Engineering Commons^™

Systematic Review Of Driver Distraction In The Context Of Advanced Driver Assistance Systems (Adas) & Automated Driving Systems (Ads), Apoorva Pramod Hungund

Masters Theses

Advanced Vehicle Systems promise improved safety and comfort for drivers. Steady advancements in technology are resulting in increasing levels of vehicle automation capabilities, furthering safety benefits. In fact, some of these vehicle automation systems are already deployed and available, but with promised benefits, such systems can potentially change driving behaviors. There is evidence that drivers have increased secondary task engagements while driving with automated vehicle systems, but there is a need for a clearer scientific understanding of any potential correlations between the use of automated vehicle systems and potentially negative driver behaviors.

Therefore, this thesis aims to understand the state …

Formally Verifiable Synthesis Flow In Fpgas, Anurag V. Muttur

Masters Theses

FPGAs are used in a wide variety of digital systems. Due to their ability to support parallelism and specialization, these devices are becoming more commonplace in fields such as machine learning. One of the biggest benefits of FPGAs, logic specialization, can lead to security risks. Prior research has shown that a large variety of malicious circuits can snoop on sensitive user data, induce circuit faults, or physically damage the FPGA. These Trojan circuits can easily be crafted and embedded in FPGA designs. Often, these Trojans are small, consume little power in comparison to the target circuit, and are hard to …

Integration Of Digital Signal Processing Block In Symbiflow Fpga Toolchain For Artix-7 Devices, Andrew T. Hartnett

Masters Theses

The open-source community is a valuable resource for many hobbyists and researchers interested in collaborating and contributing towards publicly available tools. In the area of field programmable gate arrays (FPGAs) this is no exception. Contributors seek to reverse-engineer the functions of large proprietary FPGA devices. An interesting challenge for open-source FPGA engineers has been reverse-engineering the operation and bitstreams of digital signal processing (DSP) blocks located in FPGAs. SymbiFlow is an open-source FPGA toolchain designed as a free alternative to proprietary computer-aided design tools like Xilinx’s Vivado. For SymbiFlow, mapping logical multipliers to DSP blocks and generating DSP block bitstreams …

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 …

Predicting Water Quality Vulnerability Under Climate Change With Machine Learning, Khanh Thi Nhu Nguyen

Doctoral Dissertations

Water quality deterioration is a global and pervasive issue due to pollution caused by industrialization, urbanization, agriculturalization, and human population growth in the modern era. This issue is even more challenging in the context of climate change due to warming temperatures and the intensification of precipitation. Therefore, assessing the potential impacts of climate change on water quality is a concern. Assessment is necessary so that planners can prepare for and reduce the negative impacts on water quality. At present, climate change impact assessment frameworks are relatively adolescent. Most studies rely on climate projections from General Circulation Models for simulations of …

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 …

Design Artifacts As Externalized Mental Models Of Children’S Science Concept Development, Christine Mcgrail

Doctoral Dissertations

The Next Generation Science Standards (NGSS) calls for the integration of the practices of science and engineering across all science disciplines beginning in the early elementary grades. Science and engineering education research has determined that engineering design is a productive means for promoting understanding of science concepts. However, design artifacts created during engineering design problem-solving have not received sufficient attention for their potential to embody children’s science understanding. The aim of this study was to examine how conceptual development of the concepts of force and motion was instantiated in design artifacts by early elementary age children engaged in engineering design. …

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 …

Data Scarcity In Event Analysis And Abusive Language Detection, Sheikh Muhammad Sarwar

Doctoral Dissertations

Lack of data is almost always the cause of the suboptimal performance of neural networks. Even though data scarce scenarios can be simulated for any task by assuming limited access to training data, we study two problem areas where data scarcity is a practical challenge: event analysis and abusive content detection} Journalists, social scientists and political scientists need to retrieve and analyze event mentions in unstructured text to compute useful statistical information to understand society. We claim that it is hard to specify information need about events using keyword-based representation and propose a Query by Example (QBE) setting for event …

Experimental Investigation Of Clay Aggregate And Granular Biofilm Behavior, Tao Jiang

