Engineering Commons^™

Anthropogenic Effects On Tidal Distortion In A Tidal River, Matthew D. Fischer

Electronic Theses and Dissertations

Tidal rivers are landward portions of estuarine systems constituting the union between coastal, tidally controlled settings and rivers, where fluvial processes dominate. In these reaches, river discharge (mean flow) and tides are the two most important mechanisms in controlling geophysical flows. The processes governing water levels and current amplitudes in tidal rivers are highly nonlinear and modulated by external forcings- thus requiring sophisticated techniques for accurate prediction and forecasting. Physical oceanographers and estuarine physicists tend to limit their study area to the maximum extent of the horizontal tide (salinity intrusion), not the most landward point influenced by tidal water levels. …

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Quantifying Spatial Heterogeneity Of Wild Blueberries And Crop Water Stress Monitoring Using Remote Sensing Technologies, Kallol Barai

Electronic Theses and Dissertations

The wild blueberry is one of the major crops of Maine, with significant economic value and potential health benefits. Due to global climate change, drought impacts have been increasing significantly in recent years in the northeast region of the USA, causing significant economic losses in the agricultural sectors. It has been predicted to increase further in the future. Changing patterns of the elevated atmospheric temperatures, increased rainfall variabilities, and more frequent drought events have made the wild blueberry industry of Maine vulnerable, suggesting the adoption of novel approaches to mitigate the negative impacts of global climate changes. Also, wild blueberry …

Intersections Of Environmentalism, Chemistry, And Racism: An Experimental Study Of Halobenzene Hydrogenolysis And Critical Communication Studies Of Equitable Learning Practices Rooted In Black Feminism, Lauren O. Babb

Electronic Theses and Dissertations

Increasing concentrations of fluorinated aromatic compounds in surface water, groundwater, and soil pose threats to the environment. Fundamental studies that elucidate mechanisms of dehalogenation for C-X compounds (where X represents a halide) are required to develop effective remediation strategies. For halogenated benzenes, previously published research has suggested that the strength of the C-X bond is not rate-determining in the overall rate of dehalogenation. Instead, the rate-determining step has been hypothesized to be adsorption of the C-X compound onto the surface of a catalyst. Building on this hypothesis, in this work, we examine the reaction kinetics of fluorobenzene conversion to benzene, …

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

Role Of Deep Learning Techniques In Non-Invasive Diagnosis Of Human Diseases., Hisham Abouelseoud Elsayem Abdeltawab

Electronic Theses and Dissertations

Machine learning, a sub-discipline in the domain of artificial intelligence, concentrates on algorithms able to learn and/or adapt their structure (e.g., parameters) based on a set of observed data. The adaptation is performed by optimizing over a cost function. Machine learning obtained a great attention in the biomedical community because it offers a promise for improving sensitivity and/or specificity of detection and diagnosis of diseases. It also can increase objectivity of the decision making, decrease the time and effort on health care professionals during the process of disease detection and diagnosis. The potential impact of machine learning is greater than …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Development And Evaluation Of Modeling Approaches For Extrusion-Based Additive Manufacturing Of Thermoplastics, Christopher C. Bock

Electronic Theses and Dissertations

This work focuses on evaluating different modeling approaches and model parameters for thermoplastic AM, with the goal of informing more efficient and effective modeling approaches. First, different modeling approaches were tested and compared to experiments. From this it was found that all three of the modeling approaches provide comparable results and provide similar results to experiments. Then one of the modeling approaches was tested on large scale geometries, and it was found that the model results matched experiments closely. Then the effect of different material properties was evaluated, this was done by performing a fractional factorial design of experiments where …

Surface-Functionalized Chemiresistive Films That Exploit H-Bonding, Cation-Pi, And Metal-Halide Interactions., Prasadanie Karunarathna Adhihetty

Electronic Theses and Dissertations

The development of gas sensors for detection of volatile organic compounds (VOCs) has been of interest in the sensing field for decades. To date, the use of metal nanoparticle-based chemiresistors for trace VOC detection, particularly gold nanoparticle-based sensors, is of great interest due to their high chemical stability, ease of synthesis, unique optical properties, large surface to volume ratio, and high level of conductivity. Much effort has been devoted towards gold monolayer protected clusters (Au MPCs) as chemiresistors to detect harmful VOCs. The present thesis documents the results of our efforts to exploit the advantages of functionalized Au MPCs chemiresistors …

Structural, Charge Transport, Gas Sensing, Magnetic, Pseudocapacitive, And Electrocatalytic Properties Of Perovskite Oxides., Surendra Bahadur Karki

Electronic Theses and Dissertations

Perovskites are functional materials with the general formula ABO₃ (A = alkali, alkaline earth or lanthanoid cations and B = transition metal or main group cations). These materials are marked by a variety of crystal structures and interesting properties such as colossal magnetoresistance, ferroelectricity, multiferroicity, superconductivity, pseudocapacitance, gas sensing, charge transport, and electrocatalytic properties. The formula of perovskite can be written as AA’BB’O₆, when there is ordering between two cations over A and B-sites. Such compounds are called double perovskite oxides. Some amount of oxygen could be lost from crystal structure without decomposition of the phase. Such …

