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Isometric Centroid Encoder (Ice) And Synthetic Data Generation Approaches For Biological Datasets, Prathyusha Kanakamalla

Browse all Theses and Dissertations

This thesis addressed two main challenges in biological data analysis: structure-preserving dimensionality reduction and synthetic data generation for small sample datasets. I proposed the Isometric Centroid Encoder (ICE), a supervised dimensionality reduction method that preserves pairwise distances between class centroids during dimension reduction. Unlike existing methods like Centroid Encoder and Super Encoder, ICE explicitly maintains geometric relationships between biological classes, achieving nearly perfect structure preservation at C dimensions (where C equals the number of classes) with strong performance even in 2D and 3D spaces. Additionally, I compared three generative models (VAE, LSH-GAN, and scDiffusion) for synthetic data generation on small …

Hydrogen Storage Density And Adsorption Energy Barriers On Li-Decorated Bc3 Nanosheet, Sri Venkat Pavan Upasi

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Hydrogen is considered an emerging carrier of clean energy with renewable capabilities. Widespread hydrogen energy utilization necessitates efficient storage strategies. Functionalized nanomaterials, such as Li-decorated BC3 nanosheets, are among the primary candidate materials for hydrogen storage. This research investigates the feasibility of hydrogen storage by estimating energy barriers and their dependence on storage density on Li-decorated BC3 nanosheet. Density functional theory (DFT) simulations provide estimates of adsorption energies and saddle points for hydrogen storage and compare corresponding reaction rates. The results are expected to help us understand the advantages and possible shortcomings of hydrogen storage on such nanomaterials.

Biosensing Applications Of Thz Rotational Spectroscopy: Sensing And Analysis Of Exogenous And Endogenous Compounds In Exhaled Breath, Daniel J. Tyree

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Exhaled human breath contains a wealth of volatile molecular species which bear an imprint of compounds dissolved in blood. Assessing trace amounts of these species in exhaled breath requires a highly sensitive and selective method. Terahertz (THz) rotational spectroscopy satisfies these needs by detecting numerous and narrow, molecule specific spectral features with feature intensity dependent on the quantity of absorbing molecules, molecular structure, and experimental parameters. Expanding the applicability of THz sensing to biological gases requires systems to measure this spectral data, reliable analysis of the spectra, and demonstration of the utility of biological data extracted from the spectra. To …

Disengaged And Drowsy: Using An Adaptive System To Detect Suboptimal Learning, William Andrew Stalker

Browse all Theses and Dissertations

Instruction is increasingly asynchronous, providing new opportunities but at the cost of losing some guard rails of in-person classes. One such guard rail is an instructor’s ability to detect boredom and learner disengagement. This dissertation explores the development and evaluation of an adaptive training simulator designed to respond to user engagement levels in real-time. The simulator monitors eyeblinks, comparing metrics to individual baselines to detect signs of fatigue and boredom. Participants are exposed to novel information in an audiobook recording of a textbook chapter and later quizzed to assess retention. An adaptive intervention offering periodic brief respite was tested against …

Ultrasonic Sensor-Based Sound Synthesis Using Raspberry Pi Pico W, Niraj Jaishwal

Williams Honors College, Honors Research Projects

At the intersection of Human Computer Interaction and digital art, this project transforms simple motion into musical expression. It explores an interactive real-time sound synthesis system using ultrasonic sensors to generate continuous audio. The objective is to design a system that maps physical distances into musical parameters such as pitch and amplitude, which will create a responsive audio environment. Two ultrasonic sensors are used in combination with the Raspberry Pi Pico W microcontroller running CircuitPython and Adafruit Audio Hat for real-time sound output. One sensor controls the pitch of the generated tone, while the other controls volume. This enables expressive …

Pca Text Sentiment Analysis Tool, Luke Gegick

Williams Honors College, Honors Research Projects

This project applies principal component analysis (PCA) to sentiment analysis of text to identify complex emotional responses from plain text. Existing sentiment analysis tools often rely on large language models or struggle to achieve high accuracy when processing large collections of short inputs, such as social media comments. By contrast, this project uses PCA as a lightweight, mathematically grounded alternative that can scale efficiently while still capturing meaningful emotional structure in text data.

