Physical Sciences and Mathematics Commons^™

Extracting Dnn Architectures Via Runtime Profiling On Mobile Gpus, Dong Hyub Kim

Masters Theses

Due to significant investment, research, and development efforts over the past decade, deep neural networks (DNNs) have achieved notable advancements in classification and regression domains. As a result, DNNs are considered valuable intellectual property for artificial intelligence providers. Prior work has demonstrated highly effective model extraction attacks which steal a DNN, dismantling the provider’s business model and paving the way for unethical or malicious activities, such as misuse of personal data, safety risks in critical systems, or spreading misinformation. This thesis explores the feasibility of model extraction attacks on mobile devices using aggregated runtime profiles as a side-channel to leak …

Machine Learning Modeling Of Polymer Coating Formulations: Benchmark Of Feature Representation Schemes, Nelson I. Evbarunegbe

Masters Theses

Polymer coatings offer a wide range of benefits across various industries, playing a crucial role in product protection and extension of shelf life. However, formulating them can be a non-trivial task given the multitude of variables and factors involved in the production process, rendering it a complex, high-dimensional problem. To tackle this problem, machine learning (ML) has emerged as a promising tool, showing considerable potential in enhancing various polymer and chemistry-based applications, particularly those dealing with high dimensional complexities.

Our research aims to develop a physics-guided ML approach to facilitate the formulations of polymer coatings. As the first step, this …

Thermal Conductivity And Mechanical Properties Of Interlayer-Bonded Graphene Bilayers, Afnan Mostafa

Masters Theses

Graphene, an allotrope of carbon, has demonstrated exceptional mechanical, thermal, electronic, and optical properties. Complementary to such innate properties, structural modification through chemical functionalization or defect engineering can significantly enhance the properties and functionality of graphene and its derivatives. Hence, understanding structure-property relationships in graphene-based metamaterials has garnered much attention in recent years. In this thesis, we present molecular dynamics studies aimed at elucidating structure-property relationships that govern the thermomechanical response of interlayer-bonded graphene bilayers.

First, we present a systematic and thorough analysis of thermal transport in interlayer-bonded twisted bilayer graphene (IB-TBG). We find that the introduction of interlayer C-C …

Design And Fabrication Of A Trapped Ion Quantum Computing Testbed, Christopher A. Caron

Masters Theses

Here we present the design, assembly and successful ion trapping of a room-temperature ion trap system with a custom designed and fabricated surface electrode ion trap, which allows for rapid prototyping of novel trap designs such that new chips can be installed and reach UHV in under 2 days. The system has demonstrated success at trapping and maintaining both single ions and cold crystals of ions. We achieve this by fabricating our own custom surface Paul traps in the UMass Amherst cleanroom facilities, which are then argon ion milled, diced, mounted and wire bonded to an interposer which is placed …

Wast3d Potential, Andrew Larsen

Masters Theses

Waste is obsolete. Standard building industry practices are harmful to the environment. Non-traditional construction methods were examined as alternatives. Circular design logic was the guiding principle in material choice. Additive manufacturing is a proven modern method for building construction. Research on 3D printing case studies revealed that recycled plastic is a proven material and readily available. Removing plastic waste from the environment and sequestering it in architectural components gives the material a new purpose. The component of focus was a building block for a wall assembly. Inspiration was taken from the hexagonal Basalt rock formations found near volcanic fault lines. …

Fungi In Flux | Designing Regenerative Materials And Products With Mycelium, Arvind Bhallamudi

Masters Theses

As the world grapples with the escalating crisis of climate threats and environmental degradation, this research delves into the synergistic potential of design and biology, developing safe and sustainable materials for applications in prototyping, furniture and interior design. Harnessing the power of a unique organism - fungi, the study proposes an accessible, efficient, and resilient material resource system. It utilizes local waste streams and mycelium (the vegetative part of fungi) to grow functional structures. An experimental and small-scale protocol is modeled by testing bio-fabrication and bio-printing methods. The composites' performance qualities and characteristics are evaluated through mechanical testing and a …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Analysis Of Turbulent Flow Behavior In Helicopter Rotor Hub Wakes, Forrest Mobley

Masters Theses

The rotor hub is one of the most important features of all helicopters, as it provides the pilot a means for controlling the vehicle by changing the characteristics of the main and tail rotors. The hub also provides a structural foundation for the rotors and allows for the rotor blades to respond to aerodynamic forces while maintaining controllability and stability. Due to the inherent geometry and high rate of rotation, the rotor hub in its current form acts a large bluff body and is the primary source of parasite drag on the helicopter, despite its relatively small size. The rotor …

