Digital Commons Network^™

Fabrication Of Al:Hfo2 Gate Dielectric Mosfets, George Mcmurdy

Theses

Replacing the traditional SiO2 gate oxide in a MOSFET with ferroelectric HfO2 creates a 1T memory device referred to as a FeFET. The bi-stable polarization states cause a retained threshold voltage shift known as the memory window. Ferroelectric HfO2 offers a number of material and electrical advantages over perovskite based ferroelectrics such as PZT or SBT. Due to its use as a high-k dielectric, the ALD capability and etch characteristics of hafnium oxide are well documented. Ferroelectric HfO2 has been shown to be thermally stable up to 1000 C, making gate first FeFET processes feasible. Electrically, HfO2 is capable of …

Vector Spaces For Multiple Modal Embeddings, Sabarish Gopalakrishnan

Theses

Deep learning has enabled great advances in the field of natural language processing, computer vision and pattern recognition in general. Deep learning frameworks have been very successful in performing classification, object detection, segmentation and translation. Before objects can be processed, a vector representation of that object needs to be created. For example, sentences and images can be encoded with a sent2vec and image2vec function respectively in preparation for input to a machine learning framework. Neural networks are able to learn efficient vector representation of images, text, audio, videos and 3D point clouds. However, the transfer of knowledge from one modality …

Community Participation In City Planning And Development: Towards Enhancing The Pedestrian Experience, Amro Anabtawi

Theses

This project is about developing a digital platform that facilitates collecting, processing, and utilizing input from community members to enhance the quality and experience of their own built environment based on their life pattern, preferences, or aspiration and in consideration of the urban requirements that are associated with their needs. As such, the platform is meant to enhance public participation in planning and urban development decisions and practices aiming to meet the needs of the community members. Focused on the pedestrian experience, the proposed platform is meant to complement the ordinary channels of communication between community members and city planning …

Rotor Current Control Design For Dfig-Based Wind Turbine Using Pi, Flc And Fuzzy Pi Controllers, Omar Al-Zabin

Theses

Due to the rising demand for electricity with increasing world population, maximizing renewable energy capture through efficient control systems is gaining attention in literature. Wind energy, in particular, is considered the world’s fastest-growing energy source it is one of the most efficient, reliable and affordable renewable energy sources. Subsequently, well-designed control systems are required to maximize the benefits, represented by power capture, of wind turbines.

In this thesis, a 2.0-MW Doubly-Fed Induction Generator (DFIG) wind turbine is presented along with new controllers designed to maximize the wind power capturer. The proposed designs mainly focus on controlling the DFIG rotor current …

Investigating Dynamic Stiffening And Softening Of A System Of Colloids Cross-Linked Via Polymers, Elisabeth Rennert

Theses

With the goal of ultimately deciphering the design principles for biomimetic materials that can autonomously stiffen and soften, we investigate colloids as a model system that can dynamically transition from fluid-like (sol) to gel-like (gel) when crosslinked with polymers. The model was first developed with colloids only, interacting via a Lennard-Jones potential and undergoing Brownian dynamics, with experimentally relevant parameters, to test and refine the simulation. We then added polymer crosslinkers that connect the colloids via an attractive spring force, and investigate resulting collective properties, such as the time needed for the formation of system spanning networks and the elastic …

Point Spread Function And Modulation Transfer Function Engineering, Jacob Wirth

Theses

A novel computational imaging approach to sensor protection based on point spread function (PSF) engineering is designed to suppress harmful laser irradiance without significant loss of image fidelity of a background scene. PSF engineering is accomplished by modifying a traditional imaging system with a lossless linear phase mask at the pupil which diffracts laser light over a large area of the imaging sensor. The approach provides the additional advantage of an instantaneous response time across a broad region of the electromagnetic spectrum. As the mask does not discriminate between the laser and desired scene, a post-processing image reconstruction step is …

