Physical Sciences and Mathematics Commons^™

Kernel Estimation Of Spot Volatility And Its Application In Volatility Functional Estimation, Bei Wu

Arts & Sciences Graduate Student Theses and Dissertations

It\^o semimartingale models for the dynamics of asset returns have been widely studied in financial econometrics. A key component of the model, spot volatility, plays a crucial role in option pricing, portfolio management, and financial risk assessment. In this dissertation, we consider three problems related to the estimation of spot volatility using high-frequency asset returns. We first revisit the problem of estimating the spot volatility of an It\^o semimartingale using a kernel estimator. We prove a Central Limit Theorem with an optimal convergence rate for a general two-sided kernel under quite mild assumptions, which includes leverage effects and jumps of …

Geometry And Dynamics Of Rolling Systems, Bowei Zhao

Arts & Sciences Graduate Student Theses and Dissertations

Billiard systems, broadly speaking, may be regarded as models of mechanical systems in which rigid parts interact through elastic impulsive collision forces. When it is desired or necessary to account for linear/angular momentum exchange in collisions involving a spherical body, a type of billiard system often referred to as no-slip has been used. Previous work indicated that no-slip billiards resemble non-holonomic systems, specifically, systems consisting of a ball rolling on surface. In prior research, such connections were only observed numerically and were restricted to very special surfaces. In this thesis, it is shown that no-slip billiard and rolling systems are …

Federated Learning And Applications In Cybersecurity, Ani Sreekumar

Cybersecurity Undergraduate Research Showcase

Machine learning is a subfield of artificial intelligence that focuses on making predictions about some outcome based on information from a dataset. In cybersecurity, machine learning is often used to improve intrusion detection systems and identify trends in data that could indicate an oncoming cyber attack. Data privacy is an extremely important aspect of cybersecurity, and there are many industries that have more demanding laws to ensure the security of user data. Due to these regulations, machine learning algorithms can not be widely utilized in these industries to improve outcomes and accuracy of predictions. However, federated learning is a recent …

2022 December 15 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Covid-19 Prediction Using Machine Learning, Parashuram Singaraveni

Masters Projects

All around the globe, humankind faces a disastrous situation that witnessed COVID-19 outbreak. The COVID-19 pandemic caused severe loss of human life across the world. Most of the countries had been socially and economically weakened. The health sector faced lots of challenges in diagnosing the COVID patients, vaccinating the people, identifying the people who are infected by the virus. At the earlier stage, it has been difficult to identify the symptoms in infected person that is caused by the virus. Months later, symptoms were identified and, disease detecting machines were invented. But still, time taking for the results from the …

Curriculum Development In Technical Education For Boys And Girls Club, Damanpreet Singh

Masters Projects

Technical education has been and will continue to be more and more important to succeed in the future. The Boys and Girls Club, founded in 1860, is a national organization of local chapters which provide voluntary after-school programs for young individuals. The Boys and Girls Club have life-changing programs that prepare the young individuals in the club for their future whether it’s for college, career, or life. The perfect way to prepare best prepare these kids for the future is to develop their technical education. Unfortunately, the boys and girls club of Muskegon has a lack of educational resources for …

College Job Portal, Harikrishna Gonuguntla

Masters Projects

Through this project, I am producing a portal called "College Job Portal" that will make life easier for students, colleges, and the companies who hire the students by handling the hiring process. On-campus job placements are a crucial component in contemporary educational institutions. By entering information about their educational history, grades, technological abilities, and CV, students would register with the portal. Like students, companies would sign up with the site by supplying basic details like their address and contact information for human resources. The college would be the portal's administrator. Companies can advertise job openings using this site by including …

Malware Detection And Analysis, Namratha Suraneni

Masters Projects

Malicious software poses a serious threat to the cybersecurity of network infrastructures and is a global pandemic in the form of computer viruses, Trojan horses, and Internet worms. Studies imply that the effects of malware are deteriorating. The main defense against malware is malware detectors. The methods that such a detector employ define its level of quality. Therefore, it is crucial that we research malware detection methods and comprehend their advantages and disadvantages. Attackers are creating malware that is polymorphic and metamorphic and has the capacity to modify their source code as they spread. Furthermore, existing defenses, which often utilize …