Chromatographic Dynamic Chemisorption, Shreya Thakkar

Masters Theses

Reaction rates of catalytic cycles over supported metal catalysts are normalized by the exposed metal atoms on the catalyst surface, reported as site time yields which provide a rigorous standard to compare distinct metal surfaces. Defined as the fraction of exposed metal surface atoms to the total number of metal atoms, it is important to measure the dispersion of supported metal catalysts to report standardized rates for kinetic investigations. Multiple characterization techniques such as electron microscopy, spectroscopy and chemisorption are exploited for catalyst dispersion measurements. While effective, electron microscopy and spectroscopy are not readily accessible due to cost and maintenance …

Path Planning And Flight Control Of Drones For Autonomous Pollination, Chapel R. Rice

Masters Theses

The decline of natural pollinators necessitates the development of novel pollination technologies. In this thesis, a drone-enabled autonomous pollination system (APS) that consists of five primary modules: environment sensing, flower perception, path planning, flight control, and pollination mechanisms is proposed. These modules are highly dependent upon each other, with each module relying on inputs from the other modules. This thesis focuses on approaches to the path planning and flight control modules. Flower perception is briefly demonstrated developing a map of flowers using results from previous work. With that map of flowers, APS path planning is defined as a variant of …

Enigma - Ongoing Development Towards Novel Beta-Decay Spectroscopy Station At Isolde, Philipp Wagenknecht

Masters Theses

Beta decay and collinear laser spectroscopy are proven efficient tools to study nuclear structure far from stability. Two areas of significance are investigations into nuclear deformation and shape coexistence, as well as delayed neutron emissions used in nuclear energy applications. This contribution presents the ongoing development towards a novel beta-decay spectroscopy station for the VITO experiment at CERN’s radioactive ion beam facility ISOLDE. The setup will utilize both collinear laser spectroscopy and beta-decay spectroscopy to measure the energy and spin-parities of the ground and excited states of radioactive beams. Initial designs of the support structure, magnetic field, and detector array …

Meta-Heuristic Optimization Techniques For The Production Of Medical Isotopes Through Special Target Design, Cameron Ian Salyer

Masters Theses

Medical isotopes are used for a variety of different diagnostic and therapeutic purposes Ruth (2008). Due to recent newly discovered applications, their production has become rapidly more scarce than ever before Charlton (2019). Therefore, more efficient and less time consuming methods are of interest for not only the industry’s demand, but for the individuals who require radio-isotope procedures. Currently, the primary source of most medical isotopes used today are provided by reactor and cyclotron irradiation techniques, followed by supplemental radio-chemical separations Ruth (2008). Up until this point, target designs have been optimized by experience, back of the envelope calculations, and …

Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch

Masters Theses

"This research presents studies of a novel type of magnetic nozzle that allows for three-dimensional (3-D) steering of a plasma plume. Numerical simulations were performed using Tech-X's USim® software to quantify the nozzle's capabilities. A2-D planar magnetic nozzle was applied to plumes of a nominal pulsed inductive plasma (PIP) source with discharge parameters similar to those of Missouri S&T's Missouri Plasmoid Experiment (MPX). Argon and xenon plumes were considered. Simulations were verified and validated through a mesh convergence study as well as comparison with available experimental data. Periodicity was achieved over the simulation run time and phase angle samples were …

Particle Swarm Optimization For Critical Experiment Design, Cole Michael Kostelac

Masters Theses

“Critical experiments are used by nuclear data evaluators and criticality safety engineers to validate nuclear data and computational methods. Many of these experiments are designed to maximize the sensitivity to a certain nuclide-reaction pair in an energy range of interest. Traditionally, a parameter sweep is conducted over a set of experimental variables to find a configuration that is critical and maximally sensitive. As additional variables are added, the total number of configurations increases exponentially and quickly becomes prohibitively computationally expensive to calculate, especially using Monte Carlo methods.

This work presents the development of a particle swarm optimization algorithm to design …

Pressure Relief Wells: Analysis Of Subsurface Heterogeneity To Evaluate Relief Well Locations For Mississippi River Levees, Emma Marie Young

Masters Theses

“When designing pressure relief well systems, it is imperative to understand what major geomorphology and heterogenies features are present, such as buried oxbow lakes, especially when the feature is parallel to the source, such as the Mississippi River. When present, there is a notable greater increase in head pressures, especially on the landward tow of the levee. This can cause erosional features that originally thought of to have been protected from by installing pressure relief wells. When comparing the effective hydraulic conductivities of horizontal clay layers and vertical clay layers spanning the length of the model, little to no noticeable …

Evaluation Of Robust Deep Learning Pipelines Targeting Low Swap Edge Deployment, David Carter Cornett

Masters Theses

The deep learning technique of convolutional neural networks (CNNs) has greatly advanced the state-of-the-art for computer vision tasks such as image classification and object detection. These solutions rely on large systems leveraging wattage-hungry GPUs to provide the computational power to achieve such performance. However, the size, weight and power (SWaP) requirements of these conventional GPU-based deep learning systems are not suitable when a solution requires deployment to so called "Edge" environments such as autonomous vehicles, unmanned aerial vehicles (UAVs) and smart security cameras.

