Digital Commons Network^™

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.

An Exploration Of Microaggression Awareness In Real-Time Conversations And Long-Term Tracking And Learning System, Feifei Guo

Theses

Microaggression is a comment or action that subtly and often unconsciously or unintentionally expresses a prejudiced attitude toward a member of a marginalized group. Microaggressions are often subtle and ambiguous, it's often hard to know if you're committing one or if you're on the receiving end. The recipients of microaggressions always feel a sense of powerlessness and invisibility, while the aggressors are often unaware of the harm they’ve brought. The impact of microaggressions always negatively affects both mental and physical health of recipients and results in persistent health problems.

My goal of the thesis is to make the invisible visible. …

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 …

Towards Lightweight Ai: Leveraging Stochasticity, Quantization, And Tensorization For Forecasting, Zachariah Jl Carmichael

Theses

The deep neural network is an intriguing prognostic model capable of learning meaningful patterns that generalize to new data. The deep learning paradigm has been widely adopted across many domains, including for natural language processing, genomics, and automatic music transcription. However, deep neural networks rely on a plethora of underlying computational units and data, collectively demanding a wealth of compute and memory resources for practical tasks. This model complexity prohibits the use of larger deep neural networks for resource-critical applications, such as edge computing. In order to reduce model complexity, several research groups are actively studying compression methods, hardware accelerators, …

Fabrication Of Organic-Inorganic Hybrid Nanocomposite-Based Sensor For H2s Gas Detection, Fajr Ibrahim Musa Ali

Theses

Low power consumption, low limits of detection, and low cost are the compelling demands in the world of gas sensors development that motivate the search for new materials. Recently, gas sensors based on organic-inorganic nanocomposite materials have attracted much attention due to their high performance and low working temperatures in comparison with the commercial sensors for Hydrogen sulfide (H_₃S) gas. The development of H_₂S gas sensors is vital because H_₂S is one of the major air pollutants produced in large quantities in petroleum/natural gas drilling and refining. H_₂S gas is extremely toxic, …

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 …

End-To-End Music Transcription Using Fine-Tuned Variable-Q Filterbanks, Frank C. Cwitkowitz Jr

Theses

The standard time-frequency representations calculated to serve as features for musical audio may have reached the extent of their effectiveness. General-purpose features such as Mel-Frequency Spectral Coefficients or the Constant-Q Transform, while being pyschoacoustically and musically motivated, may not be optimal for all tasks. As large, comprehensive, and well-annotated musical datasets become increasingly available, the viability of learning from the raw waveform of recordings widens. Deep neural networks have been shown to perform feature extraction and classification jointly. With sufficient data, optimal filters which operate in the time-domain may be learned in place of conventional time-frequency calculations. Since the spectrum …

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 …

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 …

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 …

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 …

Sedentariness, Productivity, Perception And Long Term Health Effects Of Sit-Stand Workstation At Work: A Literature Review, Danielle Mengistab

Theses

Sedentary behavior has been increasingly identified as a contributor to poor health outcomes and sit-stand workstations (SSW) have been introduced in offices to potentially reduce these adverse effects. This thesis presents a review of literature on SSW as they relate to musculoskeletal complaints, sedentary behavior, users’ perception after short- and long-term use, productivity and cardiometabolic markers. To be included in the review, studies were required to include the adult working population subject to a sit-stand workstation intervention with above outcome measures. The review indicates that on an average, SSW has decreased sitting time by about 85 minutes per eight hour …

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 …

The Use Of Electrical Resistance Tomography To Determine The Minimum Agitation Speed For Solids Suspension In Stirred Tank Reactors, Baran Teoman

Theses

Njs, the minimum agitation speed needed to just suspend all the solid particles in a solid-liquid mixture stirred in an agitated vessel, is a critical parameter to properly operate industrial tanks in a large number of industrial operations. As a result, a significant literature on Njs is available. The oldest and the most common method to measure Njs experimentally is that of Zwietering’s (Chem. Eng. Sci., 1958, 8, 244-253), where Njs can be visually obtained by determining when the solids stay at the bottom of the tank for no more than 1-2 seconds before being swept away. Although this has …

A Comparative Study Of Russian Trolls Using Several Machine Learning Models On Twitter Data, Kannan Neten Dharan Kannan Neten Dharan

Theses

Ever since Russian trolls have been brought into light, their interference in the 2016 US Presidential elections has been monitored and studied thoroughly. These Russian trolls have fake accounts registered on several major social media sites to influence public opinions. Our work involves trying to discover patterns in these tweets and classifying them by using different machine learning approaches such as Support Vector Machines, Word2vec and neural network models, and then creating a benchmark to compare all the different models. Two machine learning models are developed for this purpose. The first one is used to classify any given specific tweet …

Colonialism To Carnival: Tracking Centuries Of Racialized Imagery Of Brazilian Woman, Livia Dias

Theses

The thesis explores how the image of Brazilian women, which is highly racialized and sexualized, was constructed historically, and try to understand why Brazilian women are seen as they are in the twentieth century. Throughout the chapters, I will analyze historical documents that I argued helped to construct this image inside Brazil and worldwide.

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 …

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 …

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 …

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 …

Glass Transition Temperature Of Particles For Drug Delivery, Yiqing Yang

Theses

Drug delivery plays an important role in targeted therapies and nanoparticles which can be used as drug carriers and it’s a frequently researched topic. Poly(lactic-co-glycolic acid) (PLGA), a highly biocompatible polymer, has been used as a drug delivery vehicle in many studies. One of the challenges facing drug delivery particles is the problem of burst release which is when a large amount of the drug is suddenly released from the particle once it is placed in the body. This is generally undesirable as usually a slow and controlled release is preferred. The glass transition temperature has an effect on drug …

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 …

Understanding The Relationship Between Sedimentation, Vegetation And Topography In The Tijuana River Estuary, San Diego, Ca., Darbi Berry

Theses

The aim of this study is to identify and characterize key geomorphic properties and relationships within the study site, the Tijuana River Estuary. This is a first step in contributing data to and assisting current and future restoration projects in employing a holistic management approach. The study identifies specific physical parameters, grain size and metal concentrations, within the estuary whose relationship to one another is not mutually exclusive and therefore should be addressed in tandem. This study also tests a remote sensing method for use as a tool for monitoring habitat changes in the estuary.

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 …

Investigation Of Nest Predation As A Cause Of Turtle Population Declines On The Sequoyah National Wildlife Refuge, Oklahoma, Alexandra M. Shipman

Theses

Investigators of a turtle population study spanning 19 years reported major declines in capture rates of red-eared sliders (Trachemys scripta; 4.05 to 0.44) and Ouachita map turtles (Graptemys ouachitensis; 0.18 to 0.01) populations within Sequoyah National Wildlife Refuge in Vian, Oklahoma. Although capture rates of alligator snapping turtles (Macrochelys temminckii) collected in 2016 were comparable to those found in a 1997-2000 study (0.33 compared to 0.35), there was concern that the cause(s) of observed declines in smaller, shorter-lived turtle species could also impact alligator snapping turtle populations, and may not yet be apparent due to differences in life histories, such …

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 …