers, copepods, etc. Vibrio cholerae (V. cholerae) bacterium is the main reason behind the cholera disease and the growth of V. cholerae depends …
Light Trapping Transparent Electrodes, Mengdi Sun
Light Trapping Transparent Electrodes, Mengdi Sun
Electronic Theses and Dissertations, 2020-2023
Transparent electrodes represent a critical component in a wide range of optoelectronic devices such as high-speed photodetectors and solar cells. Fundamentally, the presence of any conductive structures in the optical path leads to dissipation and reflection, which adversely affects device performance. Many different approaches have been attempted to minimize such shadowing losses, including the use of transparent conductive oxides (TCOs), metallic nanowire mesh grids, graphene-based contacts, and high-aspect ratio metallic wire arrays. In this dissertation I discuss a conceptually different approach to achieve transparent electrodes, which involves recapturing photons initially reflected by highly conductive electrode lines. To achieve this, light-redirecting …
Electronic And Optoelectronic Properties Of Two-Dimensional Heterostructures For Next-Generation Device Technologies, Jesse Thompson
Electronic And Optoelectronic Properties Of Two-Dimensional Heterostructures For Next-Generation Device Technologies, Jesse Thompson
Electronic Theses and Dissertations, 2020-2023
Since monolayer graphene was isolated in 2004, there has been significant interest in integrating layered materials into innovative device designs and hybrid materials to help solve pressing technological challenges. This is partially because they can typically be thinned to a two-dimensional (2D) form without suffering from roughness-induced scattering and can exhibit thickness-dependent variations in properties such as their energy band gap. This dissertation reports on investigations of electronic and optoelectronic device physics in 2D material heterostructures. The investigation of electronic device physics focuses on the interface between 2D molybdenum disulfide (MoS2) and gold (Au), which behaves as a resistive switching …
Patterned Liquid Crystal Devices For Near-Eye Displays, Kun Yin
Patterned Liquid Crystal Devices For Near-Eye Displays, Kun Yin
Electronic Theses and Dissertations, 2020-2023
As a promising next-generation display, augmented reality (AR) and virtual reality (VR) have shown attractive features and attracted broad interests from both academia and industry. Currently, these near-eye displays (NEDs) have enabled numerous applications, ranging from education, medical, entertainment, to engineering, with the help of compact and functional patterned liquid crystal (LC) devices. The interplay between LC patterns and NEDs stimulates the development of novel LC devices with unique surface alignments and volume structures, which in turn feedback to achieve more compact and versatile NEDs. This dissertation will focus on the patterned LC with applications in NEDs. Firstly, we propose …
Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong
Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong
Electronic Theses and Dissertations, 2020-2023
Liquid crystal planar optics (LCPO) with versatile functionalities is emerging as a promising candidate for overcoming various challenges in near-eye displays, like augmented reality (AR) and virtual reality (VR), while maintaining a small form factor. This type of novel optical element exhibits unique properties, such as high efficiency, large angular/spectral bandwidths, polarization selectivity, and dynamic modulation. The basic molecular configuration of these novel reflective LCPO is analyzed, based on the simulation of molecular dynamics. In contrast to previously assumed planar-twist structure, our analysis predicts a slanted helix structure, which agrees with the measured results. The optical simulation model is established …
Polymer Derived Ceramic For Lithium-Ion Storage, And Electrospun Polyelectrolyte Fiber For Heavy Metal Ions Removal, Zeyang Zhang
Polymer Derived Ceramic For Lithium-Ion Storage, And Electrospun Polyelectrolyte Fiber For Heavy Metal Ions Removal, Zeyang Zhang
Electronic Theses and Dissertations, 2020-2023
This dissertation includes two major projects. The first project investigated the great potential of polymer-derived ceramics (PDCs) as lithium-ion battery anode materials with good cycling stability and large capacity. SiCNO ceramic nanoparticles were produced by pyrolysis of polysilazane nanoparticles synthesized via an oil-in-oil emulsion crosslinking. The SiCNO nanoparticles had an average particle size of around 9 nm and contained graphitic carbon, Si3N4, and SiO2 domains. The electrochemical behavior of SiCNO nanoparticles anode was investigated to evaluate the Li-ion storage performance and understand its mechanism of Li-ion storage. The lithiation of SiCNO was observed at ~0.385 V versus Li/Li+. The anode …
Function Approximation Guarantees For A Shallow Neural Network Trained By Gradient Flow, Russell Gentile
Function Approximation Guarantees For A Shallow Neural Network Trained By Gradient Flow, Russell Gentile
Electronic Theses and Dissertations, 2020-2023
This work features an original result linking approximation and optimization theory for deep learning. Several examples from recent literature show that, given the same number of learnable parameters, deep neural networks can approximate richer classes of functions, with better accuracy than classical methods. The bulk of approximation theory results though, are only concerned with the infimum error for all possible parameterizations of a given network size. Their proofs often rely on hand-crafted networks, where the weights and biases are carefully selected. Optimization theory indicates that such models would be difficult or impossible to realize with standard gradient-based training methods. The …
First And Third Order Susceptibility Of Organic Molecules, Hao-Jung Chang
First And Third Order Susceptibility Of Organic Molecules, Hao-Jung Chang
Electronic Theses and Dissertations, 2020-2023
Illuminating a material with intense laser excitation may change its properties and result in nonlinear absorption (NLA) and nonlinear refraction (NLR). In this dissertation we study the nonlinear absorption of organic compounds, the effect of extremely nondegenerate NLR in semiconductors, and the linear refractive index of organic solvents. In liquids, the refractive index has been studied for decades and different kinds of refractometers have been proposed. However, most of the reported values are in the visible region and only for commonly used solvents. We proposed a new interferometer-based refractometer that allows us to measure the refractive index from the visible …
An Analysis Of Associations Between Polarimetric Supercell Signatures, Erik Green
An Analysis Of Associations Between Polarimetric Supercell Signatures, Erik Green
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
Supercell thunderstorms produce unique polarimetric radar signatures that are not often observed in unorganized deep convection. Repetitive signatures include deep and persistent differential reflectivity (ZDR) columns and the ZDR arc signature, which are both indicative of thermodynamic and microphysical processes intrinsic to supercells. Prior investigations of supercell polarimetric signatures, both those observed by operational and research radars, and those simulated numerically, reveal positive correlations between the ZDR column depth and cross-sectional area and quantitative characteristics of the radar reflectivity field. This study expands upon prior work by incorporating a dataset of discrete, right moving supercells …
2022 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University
2022 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University
Tennessee Climate Office Monthly Report
No abstract provided.