PCA has shown strong effectiveness in text analysis, particularly when supported by a sufficiently large dataset and a robust preprocessing pipeline. To create consistent, information-rich input vectors, …

Improving The Accuracy Of Neighborhood Median Pixel Method (Nmpm) In Classifying Landsat-8 Oli Images By Optimizing The Scoring System’S Point Values, Abraham T. Magpantay, Proceso L. Fernandez Jr

Department of Information Systems & Computer Science Faculty Publications

The Neighborhood Median Pixel Method has previously been introduced as an image processing technique in remote sensing, developed to classify Landsat-8 OLI satellite image pixels into categories of vegetation, water, and built-up areas. This method relies on a lookup table based on the median pixel values within a pixel’s neighborhood and a scoring system that assigns point values for classification. While a 9x9 neighborhood size was originally proposed, a succeeding study suggested a 13x13 neighborhood for better classification accuracy. This study focuses on refining the scoring system used in the Neighborhood Median Pixel Method, particularly the original set of arbitrary …

Electronic Health Records In Non-Hospital Settings Of Developing Economies: A Systematic Review On Enablers And Barriers, Bejie Rodriguez, Joenelyn Kaye Demoral, Jan Jacob Carpio, Alan Napoleon Gultia, Gloria Shiela Coyoca, Cecilio Garciano, Lemuel Clark Velasco

Institute of Philippine Culture (IPC)

In recent years, rapid advancements in Information and Communications Technology (ICT) have greatly transformed the healthcare landscape by streamlining health data management and providing decision-makers with secure and convenient access to health records. In developing economies, limited resources hinder healthcare access. Implementing EHRs in non-hospital settings is essential for enhancing healthcare quality and accessibility. While existing literature supports EHR use, further research is needed to pinpoint specific barriers and enablers. Using PRISMA guidelines, 18 relevant articles were systematically analyzed with the Human, Organization, and Technology Fit (HOT-fit) framework to examine these factors in non-hospital settings within developing economies. This study …

Fabrication And Characterization Of Chalcogenide And Oxide Thin Films, Shuhang Pan

Yale Graduate School of Arts and Sciences Dissertations

This dissertation explores the fabrication, structural characterization, and quantum transport properties of chalcogenide and oxide thin films. High-quality SnTe films were synthesized via molecular beam epitaxy (MBE), demonstrating tunable topological surface states through nanoscale patterning. Magnetoconductivity measurements revealed weak antilocalization (WAL) effects across continuous and patterned films, with coherence lengths governed by boundary scattering in hole-patterned geometries. Advanced focused ion beam (FIB) protocols enabled atomic-resolution transmission electron microscopy (TEM) of monolayer ZrO2 on silicon, defect distribution in off-stoichiometric CaWO4 films and orientation analysis in YVO4 thin films. Josephson junctions fabricated on superconducting Nd1−xEuxNiO2 thin films exhibited …

Tennessee’S Education Savings Account Pilot Program: An Equal Protection Violation Under The Guise Of “School Choice”, Haylie N. Lovelace

University of Memphis Law Review

No abstract provided.

Algorithmic Lawmaking, Moral Judging, And Free Will, Jacob Eisler

Case Western Reserve Law Review

No abstract provided.

Across The Bitter Divide: A Proposal To Improve Certainty In Patent Eligibility, Ian M. Adams

Case Western Reserve Law Review

No abstract provided.