Doctoral Dissertations

Clay minerals are a class of phyllosilicates as the major solid constituents in cohesive fine-grained soils (e.g., clays). Owing to their tiny size (i.e., < 2 μm), high aspect ratio, and active surface properties that inherit from the geological process, clay minerals can extensively interact with other suspended matter (e.g., exoployemers, microorganisms) and dissolved ions via the process of flocculation and aggregation, resulting in the formation of larger, porous cohesive particulate aggregates or flocs. Such a complex mechanism of microscale particle interaction generates significant challenges for understanding the bulk clay behavior as a particulate system. In order to better characterize the flocculation and aggregation of clay minerals under various stimuli and to understand the underlying mechanism of particle interactions, particle/aggregate size kinetics of flocculated suspensions of illite, a representative 2:1 clay mineral abundant in marine soils, are studied with varied ionic strength induced by monovalent salt (NaCl), pH, and hydrodynamic shearing in the first phase of this research. Furthermore, a new statistical data binning method termed “bin size index” (BSI) was employed to determine the probability density function (PDF) distributions of flocculated illite suspensions. The statistical results demonstrate that the size kinetics of flocculated illite suspensions is chiefly controlled by the face-to-face and edge-to-face interparticle interactions under the mutual effects of ionic strength and pH, while the hydrodynamic shearing has minimal effects on the variation of particle size groups. In the second phase of this research, the mechanics of clay aggregates are studied using an innovative measurement technique and analytical approach. Individual clay minerals prepared with different mineralogy and salinities are tested via unconfined compression, which shows that the increasing ionic strength can improve the strength and stiffness of clay aggregates, which are further affected by the mineralogical compositions and dominant microfabric in different water chemistry. In the final phase of this research, a collaborative study with an environmental engineer on an NSF CAREER project was conducted to investigate the mechanical behavior of macroscale, light-induced oxygenic granules (biofilm aggregates) using the same technique and analytics developed for the individual clay aggregates. The findings are expected to provide reference values to subsequent studies and engineering practices associated with the water treatment process.

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 …

Quantifying Elasto-Adhesion And Fluid-Elastic Dynamics For Ultra-Soft Hydrogel Interfaces, Hongbo Fu

Doctoral Dissertations

Hydrogels are constructed with polymer networks swollen with water, which are soft and with much smaller shear moduli than bulk moduli. Due to the similar moduli to biological tissues, synthetic hydrogels have been used for biological applications. While interfacial properties are important for many of the applications of soft materials, quantifying these properties is challenging for ultra-soft materials. Ultra-softness causes difficulties in measuring interfacial properties with conventional force-based methods. For example, soft specimens deform largely under gravity and external forces, and thus the assumptions of the established methods are invalid. Additionally, many of the applications for hydrogels require them to …

Lateral Response Of Cold-Formed Steel Diaphragms With Variable Sheathing, Hernan Castaneda

Doctoral Dissertations

Cold-formed steel (CFS) framed buildings and subsystems have demonstrated safe and reliable performance while under lateral and seismic loads. Combined with their structural efficiency, this makes CFS-framed buildings popular choice even in high seismic zones. However, due to the complexity in response of CFS members and their interaction in subsystem and system levels, more research needs to be conducted to better understand the overstrength in the system, as well as the contribution of non-structural components to the overall response of the building. The lateral force resisting system (LFRS) of CFS framed buildings consist primarily of shear walls and diaphragms. The …

Optimizing Transportation Systems With Information Provision, Personalized Incentives And Driver Cooperation, Sayeeda Ayaz

Doctoral Dissertations

Poor performance of the transportation systems has many detrimental effects such as higher travel times, increased travel costs, higher energy consumption, and greenhouse gas emissions, etc. This thesis optimizes the transportation systems by addressing the traffic congestion problem and climate change impact resulting from the inefficient operation of these systems. I first focus on the key player of the transportation systems e.g., human being/traveler, and model travelers' route choice behavior with real-time information. In this study, I define looking-ahead behavior in route choice as a traveler's taking into account future diversion possibilities enabled by real-time information in a network with …

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 …

Applications Of Thermal Energy Storage With Electrified Heating And Cooling, Erich Ryan

Masters Theses

With a clear correlation between climate change and rising CO₂ emissions, decarbonization has garnered serious interest in many sectors to limit the adverse effects of global warming. Heating and cooling systems have been a focus of decarbonization efforts, with heat pumps becoming more popular in the United States and abroad. In fact, heating, ventilation, and air conditioning accounts for nearly 27% of total energy use in the United States [1]. Ground source heat pumps (GSHP) utilizing borehole heat exchangers (BHE) have been shown to be an effective method of electrifying heating and cooling systems, maintaining some of the best …

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 …

Measuring Accessibility To Food Services To Improve Public Health, Efthymia Kostopoulou

Masters Theses

Food accessibility has lately been of primary interest given its impact on public health outcomes. This thesis illustrates the gaps in food access by applying spatial analysis in Massachusetts accounting for a variety of demographic and socioeconomic factors. The number of grocery stores, farmers markets, and convenience stores within 1/4 and 1 mile of the Census tracts’ centroids are the two accessibility metrics used in the spatial analysis. In addition, a regression model is developed using the Gradient Boosting machine learning method to show the relationship between the socioeconomic factors and the number of grocery stores within 1 mile of …

Theory And Analysis Of Backprojection Processing For Interferometric Sar, Marc Closa Tarres

Masters Theses

Synthetic Aperture Radar (SAR) is a well-known radar technique widely used for 2D and 3D imaging since the 1960s. SAR systems offer all-weather, day and night, high-resolution imaging by using the motion of the antenna over the target of interest. By later use of signal processing techniques, the received echoes can be put back together using precise knowledge of the system location and geometry to obtain the distinct high-resolution SAR imagery.

Moreover, when the system is equipped with multiple antennas, topography and topographic changes in the region of interest can be inferred using interferometric techniques.

