Digital Commons Network^™

Prediction Of Chlorine And Disinfection Byproduct Concentration In Water Distribution Systems Using Kypipe And Tthm Regression Models: Application To Two Systems In Kentucky, Yogesh Gautam

Theses and Dissertations--Civil Engineering

The main objective of this research is to study if the hydraulic and water quality models can be used for water quality analysis of chlorine decay and TTHM formation at various locations across a water distribution system. This is particularly important because it is not always easy or economical to take multiple field samples and analyze them in the laboratory. In this study, models of two different water distribution systems (one more urban and efficiently managed system located in a relative flat topography, and other more rural and less efficiently managed system located in a mountainous topography) were developed in …

Practical Ai Value Alignment Using Stories, Md Sultan Al Nahian

Theses and Dissertations--Computer Science

As more machine learning agents interact with humans, it is increasingly a prospect that an agent trained to perform a task optimally - using only a measure of task performance as feedback--can violate societal norms for acceptable behavior or cause harm. Consequently, it becomes necessary to prioritize task performance and ensure that AI actions do not have detrimental effects. Value alignment is a property of intelligent agents, wherein they solely pursue goals and activities that are non-harmful and beneficial to humans. Current approaches to value alignment largely depend on imitation learning or learning from demonstration methods. However, the dynamic nature …

Hypogene Speleogenesis In The Grand Canyon; Observational, Mineralogical, And Geochemical Investigations From The Bopper Cave System, Sierra Heimel

Theses and Dissertations--Earth and Environmental Sciences

One of the most prominent features of the Grand Canyon is the iron-stained Redwall Limestone, which has been documented to contain extensive cave systems with significant storage potential in the karstic Redwall-Muav (R-M) aquifer. The hydrogeologic relationships between the R-M aquifer and cave formation in the Grand Canyon via descending (epigenic) surface waters have been well documented. However; the potentially large role of deeply sourced (hypogenic) waters rising from depth in relation to cave formation is poorly understood. The Bopper Cave System (BCS) is a relict feature of the ancient abandoned hydrologic system at Grand Canyon and displays unique network …

Field Tests Of A Uav-Compatible Spectrometer To Evaluate Its Suitability For Detailed Soil Radon Potential Mapping, Alexandria Briahnne Thomas

Theses and Dissertations--Earth and Environmental Sciences

As part of ongoing research on radionuclide mapping and radon hazard characterization, field tests were performed to evaluate the suitability and limitations of a UAV-compatible gamma spectrometer. To date, this data set includes completed stationary data collection, mobile ground collection, multi-level UAV flights over a known material transition, as well as redundant ground and multi-level UAV data collection over a relatively uniform area. Total counts were used as a measure of soil radionuclide levels for our data collected above background. Although our test sites were in regions underlain by bedrock with high indoor radon levels, uranium counts were barely above …

Closing The Modern Seismic Gap Along The Teton Fault Via Seismic Mapping Of Mass Transport Deposits In Jackson Lake, Wy, Callia Jacqueline Cortese

Theses and Dissertations--Earth and Environmental Sciences

Terrestrial paleoseismological records along the Teton fault have historically indicated two-to-three major post-Pinedale (~14 ka) earthquake events, leaving an unresolved 6-9 m offset along the modern scarp. Recent studies of Jenny Lake have augmented this record, but the triggering mechanism is still equivocal until new paleo-earthquake records are developed. The earthquake record of the Teton fault is complicated by quiescence from ~5 ka to present, demonstrating the need for additional paleoseismic investigations. Compressed, high-intensity radar pulse (CHIRP) reflection data from Jackson Lake indicates multiple potentially seismically-induced mass transport deposits (MTDs). At least six MTD Groups representing chronostratigraphic intervals were interpreted …

The Appalachian System Of Basins And Platforms As A Tectonostratigraphic Analogue To The Barents Sea Shelf: Where Arctic Meets The Appalachians, Gustavo De Aguiar Martins

Theses and Dissertations--Earth and Environmental Sciences

Divided between Norway and Russia, the Barents Sea shelf (BSS) is an ~1.4 million km² Arctic province, containing significant hydrocarbon accumulations. However, much of the area is frontier, and geologic data are often restricted or unavailable. One strategy to mitigate lack of geologic data is the use of analogues from well-known, mature basins. Even though there have been attempts to use analogues to study the geology of the BSS, such use is limited. Moreover, no analogue, to my knowledge, has been capable of addressing the regional tectonostratigraphic development of the shelf as a whole.

