Physical Sciences and Mathematics Commons^™

Advanced Deep Learning Methodologies For Deepfake Detection, Aminollah Khormali

Electronic Theses and Dissertations, 2020-2023

The recent advances in the field of Artificial Intelligence (AI), particularly Generative Adversarial Networks (GANs) and an abundance of training samples along with robust computational resources have significantly propelled the field of AI-generated fake information in all kinds, e.g., deepfakes. Deepfakes are among the most sinister types of misinformation, posing large-scale and severe security and privacy risks targeting critical governmental institutions and ordinary people across the world. The fact that deepfakes are AI-generated digital content and not actual events captured by a camera implies that they still can be detected using advanced AI models. Although the deepfake detection task has …

Dynamic Rbi With Central Difference Method Approach In Calculation Of Uniform Corrosion Rate: A Casestudy On Gas Pipelines, M.Riefqi Dwi Alviansyah, Fernanda Hartoyo, Zahra Nadia Nurullia, Ari Kurniawan

Journal of Materials Exploration and Findings

The oil and gas industry generally uses a piping system to drain fluids. Even though the pipes used have been well designed, the use of pipes as a means of fluid transportation still provides the possibility of failure that can occur at any time, one of which is due to uniform corrosion. The use of standard Risk Based Inspection (RBI) according to the API RBI 581 document has been widely used to anticipate potential failures to pipe components. The use of standard RBI can reduce the risk of failure significantly. Because the standard RBI considers the component risk value to …

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 …

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

Arts & Sciences Electronic 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 …

Quasiparticle And Excitonic Effects In Two-Dimensional Van Der Waals Materials, Linghan Zhu

Arts & Sciences Electronic Theses and Dissertations

Since their discovery, low dimensional van der Waals materials have attracted increasing research interests. They serve as ideal platforms to study novel physics in reduced-dimensional systems, and are critical in nowadays’ nanotechnology applications. Due to the reduced dielectric screening in low dimensions, strong excited state properties dictate their electronic, transport and optical properties, the study of which calls for a description of the many-particle interactions beyond the traditional density functional theory. This is where the many-body perturbation theory comes into play. In this thesis, I will present a comprehensive study of the quasiparticle and excitonic properties of a variety of …

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

Culminating Experience 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 …

Devops: Course Development, James Lee Vanderzouwen

Culminating Experience Projects

DevOps has become somewhat of a buzzword amongst software engineers in the industry. Often developers do not have a dedicated DevOps engineer let alone a DevOps team. Developers benefit when they know what happens between ‘works on my machine’ and production. Making sure those steps make sense and are safe benefits the operations team. From compliance to code review to regression testing, understanding the full SDLC, employing DevOps concepts, and minimizing overhead from dependencies is quickly becoming a pre-requisite for the modern software engineer. This project attempts to bridge the gap between buzzword and best practice by developing a college-level …

Building A Deep Model For Multi-Class Coral Species Discrimination, Hyeong Gyu Jang

Culminating Experience Projects

The goal of this qualitative research project is to develop and optimize a multi-class discrimination model to identify different species of coral based on their digital images. Currently, there are artificial intelligence (AI) models that can distinguish between coral and other undersea objects such as sand or rocks, but to our knowledge the problem of multi-species classification has not yet been addressed. Given that coral reefs are a good indicator of overall ocean health, it is important to develop models that can classify the presence of different species in underwater images as a way to monitor the effects of climate …

Covid-19 Prediction Using Machine Learning, Parashuram Singaraveni

Culminating Experience 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 …

Exploring Coral Reefs With Interactive Geospatial Visualizations, David Nicolas Tonning

Culminating Experience Projects

This project uses geospatial data to generate custom polygons in an interactive setting to represent the size and location of coral reefs to extract insights from coral reef-centered data sets. Historically, the data used by the Reef Restoration Group Bonaire exists in disparate sources, making it difficult to track and analyze the outcomes of their restoration work. Additionally, this information is not available in a digestible format for other audiences who would be interested in this data, such as citizen scientists seeking coral reef health statistics, the general public wanting to better understand the coral reefs surrounding Bonaire or recreational …