Human Auditory Discrimination Of Bottlenose Dolphin Signature Whistles Masked By Noise: Investigating Perceptual Strategies For Anthropogenic Noise Pollution, Evan L. Morrison

Theses

Anthropogenic masking noise in the world’s oceans is known to impede many species’ ability to perceive acoustic signals, but little research has addressed how this noise pollution affects the detection of bioacoustic signals used for communication. Bottlenose dolphins (Tursiops truncatus) use signature whistles which contain identification information. Past studies have shown that human participants can be used as models for dolphin hearing, but most previous research investigated echolocation. In Experiment 1, human participants were tested on their ability to auditorily discriminate among signature whistles from three dolphins. Participants’ performance was nearly errorless (M = 98.8%). In Experiment 2, participants identified …

Pulsed Photonic Sintering Of Lithium Doped Potassium Sodium Niobate (Knn) For Flexible Energy Harvesting Devices, Sara Hernandez Juarez

Theses

In this work, KNNL was sintered as a lead-free alternative to PZT using a pulsed photonic sintering method. The KNNL post-sintering composition remained close to theoretical composition indicating minimal volatilization of alkali metals. Furthermore, a remnant polarization was observed in the processed material. Energy and time demands were greatly reduced using the pulsed photonic sintering method versus conventional furnace sintering.

Piezoelectric materials can produce electric current when bent or compressed. Currently lead zirconium titanate (PZT) is the most widely used piezoelectric material. A promising lead-free alternative is sodium potassium niobate (KNN), which can be doped with lithium (KNNL) to improve …

Impact Of Education Policies On Stem Education For Deaf/Hard Of Hearing Students, Valerie Horn

Theses

The thesis is focused on STEM education and education policy for students who are deaf/hard of hearing. The research broadly examines the impacts of legislation such as the Individuals with Disabilities Education Act (IDEA) and No Child Left Behind (NCLB) on science education for deaf/hard of hearing students. Additionally, the thesis argues that the benefits of greater accessibility in STEM for deaf/hard of hearing students would be beneficial.

The findings considered STEM education in the deaf/hard of hearing community and how their perspectives and practices may improve science education. Deaf students’ personal experiences and available services in schools may spark …

Water Quality And Algal Bloom Sensing From Multiple Imaging Platforms, Ryan Ford

Theses

Harmful cyanobacteria blooms have been increasing in frequency throughout the world resulting in a greater need for water quality monitoring. Traditional methods of monitoring water quality, such as point sampling, are often resource expensive and time consuming in comparison to remote sensing approaches, however the spatial resolution of established water remote sensing satellites is often too coarse (300 m) to resolve smaller inland waterbodies. The fine scale spatial resolution and improved radiometric sensitivity of Landsat satellites (30 m) can resolve these smaller waterbodies, enabling their capability for cyanobacteria bloom monitoring.

In this work, the utility of Landsat to retrieve concentrations …

Modeling Composite Cytoskeletal Networks Using Effective Medium Theory, Jacob Wales

Theses

The mechanical response of most living cells arises from their cytoskeleton, a polymeric scaffold made of different types of biopolymers and associated crosslinking proteins.

We used rigidity percolation theory to devise a set of models using an effective medium approach to study the mechanical properties of cytoskeleton-like networks. We first successfully recreated a model which obtains the mechanical response of a disordered network of a single filament type, given the constitutive material properties of individual filaments and the network geometry. In this model, wherever two filaments cross they are crosslinked together, and these crosslinkers allow for energy free rotation of …

The Characterization Of Earth Sediments Using Radiative Transfer Models From Directional Hyperspectral Reflectance, Rehman S. Eon

Theses

Remote sensing techniques are continuously being developed to extract physical information about the Earth’s surface. Over the years, space-borne and airborne sensors have been used for the characterization of surface sediments. Geophysical properties of a sediment surface such as its density, grain size, surface roughness, and moisture content can influence the angular dependence of spectral signatures, specifically the Bidirectional Reflectance Distribution Function (BRDF). Models based on radiative transfer equations can relate the angular dependence of the reflectance to these geophysical variables. Extraction of these parameters can provide a better understanding of the Earth’s surface, and play a vital role in …

