Digital Commons Network^™

Annealing Of Fused Filament Fabricated Nylon 6 With Elevated Isostatic Pressure, Anthony G. Tantillo

Theses

Fused filament fabrication (FFF) is the most common form of 3D-printing used today. It combines ease-of-use with broad material options that allow for a wide spectrum of applications. Parts made this way are still considered only prototypes due to their relatively weak strength as compared to traditional manufacturing methods. Two factors leading to a decrease in strength are the interior voids and poor bonding roads. A chamber was created to implement pressurized annealing cycles on nylon 6 co-polymer parts to decrease interior voids and increase road bonding. A designed experiment was used to determine main effect parameter estimates for five …

Numerical Model To Predict Hemolysis And Transport In A Membrane-Based Microfluidic Device, Matthew D. Poskus

Theses

Microfluidics has become an increasingly popular tool in the design and development of medical devices and artificial organs. Two promising applications of microfluidics are dialyzers and oxygenators. As a step toward portable dialysis treatment, continuous microfluidic dialysis may resolve many clinical issues with current dialysis treatments. Additionally, commercially available oxygenators exceed the blood volume of neonatal patients; low-volume microfluidic devices may safely deliver oxygen to these patients. Two critical parameters in the development of these devices is mechanical hemolysis and membrane diffusion, which are intricately connected to the geometry, flow rate, properties of the membrane, and each other. A computational …

Automatic Cancer Tissue Detection Using Multispectral Photoacoustic Imaging, Kamal Jnawali

Theses

Convolutional neural networks (CNNs) have become increasingly popular in recent years because of their ability to tackle complex learning problems such as object detection, and object localization. They are being used for a variety of tasks, such as tissue abnormalities detection and localization, with an accuracy that comes close to the level of human predictive performance in medical imaging. The success is primarily due to the ability of CNNs to extract the discriminant features at multiple levels of abstraction.

Photoacoustic (PA) imaging is a promising new modality that is gaining significant clinical potential. The availability of a large dataset of …

Exploration Of Gpu Cache Architectures Targeting Machine Learning Applications, Gerald Kotas

Theses

The computation power from graphics processing units (GPUs) has become prevalent in many fields of computer engineering. Massively parallel workloads and large data set capabilities make GPUs an essential asset in tackling today's computationally intensive problems. One field that benefited greatly with the introduction of GPUs is machine learning. Many applications of machine learning use algorithms that show a significant speedup on a GPU compared to other processors due to the massively parallel nature of the problem set. The existing cache architecture, however, may not be ideal for these applications. The goal of this thesis is to determine if a …

Exploring The Effectiveness Of Privacy Preserving Classification In Convolutional Neural Networks, Prathibha Rama

Theses

A front-runner in modern technological advancement, machine learning relies heavily on the use of personal data. It follows that, when assessing the scope of confidentiality for machine learning models, understanding the potential role of encryption is critical. Convolutional Neural Networks (CNN) are a subset of artificial feed-forward neural networks tailored specifically for image recognition and classification. As the popularity of CNN increases, so too does the need for privacy preserving classification. Homomorphic Encryption (HE) refers to a cryptographic system that allows for computation on encrypted data to obtain an encrypted result such that, when decrypted, the result is the same …

Joint Source-Channel Coding For Image Transmission Over Underlay Multichannel Cognitive Radio Networks, Long Pham

Theses

The increasing prominence of wireless applications exacerbates the problem of radio spectrum scarcity and promotes the usage of Cognitive Radio (CR) in wireless networks. With underlay dynamic spectrum access, CRs can operate alongside Primary Users, the incumbent of a spectrum band, as long as they limit the interference to the Primary Users below a certain threshold. Multimedia streaming transmissions face stringent Quality of Services constraints on top of the CR interference constraints, as some packets in the data stream have higher levels of importance and are the most vulnerable to packet loss over the channel. This raises a need for …

Etching Processes For Gan Nanowire Fabrication And Single Photon Emitter Device Application, Gildas Ouin

Theses

As they have exhibited great potential for light emitting devices, Gallium Nitride (GaN) nanowire (NW)-based devices have attracted a lot of interest over recent years. Ultra-thin GaN NWs can be used to manufacture many novel devices for future communication and encryption systems, such as single photon emitters (SPEs). However, the conventional growth techniques have limitations in terms of manufacturability, creating the need to explore top-down, etch reliant GaN NW fabrication processes.

