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Articles 1 - 26 of 26
Full-Text Articles in Physical Sciences and Mathematics
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Electronic Theses and Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
A Quantitative Visualization Tool For The Assessment Of Mammographic Risky Dense Tissue Types, Margaret R. Mccarthy
A Quantitative Visualization Tool For The Assessment Of Mammographic Risky Dense Tissue Types, Margaret R. Mccarthy
Electronic Theses and Dissertations
Breast cancer is the second most occurring cancer type and is ranked fifth in terms of mortality. X-ray mammography is the most common methodology of breast imaging and can show radiographic signs of cancer, such as masses and calcifcations. From these mammograms, radiologists can also assess breast density, which is a known cancer risk factor. However, since not all dense tissue is cancer-prone, we hypothesize that dense tissue can be segregated into healthy vs. risky subtypes. We propose that risky dense tissue is associated with tissue microenvironment disorganization, which can be quantified via a computational characterization of the whole breast …
Mathematical Models Yield Insights Into Cnns: Applications In Natural Image Restoration And Population Genetics, Ryan Cecil
Electronic Theses and Dissertations
Due to a rise in computational power, machine learning (ML) methods have become the state-of-the-art in a variety of fields. Known to be black-box approaches, however, these methods are oftentimes not well understood. In this work, we utilize our understanding of model-based approaches to derive insights into Convolutional Neural Networks (CNNs). In the field of Natural Image Restoration, we focus on the image denoising problem. Recent work have demonstrated the potential of mathematically motivated CNN architectures that learn both `geometric' and nonlinear higher order features and corresponding regularizers. We extend this work by showing that not only can geometric features …
The Effect Of Initial Conditions On The Weather Research And Forecasting Model, Aaron D. Baker
The Effect Of Initial Conditions On The Weather Research And Forecasting Model, Aaron D. Baker
Electronic Theses and Dissertations
Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to …
Image Analysis Of Charged Bimodal Colloidal Systems In Microgravity., Adam J. Cecil
Image Analysis Of Charged Bimodal Colloidal Systems In Microgravity., Adam J. Cecil
Electronic Theses and Dissertations
Colloids are suspensions of two or more phases and have been topics of research for advanced, tunable materials for decades. Stabilization of colloids is typically attributed to thermodynamic mechanisms; however, recent studies have identified transport or entropic mechanisms that can potentially stabilize a thermodynamically unstable colloidal system. In this study, suspensions of silsesquioxane microparticles and zirconia nanoparticles were dispersed in a nitric acid solution and allowed to aggregate for 8-12 days in microgravity aboard the International Space Station. The suspensions were subsequently imaged periodically at 2.5x magnification. Due to the inadequacy of existing image analysis programs, the python package “Colloidspy” …
Exploring Information For Quantum Machine Learning Models, Michael Telahun
Exploring Information For Quantum Machine Learning Models, Michael Telahun
Electronic Theses and Dissertations
Quantum computing performs calculations by using physical phenomena and quantum mechanics principles to solve problems. This form of computation theoretically has been shown to provide speed ups to some problems of modern-day processing. With much anticipation the utilization of quantum phenomena in the field of Machine Learning has become apparent. The work here develops models from two software frameworks: TensorFlow Quantum (TFQ) and PennyLane for machine learning purposes. Both developed models utilize an information encoding technique amplitude encoding for preparation of states in a quantum learning model. This thesis explores both the capacity for amplitude encoding to provide enriched state …
Knot Flow Classification And Its Applications In Vehicular Ad-Hoc Networks (Vanet), David Schmidt
Knot Flow Classification And Its Applications In Vehicular Ad-Hoc Networks (Vanet), David Schmidt
Electronic Theses and Dissertations
Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that meets this criterion. To this end, a spline-based intrusion detection system has been pioneered as a solution. By combining clustering with spline-based general linear model classification, this knot flow classification method (KFC) allows for robust intrusion detection to occur. Due its …
A Tale Of Two Bays: The Development And Applications Of The Saco And Casco Modeling Project, Stephen M. Moore
A Tale Of Two Bays: The Development And Applications Of The Saco And Casco Modeling Project, Stephen M. Moore
Electronic Theses and Dissertations
This thesis details the development and application of a finite-volume, hydrodynamic model of Saco and Casco Bays. The primary study conducted herein focused on coupling storm simulations with sea level rise (SLR) to identify vulnerabilities of the two bays. The February 1978 Northeaster and an April freshwater discharge event in 2007 following the Patriot’s Day Storm were modeled by utilizing the Finite-Volume Coastal Ocean Model (FVCOM). Both events were repeatedly simulated under SLR scenarios ranging from 0 to 7 ft. Modeled storm responses were identified from the 1978 blizzard simulations and were tracked across SLR scenarios. By comparing changes in …