In this research, the Appalachian …

Discovery Of The Middle Mantle Transition Zone (Mmtz) And Its Geodynamic Significance, Yuping Wang

Theses and Dissertations--Earth and Environmental Sciences

Global mantle discontinuities and mantle transition zones are crucial to the earth’s evolution. By employing K-Means clustering, which belongs to cluster analysis in machine learning (ML), on shear velocity variation data, we generate heterogeneity percentage profiles for three different global tomographic models (Models S362WMANI+M, SEMUCB-WM1, and S40RTS). Key cluster percentage shifts, which are observed at around 400 km, 650 km, 1050 km, 1500 km, and 2700 km, suggest global mantle discontinuities at corresponding depths. All profiles also indicate a global discontinuity in the lower mantle between 2200 km and 2600 km. The middle mantle transition zone (MMTZ), bounded between 1050 …

Applications Of Digital Terrain Modeling To Address Problems In Geomorphology And Engineering Geology, Sarah Johnson

Theses and Dissertations--Earth and Environmental Sciences

This dissertation uses digital terrain modeling and computational methods to yield insight into three topics: 1) evaluating the influence of glacial topography on fluvial sediment transport in the Teton Range, WY, 2) integrating regional airborne lidar, UAV lidar, and structure from motion photogrammetry to characterize decadal-scale movement of slow-moving landslides in northern Kentucky, and 3) applying machine learning methods to surficial geologic mapping.

The role of topography as a boundary condition that controls the efficiency of fluvial erosion in the Teton Range, Wyoming, was investigated by using existing lidar data to delineate surficial geologic units, geometrically reconstruct the depth to …

Slices Of C_2, Klein-4, And Quaternionic Eilenberg-Mac Lane Spectra, Carissa Slone

Theses and Dissertations--Mathematics

We provide the slice (co)towers of \(\Si{V} H_{C_2}\ul M\) for a variety of \(C_2\)-representations \(V\) and \(C_2\)-Mackey functors \(\ul M\). We also determine a characterization of all 2-slices of equivariant spectra over the Klein four-group \(C_2\times C_2\). We then describe all slices of integral suspensions of the equivariant Eilenberg-MacLane spectrum \(H\ulZ\) for the constant Mackey functor over \(C_2\times C_2\). Additionally, we compute the slices and slice spectral sequence of integral suspensions of $H\ulZ$ for the group of equivariance $Q_8$. Along the way, we compute the Mackey functors \(\mpi_{k\rho} H_{K_4}\ulZ\) and $\mpi_{k\rho} H_{Q_8}\ulZ$.

Normalization Techniques For Sequential And Graphical Data, Cole Pospisil

Theses and Dissertations--Mathematics

Normalization methods have proven to be an invaluable tool in the training of deep neural networks. In particular, Layer and Batch Normalization are commonly used to mitigate the risks of exploding and vanishing gradients. This work presents two methods which are related to these normalization techniques. The first method is Batch Normalized Preconditioning (BNP) for recurrent neural networks (RNN) and graph convolutional networks (GCN). BNP has been suggested as a technique for Fully Connected and Convolutional networks for achieving similar performance benefits to Batch Normalization by controlling the condition number of the Hessian through preconditioning on the gradients. We extend …

Lattice Minors And Eulerian Posets, William Gustafson

Theses and Dissertations--Mathematics

We study a partial ordering on pairings called the uncrossing poset, which first appeared in the literature in connection with a certain stratified space of planar electrical networks. We begin by examining some of the relationships between the uncrossing poset and Catalan combinatorics, and then proceed to study the structure of lower intervals. We characterize the lower intervals in the uncrossing poset that are isomorphic to the face lattice of a cube. Moving up in complexity certain lower intervals are isomorphic to the poset of simple vertex labeled minors of an associated graph.