Nucleate Boiling Under Different Gravity Values: Numerical Simulations & Data-Driven Techniques., Sandipan Banerjee

Electronic Theses and Dissertations

Nucleate boiling is important in nuclear applications and cooling applications under earth gravity conditions. Under reduced gravity or microgravity environment, it is significant too, especially in space exploration applications. Although multiple studies have been performed on nucleate boiling, the effect of gravity on nucleate boiling is not well understood. This dissertation primarily deals with numerical simulations of nucleate boiling using an adaptive Moment-of-Fluid (MoF) method for a single vapor bubble (water vapor or Perfluoro-n-hexane) in saturated liquid for different gravity levels. Results concerning the growth rate of the bubble, specifically the departure diameter and departure time have been provided. The …

Charged-Particle Interactions To Generate Novel Coatings And Materials, Pradnya D. Rao

Electronic Theses and Dissertations

A typical paper coating formulation contains anionically charged pigments and latex to provide a high-quality surface for printing. However, during application and drying, the latex can migrate to the surface or deep into the paper, resulting in weak coating layers or the need to use a high latex content to obtain the same strength properties. In this thesis, we have explored the introduction of cationically charged particles into the suspension as a way to reduce the amount of binder in the coatings, improve coating strength and reduce binder migration. With these aims in mind, we have generated cationic precipitated calcium …

Robot Learning From Human Observation Using Deep Neural Networks, Michael Elachkar

Electronic Theses and Dissertations

Industrial robots have gained traction in the last twenty years and have become an integral component in any sector empowering automation. Specifically, the automotive industry implements a wide range of industrial robots in a multitude of assembly lines worldwide. These robots perform tasks with the utmost level of repeatability and incomparable speed. It is that speed and consistency that has always made the robotic task an upgrade over the same task completed by a human. The cost savings is a great return on investment causing corporations to automate and deploy robotic solutions wherever feasible.

The cost to commission and set …

Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan

Electronic Theses and Dissertations

Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …

Efficient Numerical Optimization For Parallel Dynamic Optimal Power Flow Simulation Using Network Geometry, Rylee Sundermann

Electronic Theses and Dissertations

In this work, we present a parallel method for accelerating the multi-period dynamic optimal power flow (DOPF). Our approach involves a distributed-memory parallelization of DOPF time-steps, use of a newly developed parallel primal-dual interior point method, and an iterative Krylov subspace linear solver with a block-Jacobi preconditioning scheme. The parallel primal-dual interior point method has been implemented and distributed in the open-source PETSc library and is currently available. We present the formulation of the DOPF problem, the developed primal dual interior point method solver, the parallel implementation, and results on various multi-core machines. We demonstrate the effectiveness our proposed block-Jacobi …

Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng

Electronic Theses and Dissertations

Convolutional Neural Network (CNN) is a neural network developed for processing image data. CNNs have been studied extensively and have been used in numerous computer vision tasks such as image classification and segmentation, object detection and recognition, etc. [1] Although, the CNNs-based approaches showed humanlevel performances in these tasks [2], they require heavy computation in both training and inference stages, and the models consist of millions of parameters. This hinders the development and deployment of CNN-based models for real world applications. Neural Network Pruning and Compression techniques have been proposed [3, 4] to reduce the computation complexity of trained CNNs …

Sentiment Without Sentiment Analysis: Using The Recommendation Outcome Of Steam Game Reviews As Sentiment Predictor, Anqi Zhang

Electronic Theses and Dissertations

This paper presents and explores a novel way to determine the sentiment of a Steam game review based on the predicted recommendation of the review, testing different regression models on a combination of Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) features. A dataset of Steam game reviews extracted from the Programming games genre consisting of 21 games along with other significant features such as the number of helpful likes on the recommendation, number of hours played, and others. Based on the features, they are grouped into three datasets: 1) either having keyword features only, 2) keyword features …

Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan

Electronic Theses and Dissertations

Neural Networks have been used in many decision-making models and been employed in computer vision, and natural language processing. Several works have also used Neural Networks for developing Pseudo-Random Number Generators [2, 4, 5, 7, 8]. However, despite great performance in the National Institute of Standards and Technology (NIST) statistical test suite for randomness, they fail to discuss how the complexity of a neural network affects such statistical results. This work introduces: 1) a series of new Long Short- Term Memory Network (LSTM) based and Fully Connected Neural Network (FCNN – baseline [2] + variations) Pseudo Random Number Generators (PRNG) …

Characterization Of A Three-Way Catalyst For High Efficiency Spark Ignition Engines, Cavin Hesketh