This work focuses on improving the fabrication methods for top-down GaN nanowires and lay out a potential process for the manufacturing of SPEs. Using a combination of dry and …

Task Scheduling Balancing User Experience And Resource Utilization On Cloud, Sultan Mira

Theses

Cloud computing has been gaining undeniable popularity over the last few years. Among many techniques enabling cloud computing, task scheduling plays a critical role in both efficient resource utilization for cloud service providers and providing an excellent user experience to the clients. In this study, we proposed a priority cloud task scheduling approach that considers users input to calculate priority, while at the same time, efficiently utilizes available resources. This approach is designed for the consideration of both user satisfaction and utilization of cloud services. In the proposed approach, clients will be required to input their time and cost preferences …

Accessibility Lab #1: Audio Cues, Jan Guillermo

Theses

An increasingly large number of people with disabilities are using software nowadays. However, much of the software created today is inaccessible to people with disabilities. The WorldWideWeb Consortium (W3C) and many other well-known companies have provided the best practices of creating accessible software. Unfortunately, developers either struggle to sympathize with accessibility issues, do not know the best practices of accessibility design, or both. Hence, there is a need to teach developers about accessibility and how to create accessible software. Unfortunately, accessibility is not widely taught in education.

The Accessibility Learning Labs (ALL) were created to address the limitation of readily …

An Exploration Of Emirati Parents’ Involvement In Their Children’S English Reading Of Primary Grades: A Mixed-Method Study, Shaikha Mohammed Ali Saeed

Theses

This study aimed at exploring the Emirati parents’ involvement in their children’s English reading in primary grades (1 through 3). The Study used an Explanatory Sequential Mixed Method Design. In the first phase of the study, a questionnaire (PIQ) was distributed to parents (n=498) who have children in those grades. In the second phase of the study, parents (n=10) were interviewed with regards to their involvement with their children in English language reading. The study found that: Parents have high involvement in their children’s English reading. Parents also reported high involvement in terms of communication, followed by involvement in academic …

Functional Comparison Of Current Software Tools For Genomic Assembly From High Throughput Sequencing Data, Lars J. Olsen

Theses

De novo genomic sequencing, which is the process of discovering the sequence of a genome which has not previously been elucidated, provides unique challenges, especially for larger genomes. Modern high-throughput sequencing technologies have addressed the issue of covering the entire genome in a reasonable time by fragmenting the genome into portions that can be examined in a massively-parallel approach. While these have saved considerable time and cost for the chemical process of determining the sequence of a genome, they result in sets of many tens of millions of sequence fragments called reads, each of which is typically on the order …

My Guest From Afar, Yuan Yao

Theses

An elderly American old man accepts a young Chinese visiting scholar to live in his house. They argue for trifles, they fight for money, but they build up the friendship as time goes by. One day the scholar finishes his research then the old man suddenly realizes that he has already been embedded in his life.

Decadal Changes In Salt Marsh Succession And Assessing Salt Marsh Vulnerability Using High-Resolution Hyperspectral Imagery, Sarah Goldsmith

Theses

Change in the coastal zone is accelerating with external forcing by sea-level rise, nutrient loading, drought and over-harvest is impacting salt marshes. Understanding marsh resilience, including recovery from coastal storms and detection of stress, is essential for conservation and prediction of ecosystem services. The ‘chronosequence approach’ of predicting future state change by examining ecosystem structure and function in existing ecosystems of different ages is a powerful tool, but assumes that the past mimics the future, and time is the dominant driver of change. This approach was evaluated by replicating a 1995 salt marsh chronosequence study in back-barrier marshes ranging from …

Modular Synthesis Of Targeted Molecular Imaging Agents For Mri, Pet, And Pet-Mri Of Cancer, Kelsea Jones

Theses

Molecular imaging is a field widely used in the diagnosis and treatment of cancer. We offer here a modular method for the synthesis of targeted molecular imaging agents (TMIAs), which will improve the accuracy of current molecular imaging methods, as well as allow for earlier detection of tumors. The use of TMIAs in molecular imaging yields increased signal at cancerous cells and reduced signal from healthy cells. Our modular approach is useful as a facile method for the synthesis of dual-modal TMIAs for PET-MRI, which combine the sensitive detection of functional activity from PET with the high-resolution structural information obtained …

Performance Analysis Of Fixed-Random Weights In Artificial Neural Networks, Humza Syed

Theses

Deep neural networks train millions of parameters to achieve state-of-the-art performance on a wide foray of applications. However, finding a global minimum with gradient descent approaches leads to lengthy training times coupled with high computational resource requirements. To alleviate these concerns, the idea of fixed-random weights in deep neural networks is explored. More critically the goal is to maintain performance akin to fully trained models.