Full-Text Search Using Elasticsearch, Akash Shrestha

Masters Projects

Search engines have changed the way we use the internet. They can search or filter out relevant and valuable content of interest to the users. But many of the applications we use today lack search or are just poor. So how can we leverage the same power of search engines in our applications? This project aims to look at “Full-Text Search” which allows us to do a text-based search in text-intensive data. The search will be performed by matching any, or all words of the query exactly or with some relevancy against the indexes created by the searching tool. The …

Docker Container Image – Vulnerability Scanning, Joseph U. Ohaeche

Masters Projects

The technology landscape for container adoption has greatly evolved over the years from the first known Unix U7 container concept introduced in 1979 to the most utilized docker container concept which emerged in 2013. Docker container image is essentially a lightweight, standalone executable software package with capabilities to run an application. It is important to know that container images become containers when deployed, and simultaneously docker container images become docker containers when deployed on Docker Engine. This project paper aims, evaluates, and presents a methodology useful in vulnerability scanning of docker container images and suggests possible fixes based on OWASP …

Dealing With Dimensionality: Problems And Techniques In High-Dimensional Statistics, Cezareo Rodriguez

Arts & Sciences Graduate Student Theses and Dissertations

In modern data analysis, problems involving high dimensional data with more variables than subjects is increasingly common. Two such cases are mediation analysis and distributed optimization. In Chapter 2 we start with an overview of high dimensional statistics and mediation analysis. In Chapter 3 we motivate and prove properties for a new marginal screening procedure for performing high dimensional mediation analysis. This screening procedure is shown via simulation to perform better than benchmark approaches and is applied to a DNA methylation study. In Chapter 4 we construct a cryptosystem that accurately performs distributed penalized quantile regression in the high-dimensional setting …

Contribution To Data Science: Time Series, Uncertainty Quantification And Applications, Dhrubajyoti Ghosh

Arts & Sciences Graduate Student Theses and Dissertations

Time series analysis is an essential tool in modern world statistical analysis, with a myriad of real data problems having temporal components that need to be studied to gain a better understanding of the temporal dependence structure in the data. For example, in the stock market, it is of significant importance to identify the ups and downs of the stock prices, for which time series analysis is crucial. Most of the existing literature on time series deals with linear time series, or with Gaussianity assumption. However, there are multiple instances where the time series shows nonlinear trends, or when the …

The Isotropic And Anisotropic Structure Of Antarctica From Seismic Inversion, Zhengyang Zhou

Arts & Sciences Graduate Student Theses and Dissertations

This dissertation utilizes multiple techniques of earthquake tomography to investigate the seismic structure of the crust and mantle beneath Antarctica. The isotropic structure of the Antarctic crust and upper mantle is now constrained by several seismic studies, but until now few studies have investigated the anisotropic structure. Therefore, in this study, I focus on the anisotropic structure, which is crucial information to understanding current or historic deformation and flow patterns, as well as the organic process of Antarctica. I use the data from the seismic stations deployed on the Antarctica continent during the past 20 years, as well as other …

Crisisready's Novel Framework For Transdisciplinary Translation: Case-Studies In Wildfire And Hurricane Response, Andrew Schroeder, Caleb Dresser, Akash Yadav, Jennifer Chan, Shenyue Jia, Caroline Buckee, Satchit Balsari

Institute for ECHO Articles and Research

Extreme weather events including wildfires and hurricanes are becoming increasingly hazardous due to climate change, and often result in transient or permanent population displacements. Disaster-related disruptions in infrastructure, workforce, wages, and social networks can combine with population displacements to result in interruptions in health care access and prolonged impacts on morbidity and mortality. The data needed to make health systems and emergency management approaches more resilient to these hazards, and more responsive to the needs of affected populations, are sequestered in silos across private corporations and public agencies. In two case studies, we describe how our research team at CrisisReady …

Truncated Realized Variations Of Lévy Models: Optimality, Debiasing, And Implementation Approaches, Yuchen Han