2021 - Tennessee Annual Climate Summary, Tennessee Climate Office, East Tennessee State University
2021 - Tennessee Annual Climate Summary, Tennessee Climate Office, East Tennessee State University
Tennessee Climate Office Monthly Report
No abstract provided.
Investigaion Of The Gamma Hurdle Model For A Single Population Mean, Alissa Jacobs
Investigaion Of The Gamma Hurdle Model For A Single Population Mean, Alissa Jacobs
Electronic Theses and Dissertations
A common issue in some statistical inference problems is dealing with a high frequency of zeroes in a sample of data. For many distributions such as the gamma, optimal inference procedures do not allow for zeroes to be present. In practice, however, it is natural to observe real data sets where nonnegative distributions would make sense to model but naturally zeroes will occur. One example of this is in the analysis of cost in insurance claim studies. One common approach to deal with the presence of zeroes is using a hurdle model. Most literary work on hurdle models will focus …
Molecular Dynamics On Quantum Annealers, Igor Gaidai, Dmitri Babikov, Alexander Teplukhin, Brian K. Kendrick, Susan M. Mniszewski, Yu Zhang, Sergei Tretiak, Pavel A. Dub
Molecular Dynamics On Quantum Annealers, Igor Gaidai, Dmitri Babikov, Alexander Teplukhin, Brian K. Kendrick, Susan M. Mniszewski, Yu Zhang, Sergei Tretiak, Pavel A. Dub
Chemistry Faculty Research and Publications
In this work we demonstrate a practical prospect of using quantum annealers for simulation of molecular dynamics. A methodology developed for this goal, dubbed Quantum Differential Equations (QDE), is applied to propagate classical trajectories for the vibration of the hydrogen molecule in several regimes: nearly harmonic, highly anharmonic, and dissociative motion. The results obtained using the D-Wave 2000Q quantum annealer are all consistent and quickly converge to the analytical reference solution. Several alternative strategies for such calculations are explored and it was found that the most accurate results and the best efficiency are obtained by combining the quantum annealer with …
Estimating Weighted Panel Sizes For Primary Care Providers: An Assessment Of Clustering And Novel Methods Of Panel Size Estimation On Electronic Medical Records, Martin A. Lavallee
Estimating Weighted Panel Sizes For Primary Care Providers: An Assessment Of Clustering And Novel Methods Of Panel Size Estimation On Electronic Medical Records, Martin A. Lavallee
Theses and Dissertations
Primary Care is on the frontlines of healthcare, thus they see the most diverse set of patients. In order to achieve high functioning primary care, a practice must establish empanelment, the pairing of patients to providers. Enumeration of empanelment, or estimating panel sizes, helps ensure that the demands of the patients demand the supply of providers and optimize the balance of primary care resources to improve quality of care. Further we can adjust panel sizes by using patient-level data on healthcare utilization and complexity extracted from the electronic medial record to determine the amount of care or burden of work …
Multi-Modality Automatic Lung Tumor Segmentation Method Using Deep Learning And Radiomics, Siqiu Wang
Multi-Modality Automatic Lung Tumor Segmentation Method Using Deep Learning And Radiomics, Siqiu Wang
Theses and Dissertations
Delineation of the tumor volume is the initial and fundamental step in the radiotherapy planning process. The current clinical practice of manual delineation is time-consuming and suffers from observer variability. This work seeks to develop an effective automatic framework to produce clinically usable lung tumor segmentations. First, to facilitate the development and validation of our methodology, an expansive database of planning CTs, diagnostic PETs, and manual tumor segmentations was curated, and an image registration and preprocessing pipeline was established. Then a deep learning neural network was constructed and optimized to utilize dual-modality PET and CT images for lung tumor segmentation. …
Universal Design In Bci: Deep Learning Approaches For Adaptive Speech Brain-Computer Interfaces, Srdjan Lesaja
Universal Design In Bci: Deep Learning Approaches For Adaptive Speech Brain-Computer Interfaces, Srdjan Lesaja
Theses and Dissertations
In the last two decades, there have been many breakthrough advancements in non-invasive and invasive brain-computer interface (BCI) systems. However, the majority of BCI model designs still follow a paradigm whereby neural signals are preprocessed and task-related features extracted using static, and generally customized, data-independent designs. Such BCI designs commonly optimize narrow task performance over generalizability, adaptability, and robustness, which is not well suited to meeting individual user needs. If one day BCIs are to be capable of decoding our higher-order cognitive commands and conceptual maps, their designs will need to be adaptive architectures that will evolve and grow in …