Physical Sciences and Mathematics Commons^™

Differential Elliptic Flow Analysis Of Hadrons With Different Wuark Content In Simulated Pp Collisions, Elhussein Osama

Theses and Dissertations

According to current physics theories, it is assumed that in the first microsecond after the big bang, the universe was in a state of matter called Quark-Gluon Plasma (QGP), where the fundamental consistent of matters (quarks and leptons), were highly energetic, and floating around freely. Searching for such phase of matter; as the possible earliest signatures after the big bang, and among many other interesting experimental measurements, the jet quenching and elliptic flow are the most important ones, in the heavy ion collisions at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC) experiments.

The azimuthal anisotropy …

Federated Learning Based Autoencoder Ensemble System For Malware Detection On Internet Of Things Devices, Steven Edward Arroyo

Theses and Dissertations

New technologies are being introduced at a rate faster than ever before and smaller in size. Due to the size of these devices, security is often difficult to implement. The existing solution is a firewall-segmented “IoT Network” that only limits the effect of these infected devices on other parts of the network. We propose a lightweight unsupervised hybrid-cloud ensemble anomaly detection system for malware detection. We perform transfer learning using a generalized model trained on multiple IoT device sources to learn network traffic on new devices with minimal computational resources. We further extend our proposed system to utilize federated learning …

Feasibility Of Oil Palm Agroforestry System: Evaluating The Application Of Oil Palm Ash For Enhancing Cherry Tomato (Solanum Lycopersicum. Var. Nancy Rz) Production Using Brackish Water., Ime Joseph Bassey

Theses and Dissertations

Monoculture systems of oil palm production are ravaging the world’s tropical forests, causing deforestation and biodiversity loss, which contribute to climate change at an uncontrollable pace. Oil palm agroforestry systems (AFSs), one of the strategies of regenerative agriculture, have proven to reverse the unfavorable effects of the oil palm monoculture systems. A sustainable means of soil fertilization and irrigation must be explored to improve the feasibility of oil palm AFSs. This study evaluates the impact of the application of oil palm ash and brackish irrigation on cherry tomato production. The experiment was conducted in a hydroponic system using a 2*4 …

Leveraging Biological Mechanisms In Machine Learning, Kyle J. Rogers

Theses and Dissertations

This thesis integrates biologically-inspired mechanisms into machine learning to develop novel tuning algorithms, gradient abstractions for depth-wise parallelism, and an original bias neuron design. We introduce neuromodulatory tuning, which uses neurotransmitter-inspired bias adjustments to enhance transfer learning in spiking and non-spiking neural networks, significantly reducing parameter usage while maintaining performance. Additionally, we propose a novel approach that decouples the backward pass of backpropagation using layer abstractions, inspired by feedback loops in biological systems, enabling depth-wise training parallelization. We further extend neuromodulatory tuning by designing spiking bias neurons that mimic dopamine neuron mechanisms, leading to the development of volumetric tuning. This …

Investigation Of Collision Cross Sections & Time-Resolved Structural Modification Of Biomolecules, Host-Guest Systems, & Small Molecules Using Ion Mobility & Fourier Transform Ion Cyclotron Resonance Mass Spectrometry, Noah Mismash

Theses and Dissertations

This thesis explores the structures and structural changes of supramolecular host-guest systems, proteins, and other small molecules in the gas phase, utilizing a combination of computational modeling and experimental data. The primary instruments employed were a Fourier transform ion cyclotron resonance mass spectrometer (FTICR-MS) and an ion mobility mass spectrometer (IM-MS). In the IM-MS experiments, the focus was on investigating the binding behavior of cyclodextrin macrocycles—specifically α, β, and γ-cyclodextrin—with per-fluoroalkane substances (PFAS), which are pervasive environmental contaminants. This investigation involved measuring ion-neutral collision cross sections and using computational modeling to determine whether PFAS compounds bind inside or outside the …

Back To The Future: A Case For The Resurgence Of Approximation Theory For Enabling Data Driven “Intelligence”, Michael Dominic Ciocco

Theses and Dissertations

Artificial Intelligence (AI) has exploded into mainstream consciousness with commercial investments exceeding $90 billion in the last year alone. Inasmuch as consumer-facing applications such ChatGPT offer astounding access to algorithms that were hitherto restricted to academic research labs, public focus of attention on AI has created an avalanche of misinformation. The nexus of investor-driven hype, “surprising” inaccuracies in the answers provided by AI models – now anthropomorphically labeled as “hallucinations”, and impending legislation by well-meaning and concerned governments has resulted in a crisis of confidence in the science of AI. The primary driver for AI’s recent growth is the convergence …

Minimal Specialization: The Coevolution Of Network Structure And Dynamics, Annika King

Theses and Dissertations

The changing topology of a network is driven by the need to maintain or optimize network function. As this function is often related to moving quantities such as traffic, information, etc., efficiently through the network, the structure of the network and the dynamics on the network directly depend on the other. To model this interplay of network structure and dynamics we use the dynamics on the network, or the dynamical processes the network models, to influence the dynamics of the network structure, i.e., to determine where and when to modify the network structure. We model the dynamics on the network …