Arts & Sciences Graduate Student Theses and Dissertations

Statistical inference for stochastic processes under high-frequency observations has been an active research area in econometrics and financial statistics for over twenty years. In this thesis, we consider some aspects related to the estimation of the volatility of an Itô semimartingale in the presence of Lévy-type jumps, which is of fundamental importance in derivatives pricing evaluation, risk management and portfolio allocation. The main technique we use is the Truncated Realized Variation (TRV) that is both rate- and variance-efficient, in the Cramer-Rao lower bound sense, when jumps are of bounded variation.Motivated by recent results that state that the optimal threshold parameter, …

The Physics Of Associative Polymers And Applications To Biomolecular Condensates, Furqan Dar

Arts & Sciences Graduate Student Theses and Dissertations

Biomolecular condensates represent a new and ubiquitous class of membraneless organelles (MLOs) that are essential for healthy cellular functioning. The constituent molecules of such condensates span a vast bio-macromolecular gamut from intrinsically disordered regions and proteins (IDPs/IDRs), to RNA and RNA-binding proteins (RNPs), to polymerases and DNA etc. Apart from being part of the regular healthy cell cycle, these condensates are also implicated in many diseases, most notably progressive neurodegenerative diseases like Amyotropic Lateral Sclerosis (ALS) and Huntingtin's Disease (HD). Since the constituent molecules of these condensates span a broad range of length scales and modes of interaction, uncovering a …

Local Spectroscopy Data Infrastructure: Solid State Nmr Crystallography With Experiment, First-Principal Analysis And Machine Learning, He Sun

Arts & Sciences Graduate Student Theses and Dissertations

Solid-state magnetic resonance (SSNMR) spectroscopy is a powerful tool for obtaining precise information about the local bonding and morphology of materials. The detailed local structure of crystalline materials cannot be easily solved by traditional experimental methods such as X-ray diffraction (XRD). SSNMR combined with first principal calculation methods such as density functional theory (DFT) can be of great use in this research area. The methodology that is called “NMR crystallography” today has been widely applied to the determination of a wide range of solid materials with an increasing amount of computationally simulated NMR spectra. The construction of a well-established computational …

Toward Enhancing The Synthesis Of Renewable Polymers: Feedstock Conversions And Functionalizable Copolymers, Tedd Casey Wiessner

Arts & Sciences Graduate Student Theses and Dissertations

This thesis describes research under the rubric of the Center for Sustainable Polymers that is aimed at two separate goals. The goal of the first project (Chapters 1 and 2) was to develop a deeper mechanistic understanding of a method for the synthesis of linear α-olefins, while the second aimed at synthesizing statistical copolymers that incorporate olefin-containing monomers through ring-opening transesterification polymerization and showing that these copolymers could be functionalized. In Chapter 1, published methods for the conversion of fatty acids to linear α-olefins are reviewed to provide context for the mechanistic work we accomplished (Chapter 2). In Chapter 2 …

Functionalized Plasmonic Nanostructures For Ultrasensitive Single Cell Analysis, Priya Rathi

Arts & Sciences Graduate Student Theses and Dissertations

Ultrasensitive detection and quantification of soluble, secreted and cell surface-bound proteins is critical for advancing our understanding of cellular systems, enabling effective drug development, novel therapies, and bio-diagnostics. However, exiting technologies are largely limited by their sensitivity, making the detection and quantification of low-abundant proteins extremely challenging. This forms a major barrier in various fields of biology and biomedical sciences. In this work, we introduce novel cellular analysis methodologies based on plasmon-enhanced fluorescence for analyzing cell structure and probing surface and secreted proteins from cells. In the first part, we introduce plasmon-enhanced expansion microscopy and demonstrate the effectiveness of employing …

The Effect Of Ionization Density In Applications Of Radiation Detection, Dosimetry, And Therapy, Daniel Mulrow