Directed Assembly Of Magnetic Binary Suspensions, David H. Harris

Dissertations

Colloids are particle suspensions in a continuous medium. The particle interactions promote the assembly of structures under the influence of a magnetic field, known as directed-assembly. The magnetic properties and shape anisotropy are relevant features of the particle building blocks to the assembled structures. The dipolar interaction between colloidal particles for directed assembly has been extensively modeled considering spherical particle potentials, which is inaccurate when anisotropic particles are at close range. This research aims to address the problem of quantifying the dipolar interaction between arbitrarily positioned and oriented ellipsoids with different aspect ratios and material properties. We combine the recently …

Correlating Optical Phase And Atmospheric Coherence Width In Characterizing Turbulence, Scott Alexander Kaiser

Dissertations

This dissertation presents the development, validation, and optimization of a novel Hartmann Turbulence Sensor (HTS) for real-time, high-speed characterization of atmospheric optical turbulence. The HTS captures and processes live data at 1 kHz and reports turbulence parameters at 22 Hz. A key innovation is the integration of a dominant spectral component selection method into the Difference in Differential Tilt Variance (DDTV) algorithm. By using spectral analysis to identify areas of interest (AOIs) based on their dominant spatial frequency content, this method reduces computational load by up to 75% while maintaining a low RMS error. It also offers a visual representation …

Signal-To-Interference Degradation Due To Adc Dynamic Range For A Pulsed Doppler Radar Digital Signal Processor, Shawn Richard German

Dissertations

The objective of this study was to develop an expression for signal processor signal-to-interference ratio (SIR) improvement that combines factors that have historically been treated separately into a simple closed form expression, specifically factors such as analog-to-digital converter (ADC) dynamic range, phase noise, sub-quanta signal levels, signal-to-noise ratio (SNR), gain, automatic gain control (AGC), receiver noise, and signal and clutter characteristics. The SIR expression developed in this study quantifies how much a signal processor’s performance is degraded by the inclusion of an analog-to-digital converter (ADC) with respect to an equivalent well designed all-analog design. Using this unified SIR metric, expressions …

Toward Measurable Explainable Ethical Ai: An Llm-Driven Data Analytics Study, Greg Bacon

Dissertations

Large Language Models (LLMs) have been a hot area for popular and research audiences. Users marvel subjectively at Artificial Intelligence (AI) outputs — so much that OpenAI delayed public release of Generative Pre-trained Transformer 2 (GPT-2) back in 2019, citing ``safety and security concerns.'' This research advances ethical and transparent AI through qualitative and quantitative measures between user intent and LLM responses in a way that aims to assist users with clear indications of good and poor alignment and of where to backtrack to minimize bias and hallucinations. The use case is recommending grant topics in a United States Department …

Novel Ai/Ml-Based Frameworks For Protein Conformation Selection In Drug Discovery Applications, Shivangi Gupta

Dissertations

Drug development is a lengthy, expensive process with a high failure rate. The urgency brought on by the COVID-19 pandemic has accelerated the integration of artificial intelligence (AI) and machine learning (ML) to enhance drug discovery by increasing target specificity, reducing toxicity, and optimizing formulation strategies. Building on this momentum, this dissertation introduces novel AI/ML-driven frameworks for protein conformation selection and classification, addressing critical challenges in modern drug discovery. However, designing such a novel AI/ML data-driven framework is a difficult task because most real-world biomedical datasets suffer from class imbalance issues, which can significantly skew AI/ML model training, resulting in …

Analysis Of Second-Order Decoupled Time-Stepping Schemes For The Navier-Stokes-Debye-Hückel Model Of Electroosmotic Flow, Craig S. Bosma

Dissertations

Electroosmotic (EO) flow has attracted much attention in recent years due to applications in microfluidics, such as in lab-on-a-chip type systems. Because of the inherent difficulties in measuring and monitoring microfluidic channels, analysis of EO flow is often performed by numerical simulation. The Navier-Stokes-Debye-Hückel model — a simplification of the Nernst-Planck model which couples conservation of the ionic concentrations to the Navier-Stokes equations — is the preferred model for studying such flows when the zeta potential is small. In this work, we study the well-posedness of the unsteady Debye-Huckël model, and propose decoupled time-stepping schemes for numerical simulation. We demon- …

Observational Analysis Of Small-Scale Structures Across The Earth’S Bow Shock, Rebecca Harvey

