Engineering 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 …

An Efficient Privacy-Preserving Framework For Video Analytics, Tian Zhou

Doctoral Dissertations

With the proliferation of video content from surveillance cameras, social media, and live streaming services, the need for efficient video analytics has grown immensely. In recent years, machine learning based computer vision algorithms have shown great success in various video analytic tasks. Specifically, neural network models have dominated in visual tasks such as image and video classification, object recognition, object detection, and object tracking. However, compared with classic computer vision algorithms, machine learning based methods are usually much more compute-intensive. Powerful servers are required by many state-of-the-art machine learning models. With the development of cloud computing infrastructures, people are able …

Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov

Doctoral Dissertations

Reactive chemistries for protein chemical modification play an instrumental role in chemical biology, proteomics, and therapeutics. Depending on the application, the selectivity of these modifications can range from precise modification of an amino acid sequence by genetic manipulation of protein expression machinery to a stochastic modification of lysine residues on the protein surface. Ligand-Directed (LD) chemistry is one of the few methods for targeted modification of endogenous proteins without genetic engineering. However, current LD strategies are limited by stringent amino acid selectivity. To bridge this gap, this thesis focuses on the development of highly reactive LD Triggerable Michael Acceptors (LD-TMAcs) …

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 …

Controlling Mechanical Properties Of Well-Defined Polymer Networks, Ipek Sacligil

Doctoral Dissertations

Polymer networks are one of the most versatile and highly studied material class that revolutionized many aspects of life. Connecting the final network properties to the molecular parameters of its building blocks remains a major research thrust. Recent advances in network synthesis techniques allowed for accurate predictions of elastic modulus in model networks. Tew Group has developed highly efficient, thiol-norbornene networks with controllable mechanical properties. Chapter 2 focuses on modifying the gel fracture energy predicted by Lake-Thomas theory by accounting for loop defects. This study allowed for a priori estimates of gel fracture energy by combining theory, experiments, and simulations. …

Effect Of Chemical Identity And Morphology On Amphiphilic-Zwitterionic Block Copolymer Membranes, Ria Ghosh

Doctoral Dissertations

Amphiphilic block copolymers have gained a broad research interest attributed to their self-assembly properties over a range of pH, temperature, and ionic strength. Polyzwitterions have attracted special attention due to their hydrophilicity, charge sensitivity and coulombic attraction of the opposite charges over a range of environments making them a popular material of study in the field of stimuli responsive systems, for example in self-healing hydrogels, and water transport membranes. Combining the stimuli responsiveness and higher hydrophilicity of zwitterionic polymers with self-assembly behavior of amphiphilic block copolymers created an interest to study the effect of composition and identity of the zwitterionic …

Thermal Transport Across 2d/3d Van Der Waals Interfaces, Cameron Foss

Doctoral Dissertations

Designing improved field-effect-transistors (FETs) that are mass-producible and meet the fabrication standards set by legacy silicon CMOS manufacturing is required for pushing the microelectronics industry into further enhanced technological generations. Historically, the downscaling of feature sizes in FETs has enabled improved performance, reduced power consumption, and increased packing density in microelectronics for several decades. However, many are claiming Moore's law no longer applies as the era of silicon CMOS scaling potentially nears its end with designs approaching fundamental atomic-scale limits -- that is, the few- to sub-nanometer range. Ultrathin two-dimensional (2D) materials present a new paradigm of materials science and …

Vapor Deposition Of Self-Wrinkling Polymer Films, Robert N. Enright

Doctoral Dissertations

Initiated chemical vapor deposition is used to grow polymer films on substrates of various three-dimensional shapes which exhibit wrinkling during film growth, termed self-wrinkling. Self-wrinkling avoids separate film growth and compression steps and more-closely mimics processes observed in nature. The self-wrinkling process is elucidated on flat elastic substrates, revealing control over the amount of compressive stress by changing deposition conditions. Next, a study of films grown on liquid substrates with interface profiles that either resemble cylinders or contain repeating concave cones, saddles, and bowls affirms the principle that the wrinkle roundness increases with interface curvature. The selection of high versus …

Water Resources Planning Under Deep Uncertainty For Physically, Socially, And Politically Complex Systems, Sarah St. George Freeman

Doctoral Dissertations

Water supply systems, particularly those of large cities, are complex systems linking supply, regulatory and distribution infrastructure, and points of use. Despite their physical complexities, it is infrequent that full supply, distribution, end use, and feedbacks therein are considered in an integrated manner. These complex systems-of-systems face large uncertainties related to physical aspects such as degradation of infrastructure, changing demand, and climate variability and change. Though great, such physical uncertainties often pale in comparison to the those related to the human systems in place to manage them and yet uncertainty in the decision-making landscape is often grossly simplified in our …