Dna-Templated Nanofabrication Of Metal-Semiconductor Heterojunctions And Their Electrical Characterization, Chao Pang

Theses and Dissertations

Bottom-up nanofabrication, although still in its early stages with formidable challenges, is considered a potential alternative method to address the limitations of traditional top-down techniques by offering benefits including process simplification, cost reduction, and environmental friendliness. DNA-templated nanofabrication, one of the most powerful bottom-up methods, presents an innovative way to create advanced nanoelectronics. In this approach, nanomaterials with specific electronic, photonic, or other functions are precisely and programmably positioned on DNA nanostructures from a disordered collection of smaller parts. These self-assembled structures offer significant potential for improving many fields such as biosensing, drug delivery and electronic device manufacturing. This dissertation …

Towards Carbon Dioxide Reduction: Synthesis And Characterization Of Ccc-Nhc Pincer Iron Complexes., Joshua Mensah

Theses and Dissertations

The industrial revolution came with its downside of emission of greenhouse gases into the atmosphere. The NOAA reported in 2019 that, of the greenhouse gases emitted into the atmosphere, CO2 contributed to about 80% of the increased greenhouse gases hence the need for CO2 Sequestering and Storage (CSS) and ultimately leading to Carbon Capture and Recycling (CCR) as a viable option to convert CO2 into useful forms. The race to find the best catalyst for CCR has led to the synthesis of many organometallic compounds. Pincer complexes catalyzed CO2 reduction has gained notoriety recently because of the tunability and robustness …

A Bilevel Approach To Resource Allocation For Utility-Based Request-Response Systems, Tanner Jack Sundwall

Theses and Dissertations

We present a novel bilevel programming formulation that aims to solve a resource allocation problem for request-response systems. Our formulation is motivated by potential inefficiencies in the allocation of computational resources to incoming user requests in such systems. In our experience, systems often operate with a surplus of resources despite potentially incurring unjustifiable cost. Our work attempts to optimize the tradeoff between the financial cost of resources and the opportunity cost of unfulfilled user demand. Our bilevel formulation consists of an \textit{upper} problem which has a constraint value appearing in the \textit{lower} problem. We derive efficient methods for finding global …

Dissecting Trypanosome Metabolism By Discovering Glycolytic Inhibitors, Drug Targets, And Glycosomal Ph Regulation, Daniel Hale Call

Theses and Dissertations

Trypanosoma brucei, the causative agent of African trypanosomiasis, and its relatives Trypanosoma cruzi and several Leishmania species belong to a class of protozoa called kinetoplastids that cause a significant health burden in tropical and semitropical countries across the world. While an improved therapy was recently approved for African trypanosomiasis, the therapies available to treat infections caused by T. cruzi and Leishmania spp. remain relatively poor. Improving our understanding of T. brucei metabolism can inform on metabolism of its relatives. The purpose of the research presented in this dissertation was to develop novel tools and methods to study metabolism in T. …

Classification And Explanation Of Iron Deficiency Anemia From Complete Blood Count Data Using Machine Learning, Siddartha Pullakhandam

Theses and Dissertations

Anemia is a global health problem, and over 2 billion people are affected. Although, the major cause of anemia is iron deficiency (IDA), global estimates suggest that only about half of anemia could be attributed to ID. The typical test of anemia involves measurement of hemoglobin using Complete Blood Count (CBC) test, which also gives additional information on blood cell numbers and morphology. The diagnosis of iron deficiency anemia (IDA, both anemic and ID co-exist in a subject) requires additional expensive serum ferritin test. However, blood cell count, and morphology can also be utilized for diagnosis of IDA. The goal …

Shoreland Development And Disturbances: A Hedonic Analysis Of Lakefront Properties In Northeastern Wisconsin, Usa, Susan Borchardt

Theses and Dissertations

Shoreland development, encompassing features like boat lifts, manicured lawns, artificial beaches, and erosion control measures, offers considerable benefits to property owners. Nevertheless, this development disrupts natural conditions and is associated with increased sediment and pollutant loading, which negatively impacts aesthetics, recreation, and habitat for fish and other aquatic species. This thesis conducts two analyses, which respectively quantify the benefits of shoreland development to homeowners and evaluate the relationship between shoreland development and lake water quality. In the first analysis, a hedonic property model is employed to value shoreland development along Wisconsin inland lakes. The model considers various shoreland development features, …

Predicting Energy Expenditure From Physical Activity Videos Using Optical Flows And Deep Learning, Gayatri Kasturi