The Microwave Remote Sensing Laboratory …

Data Parallel Frameworks For Training Machine Learning Models, Guoyi Zhao

Doctoral Dissertations

Machine learning is the study of computer algorithms that focuses on analyzing and interpreting patterns and structures in data. It has been successfully applied to many areas in computer science and achieved state-of-the-art results to enable learning, reasoning, and decision-making without human interactions. This research aims to develop innovated data parallel frameworks to accommodate the computing resources to parallelize different machine learning and deep learning algorithms and speed up the training. To achieve that, we explore three interesting frameworks in this dissertation: (1) Sync-on-the-fly framework for gradient descent algorithms on transient resources; (2) Asynchronous Proactive Data Parallel framework for both …

Extracellular Matrix Stiffness As A Cue To Shape Phenotypic Evolution Of Triple Negative Breast Cancer, Ning-Hsuan Tseng

Doctoral Dissertations

Accumulation of epigenetic and genetic changes results in oncogenic transformation of epithelial cells. During breast cancer metastasis, while the extracellular matrix (ECM) becomes stiffer, breast cancer cells transmit mechanical forces into intracellular tension and activate signaling pathways influencing growth, migration, and metastasis. Once cancer cells detach from the primary tumor, they intravasate into the vasculature, survive in the circulation, extravasate and adapt to a new microenvironment of a secondary site. Throughout the process, only a very small population of cancer cells survive, and they are likely to reside at the metastatic sites for several years. The most frequent metastatic sites …

Development Of In Vitro Bone Organoid Models For The Recapitulation Of Bone Complexity, Yongkuk Park

Doctoral Dissertations

Osteoporosis is the most common skeletal disorder that thins and weakens the bones, yet the detailed mechanisms remain poorly understood and limited therapeutic options are available. This can be attributed to the lack of relevant experimental models that can recapitulate the bone complexity and bone remodeling. Mouse models have identified many critical genes and molecules regulating bone metabolism but are limited to studying detailed cellular and molecular processes due to anatomical inaccessibility and restricted ability to manipulate bone structure. Considerable efforts have been made to generate physiologically relevant models by using synthetic and biomaterial-based 3D scaffolds. However, there are no …

Additive Manufacturing Of Sub-Micron Features And Mechanical Linkages, David K. Limberg

Doctoral Dissertations

In recent years material constraints have become the limiting factor in several fields, including batteries, robotics, and medicine, and these needs have prompted the development of materials with programmable properties. To this end, much effort has been dedicated to designing metamaterials that have unprecedented optical, mechanical, and thermal properties, along with systems for additive manufacturing to build their complex structures with high precision and throughput. The field of additive manufacturing has proved to be a platform for innovation across many industries yet is still limited with regards to feature sizes, print rates, and diversity of materials. Mechanical devices like linkages …

Phase Behavior Of Oppositely Charged Polymerized Ionic Liquids In Solution, Bulk, And Crosslinked Network States, Minjung Lee

Doctoral Dissertations

Polymerized ionic liquids (PILs), a class of polyelectrolytes, are fascinating materials for various applications utilizing ion transport, especially due to their advantageous properties including negligible vapor pressure, low flammability, thermal stability, high conductivity, and wide electrochemical stability windows. Furthermore, PILs are tunable in their properties such as ionic conductivity, glass transition temperature (T_g), solubility, and (electro-)chemical stability. In this thesis, we focus on fundamental studies of phase behaviors of PILs in the solution and bulk states in chapters 2 and 3, respectively. Specifically, non-aqueous systems are used to study the effect of solvent quality in the regime …

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 …

The Influence Of Flow Mechanotransduction On Endothelial Cells In The Lymphatic Valve Sinus, Joshua Daniel Hall

Doctoral Dissertations

Fluid flow in the cardiovascular and lymphatic systems influences the phenotype of endothelial cells that line the interior to the vessel via mechanotransduction. Geometric features in a vessel such as curvature, bifurcation, and valves promote heterogeneous fluid flow profiles, inducing a heterogeneous endothelial phenotype within a vessel region. Certain flow conditions are associated with vascular dysfunction, and diseases such as atherosclerosis preferentially develop in areas of flow disturbance. Lymphatic vessels are highly analogous to blood vessels, although lymphatic flow characteristics and its effect on lymphatic endothelial cells (LECs) via mechanotransduction have been comparatively less examined. The most significant geometric features …

Enhancing Management Of Built And Natural Water And Sanitation Systems With Data Science, Nelson Da Luz

Doctoral Dissertations

In the age of the data revolution, the civil engineer can enhance the management of infrastructure systems using new techniques focused on data. This dissertation present three studies in which data science approaches are used to enhance management of water and sanitation systems in both the built and natural environments. Chapters 1 and 2 focus on improving methods for data collection relating to water quality monitoring. In Chapter 1, the efficacy of different water quality sampling program designs is evaluated as the programs relate to meeting monitoring goals. Considerations include how timing, location, and distribution system operations can affect monitoring …

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, …