Electronic Theses and Dissertations

The push for environmental protection and sustainability has led to strict emission regulations for automotive manufacturers as evident in EURO VII and 2026 EPA requirements set to take effect in the coming years. The modern gasoline spark ignition (SI) engine typically employs various in-cylinder emission reduction techniques along with an exhaust after-treatment system to comply with emission standards. The three-way catalyst (TWC) is wholly responsible for removing the engine-out emissions including hydrocarbons (HC), carbon monoxide (CO) and nitrogen oxides (NOx). The main objective of this thesis is to investigate the impact of extensive exhaust gas recirculation (EGR) on …

Femtosecond Pulse Compression Via Self-Phase Modulation In 1-Decanol, Jacob A. Stephen

Electronic Theses and Dissertations

Ultrafast science is a branch of photonics with far reaching applications in and outside the realm of physics. Ultrashort laser pulses on the order of femtoseconds (1 fs = 1 × 10−15 s) are widely used for ultrafast science. Many lasers can produce pulses on the order of 100 fs, with state of the art, high end lasers being capable of producing pulses around 30 fs. However, many experiments require pulses around 10 fs or shorter. Femtosecond pulses are typically generated using spectral broadening via self-phase modulation, followed by dispersion compensation. The most common spectral broadening technique exploits the nonlinear …

Human-Machine Collaboration In Healthcare Innovation, Breeze Fenton

Electronic Theses and Dissertations

Almost every individual has visited a healthcare institute, whether for an annual checkup, surgery, or a nursing home. Ensuring healthcare institutes are using human-machine collaboration systems correctly can improve daily operations. A maturity assessment and an implementation plan have been developed to help healthcare institutes monitor the human-machine collaboration systems. A maturity model, the Smart Maturity Model for Health Care (SMMHC), is a tool designed for maturity assessment. A four-step implementation plan was also created in this research. The implementation plan views the maturity of the institute and develops a strategy on how to improve it. The research utilized Integrated …

Hardware Implementations Of Spiking Neural Networks And Artificially Intelligent Systems, Alexander J. Leigh

Electronic Theses and Dissertations

Artificial spiking neural networks are gaining increasing prominence due to their potential advantages over traditional, time-static artificial neural networks. Custom hardware implementations of spiking neural networks present many advantages over other implementation mediums. Two main topics are the focus of this work. Firstly, digital hardware implementations of spiking neurons and neuromorphic hardware are explored and presented. These implementations include novel implementations for lowered digital hardware requirements and reduced power consumption.

The second section of this work proposes a novel method for selectively adding sparsity to a spiking neural network based on training set images for pattern recognition applications, thereby greatly …

Building Competent Teams Of Experts Based On Project Completion Time And Skill Levels, Yalda Yazdanpanah

Electronic Theses and Dissertations

With many companies quickly expanding their sizes, building the best team of experts from the applicants has evolved into an interesting subject for computer-aided decision-making tasks. In this regard, the Team Formation Problem (TFP) has been well-studied in Artificial Intelligence and operations research literature in recent years. We consider a Team Formation Problem of assigning qualified experts to a given set of positions in a given set of projects where each position is to be filled with an expert with a required skill. In our setting, an expert can be quantitatively characterized by one level per skill, and each expert …

Enhancing Multi-View 3d-Reconstruction Using Multi-Frame Super Resolution, Michael Lee

Electronic Theses and Dissertations

Multi-view stereo is a popular method for 3D-reconstruction. Super resolution is a technique used to produce high resolution output from low resolution input. Since the quality of 3D-reconstruction is directly dependent on the input, a simple path is to improve the resolution of the input.

In this dissertation, we explore the idea of using super resolution to improve 3D-reconstruction at the input stage of the multi-view stereo framework. In particular, we show that multi-view stereo when combined with multi-frame super resolution produces a more accurate 3D-reconstruction.

The proposed method utilizes images with sub-pixel camera movements to produce high resolution output. …

Analysis Of Bio-Alcohols With Mie-Scattering And Ltc For Lowered Emissions In Pcci, Cesar E. Carapia

Electronic Theses and Dissertations

An investigation was conducted on the optimal engine parameters for facilitating lower NOX and soot emissions of PCCI combustion with either ethanol or n-butanol. The PFI fuels selected were tested at loads of 3, 4, and 5 Bar IMEP for a total of 28 total combustion tests with variations made to the EGR% and boost pressure for each test in order to find the optimal emissions strategy. A Mie-scattering spray fuel analysis was also conducted on the three fuels to gain insight on their influence on combustion/emissions characteristics. It was found that ethanol had a greater average Sauter Mean Diameter …

License Plate Image Quality Enhancement Utilizing Super Resolution Generative Adversarial Networks, Mark Moelter

Electronic Theses and Dissertations

This thesis focuses primarily on enhancing the image quality of blurred license plates through the use of Super-Resolution Generative Adversarial Networks (SRGANs) [1]. We propose a synthetic dataset with SRGAN model to promote blurred image quality enhancement, and allow for model evaluation on a multitude of image input and output size combinations. SRGAN is mainly used for low-resolution image enhancement, but by heavily blurring the input images, the model is tested on its ability to blindly deblur and upsample images to the desired super-resolution (SR) size. The model enhances the image quality to nearly that of the reference images. The …