Remote Sensing Of Icebergs In Greenland's Fjords And Coastal Waters, Jessica Scheick
Remote Sensing Of Icebergs In Greenland's Fjords And Coastal Waters, Jessica Scheick
Electronic Theses and Dissertations
Increases in ocean water temperature are implicated in driving recent accelerated rates of mass loss from the Greenland Ice Sheet. Icebergs provide a key tool for gaining insight into ice-ocean interactions and until recently have been relatively understudied. Here we develop several methods that exploit icebergs visible in optical satellite imagery to provide insight on the ice--ocean environment and explore how iceberg datasets can be used to examine the physics of iceberg decay and parent glacier properties. First, a semi-automated algorithm, which includes a machine learning-based cloud mask, is applied to six years (2000-2002 and 2013-2015) of the Landsat archive …
Three-Dimensional Bedrock Channel Evolution With Smoothed Particle Hydrodynamics, Nick Richmond
Three-Dimensional Bedrock Channel Evolution With Smoothed Particle Hydrodynamics, Nick Richmond
Electronic Theses and Dissertations
Bedrock channels are responsible for balancing and communicating tectonic and climatic signals across landscapes, but it is difficult and dangerous to observe and measure the flows responsible for removing weakly-attached blocks of bedrock from the channel boundary. Consequently, quantitative descriptions of the dynamics of bedrock removal are scarce. Detailed numerical simulation of violent flows in three dimensions has been historically challenging due to technological limitations, but advances in computational fluid dynamics aided by high-performance computing have made it practical to generate approximate solutions to the governing equations of fluid dynamics. From these numerical solutions we gain detailed knowledge of the …
An Evaluation Of Geotagged Twitter Data During Hurricane Irma Using Sentiment Analysis And Topic Modeling For Disaster Resilience, Ike Robert Vayansky
An Evaluation Of Geotagged Twitter Data During Hurricane Irma Using Sentiment Analysis And Topic Modeling For Disaster Resilience, Ike Robert Vayansky
Electronic Theses and Dissertations
Disasters require quick response times, thought-out preparations, overall community, and government support. These efforts will ensure prevention of loss of life and reduce possible damages. The United States has been battered by multiple major hurricanes in the recent years and multiple avenues of disaster response efforts were being tested. Hurricane Irma can be recognized as the most popular hurricane in terms of social media attention. Irma made landfall in Florida as a Category 4 storm and preparation measures taken were intensive thus providing a good measure to evaluate in terms of efficacy. The effectiveness of the response methods utilized are …
Using Hydroacoustics To Investigate Biological Responses In Fish Abundance To Restoration Efforts In The Penobscot River, Maine, Constantin C. Scherelis
Using Hydroacoustics To Investigate Biological Responses In Fish Abundance To Restoration Efforts In The Penobscot River, Maine, Constantin C. Scherelis
Electronic Theses and Dissertations
Spatiotemporal advantages linked to hydroacoustic sampling techniques have caused a surge in the use of these techniques for fisheries monitoring studies applied over long periods of time in marine systems. Dynamic physical conditions such as tidal height, boat traffic, floating debris, and suspended particle concentrations result in unwanted noise signatures that vary in intensity and location within a hydroacoustic beam over time and can be mixed with the acoustic returns from intended targets (e.g., fish). Typical processing filters applied over long term datasets to minimize noise and maximize signals do not address spatiotemporal fluctuations of noise in dynamic systems. We …
Rationalizing The Band Gap Tunability Of Semiconductors Via Electronic Structure Calculations, Matthew N. Srnec
Rationalizing The Band Gap Tunability Of Semiconductors Via Electronic Structure Calculations, Matthew N. Srnec
Electronic Theses and Dissertations
The polymorphs of titanium dioxide and various diamond-like semiconductor materials are promising candidates in photovoltaic solar cell applications. Several of these polymorphs have been studied with experimental and computational methods, which often aim at tuning the electronic structure, particularly the band gap value of the crystalline solid. Prior studies report that the addition of a substituent into the structure of titanium dioxide decreases its band gap value, but the reasons for this are unknown. Possible explanations for the change in band gap involve the substituent atom's crystal radius, electronegativity, and ionization energy. Understanding the cause of these changes will provide …
Modeling Volatility Of Financial Time Series Using Arc Length, Benjamin H. Hoerlein
Modeling Volatility Of Financial Time Series Using Arc Length, Benjamin H. Hoerlein
Electronic Theses and Dissertations
This thesis explores how arc length can be modeled and used to measure the risk involved with a financial time series. Having arc length as a measure of volatility can help an investor in sorting which stocks are safer/riskier to invest in. A Gamma autoregressive model of order one(GAR(1)) is proposed to model arc length series. Kernel regression based bias correction is studied when model parameters are estimated using method of moment procedure. As an application, a model-based clustering involving thirty different stocks is presented using k-means++ and hierarchical clustering techniques.
Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook
Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook
Electronic Theses and Dissertations
This dissertation is concerned with the development of robust numerical solution procedures for the generalized micromechanical analysis of linear and nonlinear constitutive behavior in heterogeneous materials. Although the methods developed are applicable in many engineering, geological, and materials science fields, three main areas are explored in this work. First, a numerical methodology is presented for the thermomechanical analysis of heterogeneous materials with a special focus on real polycrystalline microstructures obtained using electron backscatter diffraction techniques. Asymptotic expansion homogenization and finite element analysis are employed for micromechanical analysis of polycrystalline materials. Effective thermoelastic properties of polycrystalline materials are determined and compared …
Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, Christopher G. Dufour
Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, Christopher G. Dufour
Electronic Theses and Dissertations
Understanding the impact of global climate change is a critical concern for society at large. One important piece of the climate puzzle is how large-scale ice sheets, such as those covering Greenland and Antarctica, respond to a warming climate. Given such ice sheets are under constant change, developing models that can accurately capture their dynamics represents a significant challenge to researchers. The problem, however, is properly capturing the dynamics of an ice sheet model requires a high model resolution and simulating these models is intractable even for state-of-the-art supercomputers.
This thesis presents a revolutionary approach to accurately capture ice sheet …
An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger
An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger
Electronic Theses and Dissertations
Problems involving the minimization of functionals date back to antiquity. The mathematics of the calculus of variations has provided a framework for the analytical solution of a limited class of such problems. This paper describes a numerical approximation technique for obtaining machine solutions to minimal path problems. It is shown that this technique is applicable not only to the common case of finding geodesics on parameterized surfaces in R3, but also to the general case of finding minimal functionals on hypersurfaces in Rn associated with an arbitrary metric.
Stereographic Visualization Of Bose-Einstein Condensate Clouds To Measure The Gravitational Constant, Ed Wesley Wells
Stereographic Visualization Of Bose-Einstein Condensate Clouds To Measure The Gravitational Constant, Ed Wesley Wells
Electronic Theses and Dissertations
This thesis describes a set of tools that can be used for the rapid design of atom interferometer schemes suitable for measuring Newton's Universal Gravitation constant also known as "Big G". This tool set is especially applicable to Bose--Einstein--condensed systems present in NASA's Cold Atom Laboratory experiment to be deployed to the International Space Station in 2017. These tools include a method of approximating the solutions of the nonlinear Schrödinger or Gross--Pitaevskii equation (GPE) using the Lagrangian Variational Method. They also include a set of software tools for translating the approximate solutions of the GPE into images of the optical …
Spatiotemporal Wireless Sensor Network Field Approximation With Multilayer Perceptron Artificial Neural Network Models, François Neville
Spatiotemporal Wireless Sensor Network Field Approximation With Multilayer Perceptron Artificial Neural Network Models, François Neville
Electronic Theses and Dissertations
As sensors become increasingly compact and dependable in natural environments, spatially-distributed heterogeneous sensor network systems steadily become more pervasive. However, any environmental monitoring system must account for potential data loss due to a variety of natural and technological causes. Modeling a natural spatial region can be problematic due to spatial nonstationarities in environmental variables, and as particular regions may be subject to specific influences at different spatial scales. Relationships between processes within these regions are often ephemeral, so models designed to represent them cannot remain static. Integrating temporal factors into this model engenders further complexity.
This dissertation evaluates the use …
Topographic Signatures Of Geodynamics, Samuel G. Roy
Topographic Signatures Of Geodynamics, Samuel G. Roy
Electronic Theses and Dissertations
The surface of the Earth retains an imperfect memory of the diverse geodynamic, climatic, and surface transport processes that cooperatively drive the evolution of Earth. In this thesis I explore the potential of using topographic analysis and landscape evolution models to unlock past and/or present evidence for geodynamic activity. I explore the potential isolated effects of geodynamics on landscape evolution, particularly focusing on two byproducts of tectonic strain: rock displacement and damage. Field evidence supports a strong correlation between rock damage and erodibility, and a numerical sensitivity analysis supports the hypothesis that an order of magnitude weakening in rock, well …
A Study On The Efficacy Of Sentiment Analysis In Author Attribution, Michael J. Schneider
A Study On The Efficacy Of Sentiment Analysis In Author Attribution, Michael J. Schneider
Electronic Theses and Dissertations
The field of authorship attribution seeks to characterize an author’s writing style well enough to determine whether he or she has written a text of interest. One subfield of authorship attribution, stylometry, seeks to find the necessary literary attributes to quantify an author’s writing style. The research presented here sought to determine the efficacy of sentiment analysis as a new stylometric feature, by comparing its performance in attributing authorship against the performance of traditional stylometric features. Experimentation, with a corpus of sci-fi texts, found sentiment analysis to have a much lower performance in assigning authorship than the traditional stylometric features.