Arts & Sciences Graduate Student Theses and Dissertations

This dissertation covers a wide range of topics but is linked by the common theme of radiation interacting with materials and studying the result of those interactions. The introduction describes the fundamentals of how radiation interacts with material and how we are able to detect that radiation and the application of how we use those interactions in radiation oncology. The thesis starts with a chapter detailing the temperature dependence of the photophysics in two organic scintillators. This chapter is the foundation for a future study that will look the degree to which these scintillators can distinguish between gammas and neutrons …

Tracking Reducing Equivalents Between Cellular Compartments To Understand The Metabolic Demands Of Proliferation, Yahui Wang

Arts & Sciences Graduate Student Theses and Dissertations

Proliferating cancer cells compartmentalize metabolic reactions, many of which require reducing equivalents. This compartmentalization is functionally important, but it is challenging to study with current technologies. As a consequence, our understanding of proliferating metabolism has been limited. Here, I developed an approach to track reducing equivalents between cellular compartments. By applying this method to a panel of different cell lines under various conditions, I investigated a dysregulated metabolic phenotype in proliferating cells known as “aerobic glycolysis”. Aerobic glycolysis is characterized by an elevated rate of glucose fermentation to lactate irrespective of oxygen availability. Using the NCI-60 cell lines, I first …

Non-Canonical Beta-Lactam Antibiotics, Brett Wesley Virgin-Downey

Arts & Sciences Graduate Student Theses and Dissertations

In canonical β-Lactam antibiotics, such as penicillin, the strained nature of the β-Lactam ring leads to acylation of the catalytic serine in the active site of transpeptidases. In 2018, our lab reported a novel mechanism for monocyclic β-lactam antibiotics in the inhibition of glutamine synthetase (GS) by a natural product, tabtoxinine-β-lactam (TβL) using a 3-hydroxy-β-lactam pharmacophore. This work aims to generalize the β-lactam scaffold from TβL to act as a warhead against ATP-dependent carboxylate-amine ligase enzymes, with dihydrofolate synthetase (DHFS) as the test case. A pure 3-hydroxy-β-lactam warhead was synthesized and ligated both chemically and chemoenzymatically to different pteridine mimics. …

Secure Authentication Scheme Based On Numerical Series Cryptography For Internet Of Things, Dr Khaled Nagaty, Maha Aladin, Abeer Hamdy Dr.

Computer Science

The rapid advancement of cellular networks and wireless networks has laid a solid basis for the Internet of Things. IoT has evolved into a unique standard that allows diverse physical devices to collaborate with one another. A service provider gives a variety of services that may be accessed via smart apps anywhere, at any time, and from any location over the Internet. Because of the public environment of mobile communication and the Internet, these services are highly vulnerable to a several malicious attacks, such as unauthorized disclosure by hostile attackers. As a result, the best option for overcoming these vulnerabilities …

Detection Of Stroke With Retinal Microvascular Density And Self-Supervised Learning Using Oct-A And Fundus Imaging, Samiksha Pachade, Ivan Coronado, Rania Abdelkhaleq, Juntao Yan, Sergio Salazar-Marioni, Amanda Jagolino, Charles Green, Mozhdeh Bahrainian, Roomasa Channa, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular information and blood perfusion in the retina and, due to the homology between retinal and cerebral vessels, infer if a cerebral stroke is underway. However, the feasibility of this strategy, the imaging features, and retina imaging modalities to do this are not clear. In this work, we show initial evidence of the feasibility of this approach by training machine learning models using feature engineering …

A Usability Study Of Fido2 Hardware Tokens On Mobile Devices, Stephen Lambert

Theses and Dissertations

Passwords as the primary form of authentication on the web have many issues, such as password re-use across sites and difficulty in remembering secure passwords. The FIDO Alliance has created a passwordless system that has with support from companies like Google, Apple, and Microsoft: FIDO2. Studies have shown so far that users find FIDO2 usable on personal computers, but no work has been published on its usability on mobile devices. I conducted a lab study in which participants used FIDO2 passwordless authentication with hardware tokens on a mobile phone. Participants found FIDO2 usable on mobile devices, but had similar fears …

Cloud Container Security’ Next Move, Vishakha Sadhwani

Dissertations and Theses

In the last few years, it is apparent to cybersecurity experts everywhere that the proverbial container tech genie is out of the bottle, and has been widely embraced across multiple organizations. To achieve the flexibility of building and deploying applications anywhere and everywhere, cloud native environments have gained great momentum and made the development lifecycle simpler than ever. However, container environments brings with them a range of cybersecurity issues that includes images, containers, hosts, runtimes, registries, and orchestration platforms, which needs the necessity to focus on investing in securing your container stack.