Tool For The Analysis Of Human Interaction With Two-Dimensional Printed Imagery, Anjali K. Jogeshwar

Theses

The study of human vision can include our interaction with objects. These studies include behavior modeling, understanding visual attention and motor guidance, and enhancing user experiences. But all these studies have one thing in common. To analyze the data in detail, researchers typically have to analyze video data frame by frame. Real world interaction data often comprises of data from both eye and hand. Analyzing such data frame by frame can get very tedious and time-consuming. A calibrated scene video from an eye-tracker captured at 120 Hz for 3 minutes has over 21,000 frames to be analyzed.

Automating the process …

Collaborative Uav Surveillance, Winston Smith

Theses

Autonomous collaborative robotics is a topic of significant interest to groups such as the Air Force Research Lab (AFRL) and the National Aeronautics and Space Administration (NASA). These two groups have been developing systems for the operation of autonomous vehicles over the past several years, but each system has several critical drawbacks. AFRL’s Unmanned Systems Autonomy Services (UxAS) supports pathfinding for multiple tasks performed by groups of vehicles, but has no formal verification, very little physical flight time, and no concept of collision avoidance. NASA’s Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) has collision avoidance, partial formal …

Human Activity Recognition And Prediction Using Rgbd Data, Paul Dixon Coen

Theses

Being able to predict and recognize human activities is an essential element for us to effectively communicate with other humans during our day to day activities. A system that is able to do this has a number of appealing applications, from assistive robotics to health care and preventative medicine. Previous work in supervised video-based human activity prediction and detection fails to capture the richness of spatiotemporal data that these activities generate. Convolutional Long short-term memory (Convolutional LSTM) networks are a useful tool in analyzing this type of data, showing good results in many other areas. This thesis’ focus is on …

Deep Grassmann Manifold Optimization For Computer Vision, Breton Lawrence Minnehan

Theses

In this work, we propose methods that advance four areas in the field of computer vision: dimensionality reduction, deep feature embeddings, visual domain adaptation, and deep neural network compression. We combine concepts from the fields of manifold geometry and deep learning to develop cutting edge methods in each of these areas. Each of the methods proposed in this work achieves state-of-the-art results in our experiments. We propose the Proxy Matrix Optimization (PMO) method for optimization over orthogonal matrix manifolds, such as the Grassmann manifold. This optimization technique is designed to be highly flexible enabling it to be leveraged in many …

Fabrication Of Resistive Thermo-Optic Heaters On Silicon Photonic Integrated Circuits, Venkatesh Deenadayalan

Theses

A reliable process for the fabrication of active heater components on passive silicon photonic integrated circuits is presented in this thesis. The heater components enable modulation of the photonic circuits’ optical response through the concept of Joule heating. This thesis proposes and successfully establishes an optimized process that can be entirely carried out in an academic clean room facility. The entire cycle of design, simulation and modelling, fabrication and testing is covered. Target lithographic resolution of 300 nm was achieved through process optimization (using a spin on carbon hard mask) by using i-line 365 nm lithography. A very good resolution …

A Patient-Specific Approach For Breast Cancer Detection And Tumor Localization Using Infrared Imaging, Jose Luis Gonzalez Hernandez

Theses

Breast cancer (BC) is the most common cancer among women in the United States; approximately one out of every 24 women die of related causes. BC screening is a critical factor for improving patient prognosis and survival rate. Infrared (IR) thermography is an accurate, inexpensive and operator independent modality that is not affected by tissue density as it captures surface temperature variations induced by the presence of tumors. A novel patient-specific approach for IR imaging and simulation is proposed. In this work, multi-view IR images of isolated breasts are obtained in the prone position (face down), which allows access to …