Source Data For Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, Malleable Double Diamond Twin", Xueyan Feng, Michael S. Dimitriyev, Edwin L. Thomas

Data and Datasets

Source data and code for Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, malleable double diamond twin"

Supplementary Code For "Chain Trajectories, Domain Shapes And Terminal Boundaries In Block Copolymers", Benjamin R. Greenvall, Michael S. Dimitriyev, Gregory M. Grason

Data and Datasets

Supplementary code used for the publication "Chain trajectories, domain shapes and terminal boundaries in block copolymers" by Benjamin R. Greenvall, Michael S. Dimitriyev, and Gregory M. Grason. Includes code for extracting and analyzing polar order and chain trajectories from self-consistent field calculations of block copolymers.

Enabling An Equitable Energy Transition Through Inclusive Research, Michael Ash, Erin Baker, Mark Tuominen, Dhandapani Venkataraman, Matthew Burke, S. Castellanos, M. Cha, Gabe Chan, D. Djokic, J.C. Ford, Anna P. Goldstein, David Hsu, Matt Lacker, C. Miller, D. Nock, A.P. Ravikumar, Allison Bates, Anna Stefanopoulou, E Grubert, D.M Kammen, M. Pastor, S.Z, Attari, S. Carley, D.L Clark, D. Dean-Ryan, U. Kosar, Kerry Bowie, Tina Johnson

ETI Publications

Comprehensive and meaningful inclusion of marginalized communities within the research enterprise will be critical to ensuring an equitable, technology-informed, clean energy transition. We provide five key action items for government agencies and philanthropic institutions to operationalize the commitment to an equitable energy transition.

Enabling Daily Tracking Of Individual’S Cognitive State With Eyewear, Soha Rostaminia

Doctoral Dissertations

Research studies show that sleep deprivation causes severe fatigue, impairs attention and decision making, and affects our emotional interpretation of events, which makes it a big threat to public safety, and mental and physical well-being. Hence, it would be most desired if we could continuously measure one’s drowsiness and fatigue level, their emotion while making decisions, and assess their sleep quality in order to provide personalized feedback or actionable behavioral suggestions to modulate sleep pattern and alertness levels with the aim of enhancing performance, well-being, and quality of life. While there have been decades of studies on wearable devices, we …

Unobtrusive Assessment Of Upper-Limb Motor Impairment Using Wearable Inertial Sensors, Brandon R. Oubre

Doctoral Dissertations

Many neurological diseases cause motor impairments that limit autonomy and reduce health-related quality of life. Upper-limb motor impairments, in particular, significantly hamper the performance of essential activities of daily living, such as eating, bathing, and changing clothing. Assessment of impairment is necessary for tracking disease progression, measuring the efficacy of interventions, and informing clinical decision making. Impairment is currently assessed by trained clinicians using semi-quantitative rating scales that are limited by their reliance on subjective, visual assessments. Furthermore, existing scales are often burdensome to administer and do not capture patients' motor performance in home and community settings, resulting in a …

Synthesis And Assembly Of Polymer Materials At Interfaces, Xiaoshuang Wei

Doctoral Dissertations

The overarching goal of the thesis is to understand growth and assembly of polymer materials at interfaces. Chapter 2 and Chapter 3 study simultaneous polymer growth and assembly at fluid interfaces, where in-situ photopolymerization and vapor phase deposition were utilized to grow polymers, respectively. Chapter 4 leverages capillary condensation to pattern polymer growth at solid substrates. Chapter 1 provides background information on polymer materials at interfaces, and vapor phase deposition method (initiated chemical vapor deposition, iCVD) to grow polymers. This chapter also reviews polymer thin film wetting, and colloidal assemblies at interfaces. In Chapter 2, we demonstrate the preparation …

Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian

Doctoral Dissertations

The self-assembly of charged macromolecules forms the basis of all life on earth. From the synthesis and replication of nucleic acids, to the association of DNA to chromatin, to the targeting of RNA to various cellular compartments, to the astonishingly consistent folding of proteins, all life depends on the physics of the organization and dynamics of charged polymers. In this dissertation, I address several of the newest challenges in the assembly of these types of materials. First, I describe the exciting new physics of the complexation between polyzwitterions and polyelectrolytes. These materials open new questions and possibilities within the context …

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale. Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …

Enabling Nanoimprint Lithography Techniques Across Multiple Manufacturing Processes, Vincent Einck