Dissertations

This work identifies and characterizes magnetic structures in the solar wind and magnetosheath across the Earth’s bow shock. I investigate the differences between the properties of small-scale flux rope (SFR) structures immediately upstream and downstream of the bow shock by employing two data analysis methods: one based on wavelet transforms and the other based on the Grad-Shafranov (GS) detection and reconstruction techniques. 676 hours in the solar wind, and 1051 hours in the magnetosheath, of in situ magnetic field and plasma data from the Magnetospheric Multiscale (MMS) and Time History of Events and Macroscale Interactions during Substorms (THEMIS) missions were …

Online Chebyshev-Based Pseudospectral Methods For Nonlinear System Identification, Arian Yousefian

Dissertations

Nonlinear system identification plays a crucial role in developing effective control for various systems, including autonomous vehicles, robotics, and industrial process control. Acquiring the system model with minimal sensing and computation can significantly reduce control costs in these applications. Traditional adaptive control techniques often rely on uniform or high-frequency sampling, which may become impractical or computationally expensive for rapidly changing or high-dimensional systems. While Chebyshev-based pseudospectral (PS) methods have proven highly effective in offline contexts, their direct online implementation faces several challenges. Successfully approximating system dynamics online requires prior information about the approximation intervals to compute Chebyshev nodes for data …

Ai Lawyering Skills Trainers: Transforming Legal Education With Generative Ai, Alexandria Serra

Journal of Law, Technology, & the Internet

The integration of generative AI (GenAI) tools in legal education is not just an innovation—it's a transformative shift redefying how law students acquire and refine advocacy skills. This article examines AI’s critical role in modernizing legal education, emphasizing its potential to offer personalized, one-on-one coaching that enhances student learning and engagement. As AI reshapes the legal profession, law schools must evolve to prepare students for an AI-driven future.

Serving as a practical guide, this article provides a step-by-step framework for educators and institutions to develop AI tools that simulate real-world courtroom scenarios and provide continuous, personalized feedback. It also highlights …

Sampling Balanced High-Quality Data To Train An Automatic Mesh Generator, Jie Pan, Jingwei Huang, Gengdong Cheng, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

In real-world scenarios, high-quality data are often scarce and imbalanced, yet it is essential for the optimal performance of data-driven algorithmic models. Data synthesis methods are commonly used to address this issue; however, they typically rely heavily on the original dataset, which limits their ability to significantly improve performance. This article presents a quality function-based method for directly generating high-quality data and applies it to a mesh generation algorithm to demonstrate its efficiency and effectiveness. The proposed approach samples input-output pairs of the algorithm based on their feature spaces, selects high-quality samples using a defined quality function that evaluates the …

Soil Tent: Implementation Guide, Haley F. Wicklein, Alicia Carlson

Earth Around Us

No abstract provided.

A Governance-Centric Framework For Strengthening Healthcare Cybersecurity: A Systems Perspective, Sujatha Alla, Sai Gireesh Komaragiri, Teresa Duvall, Satluk Karahan, Nagesh Bheesetty, Vijay Kumar Chattu

Engineering Management & Systems Engineering Faculty Publications

Healthcare systems face unprecedented security and privacy challenges due to increasing digitization and interconnectedness. This paper provides a comprehensive analysis of these challenges by examining various cyberattacks, defensive mechanisms, and governance frameworks within modern healthcare infrastructure. The research systematically categorizes prevalent security threats, such as ransomware, insider threats, and data breaches, identifying vulnerabilities specific to healthcare systems. Furthermore, the study evaluates current defensive strategies, including encryption techniques, access control systems, and intrusion detection tools, assessing their effectiveness against complex cyber threats. A key focus is placed on governance structures and their role in cybersecurity resilience. The research explores how regulatory …

A Unionid Mussel Biodiversity Hotspot Experiencing Unexplained Declines: Evaluating The Influence Of Chemical Stressors Using Caged Juveniles, W. Aaron Wilson, Christine Bergeron, Jennifer Archambault, Jason M. Unrine, Jess Jones, Braven Beaty, Damian Shea, Peter R. Lazaro, Jody L. Callihan, Jennifer J. Rogers