The objective of this work is to benchmark FPGA-based alternatives to conventional GPU systems that have the …

Modeling And Characterization Of Optical Metasurfaces, Mahsa Torfeh

Masters Theses

Metasurfaces are arrays of subwavelength meta-atoms that shape waves in a compact and planar form factor. During recent years, metasurfaces have gained a lot of attention due to their compact form factor, easy integration with other devices, multi functionality and straightforward fabrication using conventional CMOS techniques. To provide and evaluate an efficient metasurface, an optimized design, high resolution fabrication and accurate measurement is required. Analysis and design of metasurfaces require accurate methods for modeling their interactions with waves. Conventional modeling techniques assume that metasurfaces are locally periodic structures excited by plane waves, restricting their applicability to gradually varying metasurfaces that …

Power System Stability Assessment With Supervised Machine Learning, Mirka Mandich

Masters Theses

Power system stability assessment has become an important area of research due to the increased penetration of photovoltaics (PV) in modern power systems. This work explores how supervised machine learning can be used to assess power system stability for the Western Electricity Coordinating Council (WECC) service region as part of the Data-driven Security Assessment for the Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS) project. Data-driven methods offer to improve power flow scheduling through machine learning prediction, enabling better energy resource management and reducing demand on real-time time-domain simulations. Frequency, transient, and small signal stability datasets were created using the …

Dissolved Organic Carbon And The Potential Role To Stream Acidity In The Great Smoky Mountains National Park, Jason R. Brown

Masters Theses

A substantial societal shift towards environmental awareness has focused research efforts on the impacts of pollution on natural landscapes. Improvements to pollutant regulations and technology have resulted in sizeable reductions of atmospheric deposition of anthropogenic acids, especially nitrates and sulfates, which has altered the role of these ions in the environment. As such, understandings of environmental chemistry dynamics have required regular updating.

Through the National Park Service Vital Signs monitoring program, increases in precipitation pH observed in Great Smoky Mountains National Park (GRSM) has been attributed to the reduction of inorganic acid concentrations. Unfortunately, these improvements have not been uniformly …

Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii

Masters Theses

“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …

A Simple Background Elimination Method For Miniaturized Fiber-Optic Raman Probe, Bohong Zhang

Masters Theses

"Raman scattering is called a photonic - molecular interaction based on the kinetic model of the analytic. Due to the uniqueness of the Raman scattering technique, it can provide a unique fingerprint signal for molecular recognition. However, a serious challenge often encountered in Raman measurement comes from the requirements of fast, real-time remote sensing, background fluorescence suppression, and micro-environmental detection.

A new Miniaturized Fiber-Optic Raman Probe (MFORP) for Raman spectroscopy, used especially for eliminating background fluorescence and enhancing sampling, is presented. Its main purpose is to provide an overview of excellent research on the detection of very small substances and …

A Compact Wavelength Meter Using A Multimode Fiber, Ogbole Collins Inalegwu

Masters Theses

“Wavelength meters are very important for precision measurements of both pulses and continuous-wave optical sources. Conventional wavelength meters employ gratings, prisms, interferometers, and other wavelength-sensitive materials in their design. Here, we report a simple and compact wavelength meter based on a section of multimode fiber and a camera. The concept is to correlate the multimodal interference pattern (i.e., speckle pattern) at the end-face of a multimode fiber with the wavelength of the input lightsource. Through a series of experiments, specklegrams from the end face of a multimode fiber as captured by a charge-coupled device (CCD) camera were recorded; the images …

Relationships Among Mineralogy, Geochemistry, And Oil And Gas Production In The Tuscaloosa Marine Shale, Hayley Roxana Beitel

Masters Theses

"The Tuscaloosa Marine Shale (TMS) is an unconventional shale reservoir located in southeast Louisiana and southwest Mississippi. Limited mineralogical and geochemical data for the TMS have been published. The data that do exist indicate that the formation is heterogeneous. Consequently, previous investigators and oil and gas companies have not managed to effectively link mineralogical and chemical changes to oil and gas production in the TMS. These linkages are critical to establish for future exploration efforts. In this study, we attempt to establish these relationships by gathering all existing mineralogical and chemical data in the TMS, including newly acquired data from …