Metrics such as floating point operations per second and memory size are compared and contrasted for fixed-random and fully trained models. Additional analysis on downsized models that mimic the number of trained parameters of the …

State Policies Of Medical Marijuana Versus Food & Drug Administration Policies Of Pharmaceutical Drugs, Kayla Stephan

Theses

In the past 22 years, 32 states have legalized and regulated marijuana for medical use. However, marijuana is scheduled as a Schedule I drug according to the federal government. This means that states have no specific regulations to follow for regulating marijuana for medical use. Because of this, states may be risking the safety of medical marijuana patients. Research was conducted to analyze the policies set out by the Food & Drug Administration (FDA) regarding the regulation of a prescription drug. Since the FDA is responsible for the safety and efficacy of prescription drugs, this analysis included what types of …

Mechanics Of Binder-Particle Interactions In Composite Battery Electrodes, Richard Johnson

Theses

A study into the particle level mechanics of polymer binder and active material used in composite lithium-ion batteries (LIB) has been conducted. Silicon is highly sought after material that can be used as an active material in a composite anode. Its high theoretical capacity can result in batteries that can store more energy than current LIBs, but high volume expansion of Si during charge/discharge cycles leads to rapid capacity fade and poor cyclic life. Understanding the stress that is generated in the binder and the active material due to the volume expansion has not been fully understood. In this study …

An Electrical Matlab Model Of Plasma Electrolytic Oxidation, Huize Xue

Theses

Plasma Electrolytic Oxidation (PEO), a part of Plasma electrolytic Deposition (PED), has been developing for surface modification of metallic materials in the past 20 years. During PEO process, sample always connect with anode of DC power source, under high temperature, accelerating process of oxidation reaction to from an average and dense oxidation film. A general passage, Plasma electrolysis for surface engineering, written by A.L. Yerokhin, X. Nie gives us a trend of what happened during PEO process but did not determine specific material and value. Linxin Zhu’s Development of PEO invent a new boiling system and investigated relationship between surface …

Tomato Puree Convective Heat Transfer Simulation Using Boussinesq Approximation, Matteo Fabbri

Theses

With the advance of new technologies, the food industries are requiring systems that allow to produce the desired products with faster rates at cheaper costs. In this case, the study was initiated with the purpose to better understand what happens inside a package containing tomato puree when this is heated above 343 K in a tunnel pasteurizer. If the fluid must reach the thermal and microbiological condition of “pasteurization”, the system must guarantee that the temperature (around 343° Kelvin) is kept for a certain time allowing to pasteurize even the cooler package’s fluid-particle. The faster the system can heat the …

A Study Of Machine Learning And Deep Learning Models For Solving Medical Imaging Problems, Fadi G. Farhat

Theses

Application of machine learning and deep learning methods on medical imaging aims to create systems that can help in the diagnosis of disease and the automation of analyzing medical images in order to facilitate treatment planning. Deep learning methods do well in image recognition, but medical images present unique challenges. The lack of large amounts of data, the image size, and the high class-imbalance in most datasets, makes training a machine learning model to recognize a particular pattern that is typically present only in case images a formidable task.

Experiments are conducted to classify breast cancer images as healthy or …

Blind Source Separation Using Dictionary Learning Over Time-Varying Channels, Anushreya Ghosh

Theses

Distributed sensors observe radio frequency (RF) sources over flat-fading channels. The activity pattern is sparse and intermittent in the sense that while the number of latent sources may be larger than the number of sensors, only a few of them may be active at any particular time instant. It is further assumed that the source activity is modeled by a Hidden Markov Model. In previous work, the Blind Source Separation (BSS) problem solved for stationary channels using Dictionary Learning (DL). This thesis studies the effect of time-varying channels on the performance of DL algorithms. The performance metric is the probability …

Design And Implementation Of An Automated Oil Distribution System For A Homogenizer Machine In Gea Mechanical Equipment – Niro Soavi, Luca Gandolfi

Theses

This thesis shows the steps that have been followed and done in order to improve a critical operation of a technological process of the GEA Mechanical Equipment. The critical operation was the filling with different types of oils the homogenizing machine because it was characterized by a lot of inefficiencies and, in particular, by huge risks for job security. These critical issues gave the opportunity and the chance to realize a project in order to give a process optimization and security improvement.