Scanning Single Shot Detector For Math In Document Images, Parag Shrikrishna Mali

Theses

We introduce the Scanning Single Shot Detector (ScanSSD) for detecting both embedded and displayed math expressions in document images using a single-stage network that does not require page layout, font, or, character information. ScanSSD uses sliding windows to generate sub-images of large document page images rendered at 600 dpi and applies Single Shot Detector (SSD) on each sub-image. Detection results from sub-images are pooled to generate page-level results. For pooling sub-image level detections, we introduce new methods based on the confidence scores and density of detections. ScanSSD is a modular architecture that can be easily applied to detecting other objects …

Gender Bias In Managerial Positions In The Private Sector In Kosovo, Diona Hoxha

Theses

This project analyzes gender bias and gender barriers in managerial positions by focusing on private the sector in Kosovo. The study specifically analyzes the barriers that women in the private sector face, such as disregarding qualifications, traditional gender based occupations, discriminatory language in job ads, maternity leave and the lack of contracts that make the employee-employer relationship legally binding. It further elaborates on the concept of gender quotas in management and analyzes their effects in managerial positions and the workplace in general. The study also analyzes best practices outside Kosovo, in which gender equality has been integrated as a part …

Predicting The Emotional Intensity Of Tweets, Intisar M. Alhamdan

Theses

Automated interpretation of human emotion has become increasingly important as human-computer interactions become ubiquitous. Affective computing is a field of computer science concerned with recognizing, analyzing and interpreting human emotions in a range of media, including audio, video, and text. Social media, in particular, are rich in expressions of people's moods, opinions, and sentiments. This thesis focuses on predicting the emotional intensity expressed on the social network Twitter. In this study, we use lexical features, sentiment and emotion lexicons to extract features from tweets, messages of 280 characters or less shared on Twitter. We also use a form of transfer …

Making Tricks More Accessible: Empowering Adults With Intellectual Disabilities To Create E-Textiles, Taylor Gotfrid

Theses

E-textiles are a newly emerging technology that can be seen in consumer, educational, and hackerspace environments. Specifically, the development of e-textiles requires a minimum level of familiarity with a variety of concepts; one of which is circuit design and prototyping.

Unfortunately, people with disabilities are rarely included in the design and development of e- textiles, so methods to manipulate these wearable interactive technologies are not always accessible to creators with disabilities. Therefore, we conducted this study to begin understanding how adults with intellectual disabilities perceive and interact with this new type of electronic technology.

This research explores an accessible process …

Identifying Galaxy Mergers With Quantitative Morphological Parameters In Simulated James Webb Space Telescope Images, Caitlin Rose

Theses

Mergers play an important role in the formation and evolution of galaxies by triggering starbursts, AGN activity, and morphological transitions from disks to ellipticals. They can also cause morphological disturbances in a galaxy’s appearance, such as double nuclei, tidal tails, and other asymmetries, which can appear before or after a merger has occurred. Therefore, one way to identify low redshift galaxy mergers is to search for these morphological signatures via quantitative morphological parameters, which quantify a galaxy’s light distribution (such as Sérsic profiles, or the CAS system, G and M20, and the MID statistics). However, for high redshift galaxies, these …

Registration Of Diffusion Tensor Images In Log-Euclidean And Euclidean Space, Kevin Tuttle

Theses

Diffusion Tensor Imaging is a type of Magnetic Resonance Imaging that allows for the examination of brain connectivity and axonal integrity. Diffusion Tensor Images are created by capturing Diffusion-Weighted MRI images with specific RF pulses, inputing the images and the RF pulse gradient vectors into a set of equations, and solving the equations with linear algebra. To compare one DTI image with another, the images can be aligned using Image Registration. Image Registration works by defining a metric that describes the similarity between two images and iteratively transforming one of the images until the similarity measure is minimized. Existing methods …