Docker Container Image – Vulnerability Scanning, Joseph U. Ohaeche

Culminating Experience 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 …

Muse: A Genetic Algorithm For Musical Chord Progression Generation, Griffin Going

Culminating Experience Projects

Foundational to our understanding and enjoyment of music is the intersection of harmony and movement. This intersection manifests as chord progressions which themselves underscore the rhythm and melody of a piece. In musical compositions, these progressions often follow a set of rules and patterns which are themselves frequently broken for the sake of novelty. In this work, we developed a genetic algorithm which learns these rules and patterns (and how to break them) from a dataset of 890 songs from various periods of the Billboard Top 100 rankings. The algorithm learned to generate increasingly valid, yet interesting chord progressions via …

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

Arts & Sciences Electronic 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 …

Geometry And Dynamics Of Rolling Systems, Bowei Zhao

Arts & Sciences Electronic 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 …

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

Arts & Sciences Electronic 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 Electronic 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 …

Effects Of Surface Ligation On Charge Extraction From Wurtzite Cadmium Selenide Quantum Platelets And Quantum Belts, Hailey Meyer

Arts & Sciences Electronic Theses and Dissertations

This dissertation presents the synthesis of flat, colloidal wurtzite CdSe quantum platelets and quantum belts for ligand exchange to novel and existing organic and inorganic L-, X-, and Z- type ligands. Use of these ligands in conjunction with the semiconductor nanocrystals allows for examination of their ligand exchange abilities, photoluminescence quenching efficiencies, and charge transfer properties.

First, zinc and cadmium dithiocarbamate compounds [M(S2CNR1R2)2] are used as ligands on wurtzite CdSe quantum belts. Complete ligand exchange is achieved when the belts are initially ligated with Cd(oleate)2, a Z-type ligand, prior to the exchange, as opposed to n-octylamine or ammonia, which are …

A Synthesis-Based Approach To The Study Of Fe(Ii) Oxidation In Smectites, Robert Joe Kupper Ii

Arts & Sciences Electronic Theses and Dissertations

Smectite clay minerals are present in diverse environments on Earth as a major product of silicate weathering. Although smectites are compositionally varied, they almost always incorporate iron. Iron-bearing smectites are an important component of the biogeochemical iron cycle, serving as a major iron fraction in many soils and altered rocks as well as participating in redox reactions within the surrounding environment. Iron incorporates into smectites in the ferric [Fe(III)] form at the modern, oxygenated surface of Earth but clays forming in anoxic settings instead incorporate ferrous iron [Fe(II)]. Owing to their ubiquity at the surface of the modern Earth, the …

Fourier Acceleration In The Linear Sigma Model, Cameron Cianci

Honors Scholar Theses

The linear sigma model is a low energy effective model of Quantum Chromodynamics. This model mimics the breaking of chiral symmetry both spontaneously and explicitly through the quark condensate and pion mass matrix respectively. Fourier acceleration is a method that can be implemented in the Hybrid Monte-Carlo algorithm which decreases autocorrelations due to critical slowing down through tuning the mass parameters in the HMC algorithm. Fourier acceleration is applied to the linear sigma model with a novel mass estimation procedure, by assuming the modes behave approximately like simple harmonic oscillators. The masses are chosen by sampling the expectation values of …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Carolina Rudisill, Alexander C. Mclain Ph.D.

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

Preferential Stiffness And The Crack-Tip Fields Of An Elastic Porous Solid Based On The Density-Dependent Moduli Model, Hyun C. Yoon, S. M. Mallikarjunaiah, Dambaru Bhatta

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, we study the preferential stiffness and the crack-tip fields for an elastic porous solid of which material properties are dependent upon the density. Such a description is necessary to describe the failure that can be caused by damaged pores in many porous bodies such as ceramics, concrete and human bones. To that end, we revisit a new class of implicit constitutive relations under the assumption of small deformation. Although the constitutive relationship \textit{appears linear} in both the Cauchy stress and linearized strain, the governing equation bestowed from the balance of linear momentum results in a quasi-linear partial …