After having faced all the aspects and steps needed for this project, it has been realized a system …

Multiframe Coded Computation For Distributed Uplink Channel Decoding, Brinell F. Monteiro

Theses

The latest 5G technology in wireless communication has led to an increasing demand for higher data rates and low latencies. The overall latency of the system in a cloud radio access network is greatly affected by the decoding latency in the uplink channel. Various proposed solutions suggest using network function virtualization (NFV). NFV is the process of decoupling the network functions from hardware appliances. This provides the exibility to implement distributed computing and network coding to effectively reduce the decoding latency and improve the reliability of the system. To ensure the system is cost effective, commercial off the shelf (COTS) …

Vergence Eye Movement Parameters For Pre/Post-Obvat And Sham Therapy On Binocularly Normal Controls, Joel V. Rajah

Theses

Vergence is the disjunctive movement of the eyes to maintain single binocular vision. Vergence eye movements are necessary to maintain the object of interest on the fovea of each eye as an individual looks from one object to another. Recent studies show that office based vergence/accommodative therapy (OBVAT) is an effective treatment for the binocular dysfunction known as convergence insufficiency. This study was performed to investigate the changes in oculomotor parameters parameter data for pre- and post-therapy subjects who are binocularly normal controls. A haploscope was used to collect eye movement data pre- and post-therapy. The analysis of the eye …

Deep Morphological Neural Networks, Yucong Shen

Theses

Mathematical morphology is a theory and technique applied to collect features like geometric and topological structures in digital images. Determining suitable morphological operations and structuring elements for a give purpose is a cumbersome and time-consuming task. In this paper, morphological neural networks are proposed to address this problem. Serving as a non-linear feature extracting layers in deep learning frameworks, the efficiency of the proposed morphological layer is confirmed analytically and empirically. With a known target, a single-filter morphological layer learns the structuring element correctly, and an adaptive layer can automatically select appropriate morphological operations. For high level applications, the proposed …

Calculating The Location Of The Center-Of-Gravity Using An Accelerometer Array, Kristin Angel

Theses

In this work, a method for determining a vehicle’s center-of-gravity using traditional commercially available sensors is developed. The method relies on using an accelerometer array along with rate gyro measurements for determining the linear acceleration of the vehicle along all directions at the center-of-gravity location. Once the acceleration at the center-of-gravity is formulated the location can be estimated by resolving measurements of acceleration not located at the center-of-gravity to the center-of-gravity location. Known kinematic equations are used to transform the accelerations at the instrument locations to the center-of-gravity location. An online parameter estimator is used to localize the center-of-gravity using …

A Taxonomic Revision Of The Genus Burmeistera (Campanulaceae) In Ecuador, Brock Mashburn

Theses

The genus Burmeistera (Campanulaceae) consists of approximately 120 species of herbaceous trailing shrubs, found mostly in cloud forests from Guatemala to Peru. Taxonomic work is difficult for the genus because of its relatively recent diversification (5–12 mya) and the morphological lability of its species. The last monograph for the genus was completed in 1943, followed periodically by country-level treatments. For Ecuador, the most recent treatment of Burmeistera was nearly 40 years ago, in Stig Jeppesen’s 1981 treatment in the Flora of Ecuador. Jeppesen’s treatment recognized 32 species and subspecies. Since then, nine new species have been described and hundreds of …

Monsters On The Move: Gravitational Recoil Of Supermassive Black Holes In Nearby Elliptical Galaxies, Yashashree Jadhav

Theses

It has long been assumed that Active Galactic Nuclei (AGN) reside at the centers of their host galaxies, but is this really true? A galaxy merger is expected to lead to the formation of a supermassive black hole (SMBH) binary, which can shrink through dynamical processes until it eventually coalesces through the emission of gravitational waves. Numerical relativity simulations show that, depending on the initial spin-orbit configuration of the binary, the merged SMBH receives a gravitational recoil kick that may reach several 1000 km s−1. The kick causes the merged SMBH to oscillate for up to ∼ 1 Gyr in …

The Effects Of Changing Local Electricity Rate Structures To Accommodate Residential Battery Energy Storage, Based On New York's Energy Storage Roadmap Goals, Robert Gaffney

Theses

In June 2018, the New York State Energy and Research Development Authority (NYSERDA) released the Energy Storage Roadmap (ESR). The ESR detailed a plan to increase the capacity of Battery Energy Storage (BES) across the state by 2025 to reach goals for improving the electric grid. A model was created to find how the operation of a residential solar + storage system could achieve the goals in the ESR. The model used linear optimization to maximize the residential homeowner’s profit under different rate structures. Further analysis of the resulting system operation provided information on metrics directly related to the ESR …

How To Build Upon Sustainable Entrepreneurial Opportunities In Developing Economies, Sherwyn Millette

Theses

Circular economy has been promoted as an alternative to the linear production and consumption patterns prevalent since the industrial era. The implementation of circular economy has proceeded in multiple ways, with different leading actors, e.g. strong industry champions (bottom-up) or with strong government involvement (top-down) and different environmental and economic drivers. This dissertation focuses on the realization of circular economy in a developing economy where there is no strong champion to promote it. It is argued that sustainable entrepreneurship can be a key mechanism for the development of circular economy activity. A circular economy focused incubator can provide a mechanism …