Inspired by this structure, we define a …

Novel Architectures And Optimization Algorithms For Training Neural Networks And Applications, Vasily I. Zadorozhnyy

Theses and Dissertations--Mathematics

The two main areas of Deep Learning are Unsupervised and Supervised Learning. Unsupervised Learning studies a class of data processing problems in which only descriptions of objects are known, without label information. Generative Adversarial Networks (GANs) have become among the most widely used unsupervised neural net models. GAN combines two neural nets, generative and discriminative, that work simultaneously. We introduce a new family of discriminator loss functions that adopts a weighted sum of real and fake parts, which we call adaptive weighted loss functions. Using the gradient information, we can adaptively choose weights to train a discriminator in the direction …

Q-Polymatroids And Their Application To Rank-Metric Codes., Benjamin Jany

Theses and Dissertations--Mathematics

Matroid theory was first introduced to generalize the notion of linear independence. Since its introduction, the theory has found many applications in various areas of mathematics including coding theory. In recent years, q-matroids, the q-analogue of matroids, were reintroduced and found to be closely related to the theory of linear vector rank metric codes. This relation was then generalized to q-polymatroids and linear matrix rank metric codes. This dissertation aims at developing the theory of q-(poly)matroid and its relation to the theory of rank metric codes. In a first part, we recall and establish preliminary results for both q-polymatroids and …

Surjectivity Of The Wahl Map On Cubic Graphs, Angela C. Hanson

Theses and Dissertations--Mathematics

Much of algebraic geometry is the study of curves. One tool we use to study curves is whether they can be embedded in a K3 surface or not. If the Wahl map is surjective on a curve, that curve cannot be embedded in a K3 surface. Therefore, studying if the Wahl map is surjective for a particular curve gives us more insight into the properties of that curve. We simplify this problem by converting graph curves to dual graphs. Then the information for graphs can be used to study the underlying curves. We will discuss conditions for the Wahl map …

Toric Bundles As Mori Dream Spaces, Courtney George

Theses and Dissertations--Mathematics

A projective, normal variety is called a Mori dream space when its Cox ring is finitely generated. These spaces are desirable to have, as they behave nicely under the Minimal Model Program, but no complete classification of them yet exists. Some early work identified that all toric varieties are examples of Mori dream spaces, as their Cox rings are polynomial rings. Therefore, a natural next step is to investigate projectivized toric vector bundles. These spaces still carry much of the combinatorial data as toric varieties, but have more variable behavior that means that they aren't as straightforward as Mori dream …

Geometry Of Pipe Dream Complexes, Benjamin Reese

Theses and Dissertations--Mathematics

In this dissertation we study the geometry of pipe dream complexes with the goal of gaining a deeper understanding of Schubert polynomials. Given a pipe dream complex PD(w) for w a permutation in the symmetric group, we show its boundary is Whitney stratified by the set of all pipe dream complexes PD(v) where v > w in the strong Bruhat order. For permutations w in the symmetric group on n elements, we introduce the pipe dream complex poset P(n). The dual of this graded poset naturally corresponds to the poset of strata associated to the Whitney stratification of the boundary of …

When The Past Comes Knocking: An Alter-Centric Perspective On Network Mobilization In Prosocial Occupations, Jason Ross

Theses and Dissertations--Management

Networks are vital to our ability to access resources. However, scholars have often overlooked just how social networks are mobilized. Underexplored in the literature is how individuals think and feel about mobilizing networks with little attention directed towards the person (alter) being reached out to. In this dissertation, I use a basic, interpretive design to better understand how people think and feel about receiving requests for task-related help, paying particular attention to when those requests originate from people from one’s past. To do so, I conducted interviews with 40 animal rescuers given their passion for helping, but their inability to …

Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan

Theses and Dissertations--Statistics

Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …

Probabilistic Methods For Inferring The Order Of Pathway Alterations During Carcinogenesis And Cancer Subtype Classification, Menghan Wang

Theses and Dissertations--Statistics

Carcinogenesis is a complex process involving somatic mutations in a number of key biological pathways. Studying cancer evolution is an important task which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. We focus on two important questions in cancer evolution. The first question is to delineating the temporal order of pathway mutations during tumorigenesis. And the other question is to cluster patients into biologically meaningful cancer subtypes. We present new statistical methods to 1)leverage functional annotations of mutations to enhance estimation of the order of pathway mutations during carcinogenesis, 2) incorporate intra-tumoral heterogeneity information …

Tolerance Intervals For Various Regression Models, Xitong Zhou

Theses and Dissertations--Statistics

Among statistical intervals, confidence intervals and prediction intervals are well-known and commonly used. In many applications, the problem becomes finding an interval that covers at least a certain proportion $P$ of the population for a characteristic of interest with a specified confidence level $(1-\alpha)$. And such interval is named a $P$-content, $(1-\alpha)$-confidence Tolerance Interval (TI). The topic of the dissertation is the utility of tolerance intervals for various regression models. We begin with a discussion of tolerance intervals for linear and nonlinear regression models. We then propose a bootstrap method of constructing TIs for Tobit regression to deal with censored …

High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang

Theses and Dissertations--Statistics

This dissertation focuses on the problem of high dimensional data analysis, which arises in many fields including genomics, finance, and social sciences. In such settings, the number of features or variables is much larger than the number of observations, posing significant challenges to traditional statistical methods.