Ultrafast Laser Polishing For Optical Fabrication, Lauren L. Taylor

Theses

Next-generation imaging systems for consumer electronics, AR/VR, and space telescopes require weight, size, and cost reduction while maintaining high optical performance. Freeform optics with rotationally asymmetric surface geometries condense the tasks of several spherical optics onto a single element. They are currently fabricated by ultraprecision sub-aperture tools like diamond turning and magnetorheological finishing, but the final surfaces contain mid-spatial-frequency tool marks and form errors which fall outside optical tolerances. Therefore, there remains a need for disruptive tools to generate optic-quality freeform surfaces.

This thesis work investigates a high-precision, flexible, non-contact methodology for optics polishing using femtosecond ultrafast lasers. Femtosecond lasers …

Shadow Detection In Aerial Images Using Machine Learning, Prasanna Reddy Pulakurthi

Theses

Shadows are present in a wide range of aerial images from forested scenes to urban environments. The presence of shadows degrades the performance of computer vision algorithms in a diverse set of applications such as image registration, object segmentation, object detection and recognition. Therefore, detection and mitigation of shadows is of paramount importance and can significantly improve the performance of computer vision algorithms in the aforementioned applications. There are several existing approaches to shadow detection in aerial images including chromaticity methods, texture-based methods, geometric, physics-based methods, and approaches using neural networks in machine learning.

In this thesis, we developed seven …

Prediction Of Treatment Target For Ventricular Tachycardia Using Multi-Task Machine Learning, Vishwanath Raman

Theses

Ventricular tachycardia (VT) is a type of abnormally fast heart rate that arises from abnormal electrical conductivity in the ventricles of the heart. Most VTs involve an abnormal origin of electrical activation inside the ventricles. An effective way to treat VT is catheter ablation that destroys the origin of VT by radiofrequency energy. To accurately localize the origin of VT therefore is an important factor for the success of ablation therapy. An Electrocardiogram (ECG) is a recording of the electrical activity of the heart with features that correspond to stages in the cardiac conduction system. Earlier works have shown that …

Low-Rank Multivariate General Linear Model And One-Way Random Effect Models For Brain Response Analysis, Yidan Yang

Theses

Human brain is the central organ of human nervous system, the activity in brain becomes a significant topic in neuroscience and medical science field. New techniques for detecting brain regions activity has been developed very fast in recent year, a basic method is functional MRIs which can measure brain activities based on oxygen level in bloodstream. This work will introduce a new approach to analyze brain region relationships through low-rank multivariate general linear model and one-way random effect model. By using fMRI and low-rank multivariate general liner model, this model contains a new penalized optimization function, which can lead to …

Analyzing Binary Black Hole Spacetimes, Jam Sadiq

Theses

With the first ever detection of gravitational waves from merging black-hole binaries by LIGO (Laser Interferometer GravitationalWave Observatory), a new era of gravitational wave astronomy was started. With its increased sensitivity, LIGO will see many more black-hole binaries in the future. To detect the gravitational waves and elucidate the properties of their sources, one needs theoretical waveform templates. These, in turn, require solving Einstein field equations, at least approximately. Approximate techniques like post-Newtonian theory and black-hole perturbation theory can produce waveforms that are accurate for certain phases of binaries evolution. Numerical relativity, on the other hand, can in principle produce …

Autocorrelation Reduction And Consistency Analysis Of Correlation For Human Brain Activity Data, Xiaowen Zhou

Theses

In recent years, the number of studies using functional magnetic resonance imaging (fMRI) on human brain activity has increased rapidly, which has become a hot topic in medical and academic fields. The autocorrelation and correlation problems in the time series of human brain activity have also become an important research direction. It is found that there are relative residuals in the time series of human brain activity processed by smoothing splines. To solve this problem, B-spline is used to smooth the curve. By choosing the right knots, a better smoothness method to process the human brain activity data is provided. …