According to this report[1], released by cloud-native …

Uv-Light-Tunable P-/N-Type Chemiresistive Gas Sensors Based On Quasi-1d Tis3 Nanoribbons: Detection Of Isopropanol At Ppm Concentrations, Victor V. Sysoev, Andrey V. Lashkov, Alexey Lipatov, Ilya A. Plugin, Michael Bruns, Dirk Fuchs, Alexey S. Varezhnikov, Mustahsin Adib, Martin Sommer, Alexander Sinitskii

Department of Chemistry: Faculty Publications

The growing demand of society for gas sensors for energy-efficient environmental sensing stimulates studies of new electronic materials. Here, we investigated quasi-one-dimensional titanium trisulfide (TiS₃) crystals for possible applications in chemiresistors and on-chip multisensor arrays. TiS₃ nanoribbons were placed as a mat over a multielectrode chip to form an array of chemiresistive gas sensors. These sensors were exposed to isopropanol as a model analyte, which was mixed with air at low concentrations of 1–100 ppm that are below the Occupational Safety and Health Administration (OSHA) permissible exposure limit. The tests were performed at room temperature (RT), as …

Predicted Episode Of Submarine Groundwater Discharge Onto The South Carolina, Usa, Continental Shelf And Its Effect On Dissolved Oxygen, Wilson S. Moore, Jacob Vincent, James L. Pickney, Alicia M. Wilson

Faculty Publications

Submarine groundwater discharge (SGD) may directly influence the dissolved oxygen (DO) content of coastal bottom waters. Here, we report a predicted episode of enhanced SGD that caused low DO concentrations on the South Carolina continental shelf. The prediction model linked episodes of SGD to upwelling-favorable winds. The data revealed these waters were a factor of 2–6 higher in ²²⁶Ra and ²²⁸Ra compared to typical bottom water values and were significantly depleted in DO (<130 μM). The tight ²²⁸Ra:²²⁶Ra correlation of these data was similar to values during a strong hypoxic event off SC in 2012. Water ages from …

Observation Of The Ξ_B^-→Λ_B^0 Π^- Decay And Measurement Of B(Ξ_B^-→Λ_B^0 Π^-), Zhuoming Li

Dissertations - ALL

We present the first observation of the weak decay Ξ−b → Λ0b π−, which is mediated by an s → u ̄ud transitionwithin the Ξ_b^- baryon. The analysis uses a pp collision data sample at a center-of-mass energy of 13 TeV corresponding to 5.5 fb^(−1) of integrated luminosity. The sample of Λb0 baryons used in this analysis are reconstructed through their decays to Λ+c π− and Λ+c π−π+π−. From a fit to the Ξ−b → Λ0b π− mass spectrum, the Ξ−b → Λ0b π− decay is observed with a significance of 11.3 standard deviations, thus establishing observation of this decay. …

Computational Studies Of Dinuclear Catalytic Reaction Mechanisms, James Curtis Coombs Iii

Theses and Dissertations

Heterodinuclear and homodinuclear metal complexes with a direct metal-metal interaction offer the potential for unique catalysis due to cooperativity effects that impact reaction mechanisms, reactivity, and selectivity. Quantum-chemical density functional theory (DFT) calculations can directly examine the origin of dinuclear reactivity and selectivity effects. Chapter 1 provides a short overview of heterodinuclear and homodinuclear catalysts that have been experimentally and computationally examined. Chapter 2 reports our study using DFT methods to understand the mechanism and reactivity of a heterodinuclear Co-Zr catalyst with phosphinoamide ligands that catalyzes a Kumada coupling between alkyl halides and alkyl Grignards. Chapter 3 reports DFT calculations …