Epistasis In Predator-Prey Relationships, Iuliia Inozemtseva
Epistasis In Predator-Prey Relationships, Iuliia Inozemtseva
Electronic Theses and Dissertations
Epistasis is the interaction between two or more genes to control a single phenotype. We model epistasis of the prey in a two-locus two-allele problem in a basic predator- prey relationship. The resulting model allows us to examine both population sizes as well as genotypic and phenotypic frequencies. In the context of several numerical examples, we show that if epistasis results in an undesirable or desirable phenotype in the prey by making the particular genotype more or less susceptible to the predator or dangerous to the predator, elimination of undesirable phenotypes and then genotypes occurs.
Selection Of Step Size For Total Variation Minimization In Ct, Anna N. Yeboah
Selection Of Step Size For Total Variation Minimization In Ct, Anna N. Yeboah
Electronic Theses and Dissertations
Medical image reconstruction by total variation minimization is a newly developed area in computed tomography (CT). In compressed sensing literature, it hasbeen shown that signals with sparse representations in an orthonormal basis may be reconstructed via l1-minimization. Furthermore, if an image can be approximately modeled to be piecewise constant, then its gradient is sparse. The application of l1-minimization to a sparse gradient, known as total variation minimization, may then be used to recover the image. In this paper, the steepest descent method is employed to update the approximation of the image. We propose a way to estimate an optimal step …
Using Transitivity With Nearest Neighbor To Reduce Error In Sample-Based Pearson Correlation Coefficients, Taylor Phillips
Using Transitivity With Nearest Neighbor To Reduce Error In Sample-Based Pearson Correlation Coefficients, Taylor Phillips
Electronic Theses and Dissertations
Pearson product-moment correlation coefficients are a well-practiced quantification of linear dependence seen across many fields. When calculating a sample-based correlation coefficient, the accuracy of the estimation is dependent on the quality and quantity of the sample. Like all statistical models, these correlation coefficients can suffer from overfitting, which results in the representation of random error instead of an underlying trend.
In this paper, we discuss how Pearson's product-moment correlation coefficients can utilize information outside of the two items for which the correlation is being computed. By introducing a relationship with one or more additional items that meet specified criterion, our …
A Computational Chemistry Study Of Spin Traps., Jacob Fosso-Tande
A Computational Chemistry Study Of Spin Traps., Jacob Fosso-Tande
Electronic Theses and Dissertations
Many defects in physiological processes are due to free radical damage: reactive oxygen species, nitric oxide, and hydroxyl radicals have been implicated in the parthenogenesis of cancer, diabetes mellitus, and rheumatoid arthritis. We herein characterize the phenyl-N-ter-butyl nitrone (PBN) type spin traps in conjunction with the most studied dimethyl-1-pyrroline-N-oxide (DMPO) type spin traps using the hydroxyl radical. In this study, theoretical calculations are carried out on the two main types of spin traps (DMPO and PBN) at the density functional theory level (DFT). The energies of the optimized structures, hyperfine calculations in gaseous and aqueous phases of the spin traps …
Implications Of Spatial Autocorrelation And Dispersal For The Modeling Of Species Distributions, Volker Bahn
Implications Of Spatial Autocorrelation And Dispersal For The Modeling Of Species Distributions, Volker Bahn
Electronic Theses and Dissertations
Modeling the geographical distributions of wildlife species is important for ecology and conservation biology. Spatial autocorrelation in species distributions poses a problem for distribution modeling because it invalidates the assumption of independence among sample locations. I explored the prevalence and causes of spatial autocorrelation in data from the Breeding Bird Survey, covering the conterminous United States, using Regression Trees, Conditional Autoregressive Regressions (CAR), and the partitioning of variance. I also constructed a simulation model to investigate dispersal as a process contributing to spatial autocorrelation, and attempted to verify the connection between dispersal and spatial autocorrelation in species' distributions in empirical …