To address these challenges, this dissertation proposes novel methods for variable screening and inference. The first part of the dissertation focuses on variable screening, which aims to identify a subset of important variables that are strongly associated with the response variable. Specifically, we propose a robust nonparametric screening method to effectively select the predictors …

Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li

Theses and Dissertations--Statistics

The exponentially-modified Gaussian (EMG) distribution is well-suited for analyzing data with positive skewness due to its characteristic positive skew from the exponential component. Despite its popularity in various fields, the EMG distribution has only been analyzed for univariate data without any regression settings. To address this limitation, we developed a generalized EMG regression model with covariates by assigning parametric functional forms to some or all of the parameters in the EMG distribution that vary with values of the covariates. To further perform data-clustering on observation points, we propose a competing regression model where the error structure is assumed to be …

Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan

Theses and Dissertations--Statistics

For modeling count data, the Conway-Maxwell-Poisson (CMP) distribution is a popular generalization of the Poisson distribution due to its ability to characterize data over- or under-dispersion. While the classic parameterization of the CMP has been well-studied, its main drawback is that it is does not directly model the mean of the counts. This is mitigated by using a mean-parameterized version of the CMP distribution. In this work, we are concerned with the setting where count data may be comprised of subpopulations, each possibly having varying degrees of data dispersion. Thus, we propose a finite mixture of mean-parameterized CMP distributions. An …

Methodologies And Computational Tools For Zero-Inflated Discrete Weibull Models, Peng Yeh

Theses and Dissertations--Statistics

Count data with excess zeros is common in many fields, such as ecology, healthcare, and insurance. Excess zeros data are often causing the inaccurate fit from the count models. While zero-inflated models have been developing for over two decades, one should also consider a more flexible model that can handle the excess zeros and further over- or under-dispersion. In this talk, we discuss zero-inflated discrete Weibull model and some novel computational contributions. The flexibility and competitiveness of the ZIDW model are illustrated by simulation studies and a real data analysis. We also investigate the performance of the proposed model through …

Effectiveness Of A Long-Acting Cocaine Hydrolase In Metabolizing Cocaine And Its Physiologically Active Metabolites, Linyue Shang

Theses and Dissertations--Pharmacy

Cocaine is a widely abused, hepatotoxic drug without an FDA-approved pharmacotherapy specific for cocaine addiction or overdose. Cocaine-induced toxicity in animals and humans is due to its multiple physiological effects on the central nervous system, cardiovascular system, etc. The toxicity of cocaine is highly complex, as its metabolites also contribute to the toxicity. Notably, the combination of cocaine and alcohol is common among drug users and can produce additional metabolites. Some of the metabolites are more toxic than cocaine itself. Hence, to develop an ideal therapeutic candidate, the candidate should not only account for cocaine but should also detoxify other …

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20^thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …

Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp

Theses and Dissertations--Epidemiology and Biostatistics

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …

Prediction Of Dynamic Subsidence In The Proximity Of Longwall Panel Boundaries, Jesus David Romero Benitez

Theses and Dissertations--Mining Engineering

The development of mining subsidence has a dynamic character, and it is related to the mining rate and a time coefficient. Reliable prediction of dynamic deformations is important when planning to undermine important structures that cannot account for large relative deformations and or large horizontal strains. This thesis discusses subsidence development for a number of points over a retreating longwall panel in the eastern US. The prediction points are at different distances from the excavation rib and, therefore, present a different response in terms of dynamic movements. Final movements, i.e., measurements after the panel was fully extracted, were used to …

Assessment Of Air Overpressure From Blasting Using Computational Fluid Dynamics, Cecilia Estefania Aramayo

Theses and Dissertations--Mining Engineering

Air overpressure is a shock wave that occurs when explosives detonate and travel through the air. This can cause damage and annoyance in mining blasts, making it a significant concern for the surroundings of the operation. Currently, the cube root scale distance is used to predict air overpressure, but this method has limitations. To accurately determine air overpressure behavior, a new method is needed. Computational fluid dynamics (CFD) is a reliable and advanced technique that can simulate and solve complex physical problems, including the behavior of air overpressure. In this thesis, two techniques, the bursting balloon, and total pressure boundary, …