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

Arts & Sciences Electronic 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 …

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

Arts & Sciences Electronic 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 …

Development Of Redox-Responsive Phenazine-Based Foldamers. Acylative Kinetic Resolution Of Hydroxamic Acids, Jingwei Yin

Arts & Sciences Electronic Theses and Dissertations

Two different research directions have been presented in this thesis. The first project is about phenazine-based foldamers as molecular actuators. Researchers have been interested in the design and synthesis of foldamers and molecular actuators for years. We began our exploration by demonstrating that phenazine-1,6-dicarboxamides can function as redox-responsive molecular switches. We then designed and synthesized two generations of phenazine-based interleafed foldamers and studied their stability and redox behaviors under chemical and electrochemical conditions. In the second project, we have developed the first acylative kinetic resolution on hydroxamic acids. Although chiral hydroxamic acids have extensive applications, synthetic methods towards them are …

Functionalized Plasmonic Nanostructures For Ultrasensitive Single Cell Analysis, Priya Rathi

Arts & Sciences Electronic 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 …

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

Arts & Sciences Electronic 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 …

Observation Of Novel Phases Of Quantum Matter Beyond Topological Insulator, Sabin Regmi

Electronic Theses and Dissertations, 2020-2023

Because of the unique electronic properties, intriguing novel phenomena, and potentiality in quantum device applications, the quantum materials with non-trivial band structures have enticed a bulk of research works over the last two decades. The experimental discovery of the three-dimensional topological insulators (TIs) - bulk insulators with surface conduction via spin-polarized electrons - kicked off the flurry of research interests towards such materials, which resulted in the experimental discovery of new topological phases of matter beyond TIs. The topological semimetallic phase in Dirac, Weyl, and nodal-line semimetals is an example, where the classification depends on the dimensionality, degeneracy, and symmetry …

Development Of Novel Nucleophile-Intercepted Beckmann Fragmentations And Progress Toward The Total Synthesis Of 2(S)-Cathafoline, Evan M. Dunkley

Dartmouth College Master’s Theses

This thesis is comprised of two chapters, the first being the discovery of a novel nucleophile-intercepted Beckmann fragmentation of [2.2.1] indoline systems that resulted in highly stereo- and regioselective reactions. Chapter one details the exploration of this reaction as well as its relevant background information detailing its significance. Chapter two describes the application of the novel nucleophile-intercepted Beckmann fragmentation in the context of a total synthesis of akuammilline alkaloid 2(S)-cathafoline. While the target natural product was never synthesized, unpredicted reactivity resulted in interesting discoveries worthy of discussion.

Effect Of X-Ray Illumination On Magnetic Domain Memory In [Co/Pd]/Irmn Multilayers, Colby Singint Walker

Theses and Dissertations

This thesis focuses on investigating the possible x-ray illumination effects on the magnetic domain memory (MDM) in magnetic [Co/Pd]IrMn multilayers. In this material, MDM is induced via exchange couplings between the ferromagnetic Co/Pd layer and the antiferromagnetic IrMn layer. To carry out this investigation, we have used magneto-transport and x-ray resonant magnetic scattering. The use of magneto-transport in-situ at synchrotron x-ray scattering facility has allowed us to follow the gradual effect of x-ray illumination on the amount of exchange bias, initially present after field cooling the material. With our in-situ measurements we have been able to see that x-ray illumination …

The Origin And Evolution Of Impact Crater Lakes: A Case Study Of The Ries Impact Structure, Germany, Matthew J. O. Svensson

Electronic Thesis and Dissertation Repository

Impact events are known to generate hydrothermal systems, which can subsequently vent into an overlying crater lake and potentially create ideal conditions for some microbial life-forms. Thus, early post-impact sedimentary deposits would be excellent targets for Mars sample return, and as such, the robust characterization of such deposits on Earth is critical. In this thesis, we establish an improved understanding of how the Ries crater lake formed, and how an active impact-generated hydrothermal system influenced its early evolution. The ~14.8 Ma Ries impact structure hosts the majority of its paleolake deposits within the structure's central basin with some deposits situated …