Metric Learning Via Linear Embeddings For Human Motion Recognition, Byoungdoo Kong

Masters Theses

We consider the application of Few-Shot Learning (FSL) and dimensionality reduction to the problem of human motion recognition (HMR). The structure of human motion has unique characteristics such as its dynamic and high-dimensional nature. Recent research on human motion recognition uses deep neural networks with multiple layers. Most importantly, large datasets will need to be collected to use such networks to analyze human motion. This process is both time-consuming and expensive since a large motion capture database must be collected and labeled. Despite significant progress having been made in human motion recognition, state-of-the-art algorithms still misclassify actions because of characteristics …

A Framework To Support Automatic Certification For Self-Adaptive Systems, Ioannis Nearchou

Masters Theses

Presently, cyber-physical systems are increasingly being integrated into societies, from the economic sector to the nuclear energy sector. Cyber-physical systems are systems that combine physical, digital, human, and other components, which operate through physical means and software. When system errors occur, the consequences of malfunction could negatively impact human life. Academic studies have relied on the MAPE-K feedback loop model to develop various system components to satisfy the self-adaptive features, such that violation of the safety requirements can be minimized. Assurance of system requirement satisfaction is argued through an industrial standard form, called an assurance case, which is usually applied …

High-Resolution Timeseries Analysis Of Dynamic Geochemistry: A 27-Well Survey Of Contaminated Groundwater Downstream Of The Former S-3 Ponds, Oak Ridge, Tennessee, Emma Dixon

Masters Theses

Spatiotemporal variability of geochemistry of contaminated groundwater has large implications on overall water quality and ability to respond to remedial applications. Gaining knowledge of how geochemistry changes over time in an area can help establish response trends to changing external conditions like weather and level of contamination. In this study, a spatiotemporal survey was performed on 27 wells at the Y-12 Complex in Oak Ridge, Tennessee. This was completed to measure diurnal fluxes in geochemistry from seasonal changes and extreme weather conditions in three areas of historically different contamination levels from a single point contamination source. Measurements were gathered over …

Empirical Modeling Of Used Nuclear Fuel Radiation Emissions For Safeguards Purposes, Amanda M. Bachmann

Masters Theses

For nuclear nonproliferation safeguards, the ability to characterize used nuclear fuel (UNF) is a vital process. Fuel characterization ^allows for independent verification by inspectors of operator declarations of the special nuclear material flow and nuclear related activities within a facility, and an estimation of fissile material remaining in a fuel assembly. Current methods to verify this information rely heavily on non-destructive assay techniques, such as gamma spectroscopy and neutron detection measurements. While these measurements are effective tools for estimating a specific characteristic of the fuel, such as burnup or cooling time, they often require an accurate estimation of a select …

Compound Effects Of Clock And Voltage Based Power Side-Channel Countermeasures, Jacqueline Lagasse

Masters Theses

The power side-channel attack, which allows an attacker to derive secret information from power traces, continues to be a major vulnerability in many critical systems. Numerous countermeasures have been proposed since its discovery as a serious vulnerability, including both hardware and software implementations. Each countermeasure has its own drawback, with some of the highly effective countermeasures incurring large overhead in area and power. In addition, many countermeasures are quite invasive to the design process, requiring modification of the design and therefore additional validation and testing to ensure its accuracy. Less invasive countermeasures that do not require directly modifying the system …

Characterization Of A Plasma Source Simulating Solar Wind Plasma In A Vacuum Chamber, Blake Anthony Folta

Masters Theses

"The United States has set an aggressive time line to not only return to the Moon, but also to establish a sustained human presence. In the Apollo missions dust was a significant factor, but the duration of those missions was short so dust and surface charging were problems, but they did not pose an immediate threat. For a long-term mission, these problems instead become incredibly detrimental. Because of this, research needs to be conducted to investigate these phenomena so that mitigation techniques can be developed and tested. To this end, this thesis serves to demonstrate the Gas and Plasma Dynamics …

Developing 5gl Concepts From User Interactions, David Stuckless Meyer

Masters Theses

In the fulfilling of the contracts generated in Test Driven Development, a developer could be said to act as a constraint solver, similar to those used by a 5th Generation Language(5GL). This thesis presents the hypothesis that 5GL linguistic mechanics, such as facts, rules and goals, will be emergent in the communications of developer pairs performing Test Driven Development, validating that 5GL syntax is congruent with the ways that practitioners communicate. Along the way, nomenclatures and linguistic patterns may be observed that could inform the design of future 5GL languages.