Doctoral Dissertations

Advanced nanooptics in the areas of flat lenses, diffractive elements, and tunable emissivity require a route to high throughput manufacturing. Nanooptics are often demanding of high refractive index materials, nanometer precision and ease of fabrication. Nanoimprint lithography (NIL) is a low-cost, high throughput manufacturing technique beginning to be realized in commercial industry.^1,2 The NIL process is an ideal manufacturing candidate due to its ability to have a fast process time, efficient use of materials, repeatability and high precision while also having wide diversity of potential structures and material choices. Appling NIL techniques to other facets of manufacturing enable the …

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 …

Remote Sensing Of High Latitude Rivers: Approaches, Insights, And Future Ramifications, Merritt E. Harlan

Doctoral Dissertations

High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensing, and the availability of satellite imagery can provide ways to overcome these challenges. Through combining various forms of fieldwork, modeling, deep learning, and remote sensing, we contribute methodologies and knowledge to three key challenges associated with better understanding high latitude rivers. In the first chapter, we combine field data that can be rapidly deployed with …

Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona

Doctoral Dissertations

The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

X-Band Phased-Array Weather-Radar Polarimetry Testbed, William Heberling Iv

Doctoral Dissertations

Phased-array weather radar have potential to replace reflector dish radar in major weather radar networks such as NEXRAD, providing faster update times and greater scan flexibility. However, the use of electronic scanning introduces polarization errors on weather radar measurables, requiring polarimetric bias calibration. The sources of polarimetric bias have been described theoretically, but experimental verification is still limited. Additionally, no standard method of calibration for polarimetric bias exists for phased-arrays. Therefore, the University of Massachusetts Amherst (UMass) presents a fully operational X-Band phased-array weather radar polarimetric testbed. The testbed evaluates the calibration of a planar dual-polarization X-band phased-array radar through …

Modeling Chain Packing In Complex Phases Of Self-Assembled Block Copolymers, Anugu Abhiram Reddy

Doctoral Dissertations

Block copolymer (BCP) melts undergo microphase seperation and form ordered soft matter crystals with varying domain shapes and symmetries. We study the con- nection between diblock copolymer molecular designs and thermodynamic selection of ordered crystals by modeling features of variable sub-domain geometry filled with individual blocks within non-canonical sphere-like and network phases that together with layered, cylindrical and canonical spherical phases forms “natural forms” of self- assembled amphiphilic soft matter at large. First, we present a model to revise our understanding of optimal Frank-Kasper sphere-like morphologies by advancing the- ory to account for varying domain volumes. We then develop generic …

Moving Polygon Methods For Incompressible Fluid Dynamics, Chris Chartrand

Doctoral Dissertations

Hybrid particle-mesh numerical approaches are proposed to solve incompressible fluid flows. The methods discussed in this work consist of a collection of particles each wrapped in their own polygon mesh cell, which then move through the domain as the flow evolves. Variables such as pressure, velocity, mass, and momentum are located either on the mesh or on the particles themselves, depending on the specific algorithm described, and each will be shown to have its own advantages and disadvantages. This work explores what is required to obtain local conservation of mass, momentum, and convergence for the velocity and pressure in a …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Synthesis, Fabrication, And Assembly Of Mesoscale Polymer Filaments, Dylan M. Barber

Doctoral Dissertations

Mesoscale materials, with feature sizes in the range of one hundred nanometers to tens of micrometers, are ubiquitous in Nature. In organisms, mesoscale building blocks connect the properties of underlying molecular and nanoscructures to those of macroscale, organism-scale materials through hierarchical assemblies of recurring structural motifs. The collective action of large numbers of mesoscale features can afford stunning features like the structural color of the morpho butterfly wing, calcium ion-mediated movement in muscle, and wood structures like xylem that can support enormous external compressive loads and negative internal pressure to transport nutrients throughout an organism. In synthetic systems, the design, …

Tailoring Interfaces And Composition For Stable And Efficient Perovskite Solar Cells, Hamza Javaid

Doctoral Dissertations

Metal halide perovskite solar cells (PSCs) have revolutionized the field of thin film photovoltaics. Within a decade, the power conversion efficiencies (PCEs) have increased at a phenomenal rate, rising from 3.8% to more than 25% in single-junction devices, moving them ahead of the current silicon-based technology. The high efficiencies of perovskite solar cells (PSCs) and their other unique properties arise from a combination of organic and inorganic components and electronic-ionic conduction, making them excellent candidates for a plethora of applications. However, PSCs face a significant—and ironic—roadblock to commercialization: these light-harvesting materials degrade under sunlight—the very condition they would need …