Plant and Soil Sciences Faculty Publications

Unionid mussel populations in a section of the Clinch River in Virginia, USA, has declined substantially, but the causes of the decline remain unknown. To investigate this zone of decline (ZOD), we deployed juvenile freshwater mussels (Villosa iris in 2012 and Lampsilis fasciola in 2013) in both cages and silos at sites within the Clinch River System. We analyzed mussel tissues for trace element and organic contaminant concentrations, shells for trace elements, and environmental media (total water, dissolved water, particulate sediment, and bedload sediment) for both inorganic and organic contaminants. We found a few differences between mussels deployed in cages …

Personalized Physics Learning Through Ai: Insights From Problem Generation, Chatbot Dialogues, And Intelligent Tutoring Systems, Atharva Dange

Physics Dissertations - Archive

Artificial intelligence (AI) is poised to transform science education, yet questions remain on how best to integrate these technologies into teaching and learning. This dissertation investigates the use of AI-driven tools in university physics courses through three complementary studies. In the first study, a generative language model (ChatGPT) was used to create novel physics homework problems aligned with course objectives. Analysis showed that, after expert vetting, AI-generated questions can foster higher-order problem-solving and reduce student reliance on solution memorization, though careful instructor oversight is required to ensure accuracy. The second study embedded an AI chatbot as a learning aid in …

Development And Application Of Gpu Based Monte Carlo Simulation Techniques In Radiation Medicine, Satzhan Sitmukhambetov

Physics Dissertations - Archive

Cancer remains a significant public health challenge, with treatments like radiation therapy forming a cornerstone of modern care. To address this challenge, advanced computer simulations can improve radiotherapy in two primary ways. From one hand, mechanistic simulations help elucidate the fundamental radiobiological working principles, which could contribute to the clinical advancements from a bottom-up framework. On the other hand, modality simulations could help design better clinical systems with better detection and therapeutic capabilities. This research enhances these critical simulation tools by introducing two significant developments.

First, this work introduces a metaphase DNA model into a microscopic Monte Carlo simulation framework …

Uncertainty In Solar Wind Propagation: An Analysis Of L1 To Earth Variability And The Implications For Geospace Modeling In Space Weather Operations, Espen T. Fredrick

Physics Dissertations - Archive

As humanity's technological dependence grows, so does its vulnerability to space weather. Space weather describes solar-driven phenomena in the near-Earth space environment and their terrestrial effects. Many of these effects occur due to the interaction of the solar wind and Earth's magnetosphere. The solar wind originates at the solar corona and carries solar plasma and magnetic field outward through the solar system. This magnetic field, known as the interplanetary magnetic field (IMF) during transit, can undergo magnetic reconnection with Earth's geomagnetic field when oppositely aligned field lines converge. This process transfers energy into Earth's magnetosphere, driving space weather phenomena.

Space …

Characterizing The Earth's Magnetosheath With In Situ Measurements, Hector A. Salinas

Physics Dissertations - Archive

Earth’s magnetosheath is a region of shocked plasma that mediates energy and momentum transfer from the solar wind to the magnetosphere. The dynamics and thus the plasma structures of this region are highly dependent on upstream solar wind conditions. As such, the region is often characterized as a turbulent environment, with the most intense periods of turbulence occurring often under quasi-parallel bow shock conditions. This magnetosheath turbulence displays as variable and large-scale fluctuations with in-situ measurements. Given that turbulence is a characteristic feature of the magnetosheath, this dissertation asks two questions: (1) How are plasma structures inside the sheath affected …

On The Orbital Dynamics Of Exoplanets, Exomoons, And Submoons, Shaan Dharmesh Patel

Physics Dissertations - Archive

Although exoplanet detection has long been a central focus in astronomy, growing interest in exomoons has highlighted the increasing need for theoretical frameworks to interpret emerging candidates. Furthermore, while submoons, natural satellites orbiting moons, are not presently observed in the Solar System and remain speculative (e.g., the hypothesized past submoon of Saturn’s Iapetus), their existence is plausible within the context of the complex and diverse architectures now identified across planetary and stellar systems. We develop a generalized framework to assess the orbital stability of exomoons and submoons through comprehensive N-body simulations incorporating both three-body dynamics and tidal interactions, with the …