Theses and Dissertations

This thesis presents a novel approach for predicting energy expenditure of physical activity from videos using optical flows and deep learning. Conventional approaches mainly rely on wearable sensors, which, despite being widely used, are constrained by practicality and accuracy concerns. This proposal introduces a new strategy that utilizes a three-dimensional Convolutional Neural Network (3D-CNN) to evaluate video data and accurately estimate energy costs in metabolic equivalents (METs). Our model utilizes optical flow extraction to analyze video, capturing complex motion patterns and their changes over time. The results are good indicating potential for this method to be deployed in various healthcare …

Conceptual Understanding Of Linear Relationships Across Various Mathematics Courses, Melissa Manley

Theses and Dissertations

This cross-sectional study investigated the conceptual understanding of linear relationships for 195 students enrolled in a single school in a large, urban district across five mathematics courses: Grade 7 Math (n = 24), Grade 8 Math (n = 52), Geometry (n = 43), Algebra 1 (n = 31), and Algebra 2 (n = 45). The following questions guided this study: (1) What differences exist in students’ conceptual understanding of linear relationships across mathematics courses? (2) What are common strengths and weaknesses in students’ conceptual understanding of linear relationships?

An assessment was created to assess three constructs of conceptual understanding of …

Which Vole Is Which: Dna-Based Species Identification For Wisconsin’S Three Microtus Species, Madeline Noel Opie

Theses and Dissertations

Accurate species identification is necessary to implement conservation strategies in the wild. When traditional morphology-based species identification is challenging due to phenotypic plasticity, overlapping characteristics, or the species are otherwise cryptic, DNA-based species identification may be more suitable. Of the three species of Microtus in Wisconsin, two are listed as threatened at the state level. Both M. ochrogaster and M. pinetorum have stable population levels at the national level but are along the northern edge of their ranges in Wisconsin. Small and vulnerable populations of M. ochrogaster and M. pinetorum are limited to isolated patches in the southwestern portion of …

Comparison Of Multidecadal Variability In Climate Reanalyses And Global Models, Andrew A. Westgate

Theses and Dissertations

Superimposed on the linear upward trend of observed global surface air temperature anomalies since the late nineteenth century is, what appears to be, a multidecadal undulation. However, this undulation is either muted or virtually absent in both the previous and current generations of the state-of-the-art climate models used to not only simulate past climates but also predict future climates. One possibility is that this signal is due to a series of complex responses to the global climate forcing; an alternative is that this signal is contained within the internal variability and teleconnected via atmospheric channels. Either way, the existential threat …

Authigenic Minerals In Volcaniclastics From An Eastern African Paleolake: A Proxy For Paleoenvironment, Kaitlyn Truss

Theses and Dissertations

Olduvai Gorge exposes the stratigraphy of Paleolake Olduvai, an often saline-alkaline rift lake that records volcanism from the Ngorongoro Volcanic Highlands. In 2014, cores retrieved from the study area revealed new stratigraphy, including the lacustrine Naibor Soit Formation (Fm) and the volcaniclastic Ngorongoro Fm. In the Ngorongoro Fm part of the cores, mineralogy and geochemistry are the best paleoenvironmental proxies, since under saline-alkaline conditions, volcanic glass alters into specific authigenic minerals (e.g., zeolite, feldspar). This study employs X-Ray Diffraction, X-Ray Fluorescence, and Scanning Electron Microscopy to analyze authigenic mineralogy and geochemistry. The lower Ngorongoro Fm experienced the most alteration, with …

Markov Chain Model Of Three-Dimensional Daphnia Magna Movement, Helen L. Kafka

Theses and Dissertations

Daphnia magna make turns through an antennae-whipping action. This action occursevery few seconds, hence, during the intervening time, the animal either remains in place or continues movement roughly along its current course. We view their movement in three dimensions. We divide the movement in the three dimensions into the movement on a two-dimensional lattice and the movement between the different planes. For the movement on the lattice, we construct a second-order Markov chain model to make predictions about which region of the lattice the animal moves to based on where it was at the last two time points. The movement …

Analytic Approximations Of Higher Order Moments In Terms Of Lower Order Moments, Sven Detlef Bergmann

Theses and Dissertations

The Cloud Layers Unified By Binormals (CLUBB) model uses the sum of two normal probability density function (pdf) components to represent subgrid variability within a single grid layer of an atmospheric model. This binormal approach, while computationally efficient, restricts the model’s ability to capture the full spectrum of potential shapes encountered inreal-world atmospheric data.

This thesis proposes to introduce a third normal pdf component strategically positioned between the existing two, significantly enhancing the model’s representational flexibility. This trinormal representation allows for a wider range of grid-layer shapes while permitting analytic solutions for certain higher order moments.

The core of this …

Coarse Homotopy Extension Property And Its Applications, William Braubach

Theses and Dissertations

A pair (X, A) has the homotopy extension property if any homotopy of A the extends overX × {0} can be extended to a homotopy of X. The main goal of this dissertation is to define a coarse analog of the homotopy extension property for coarse homotopies and prove coarse versions of results from algebraic topology involving this property. First, we define a notion of a coarse adjunction metric for constructing coarse adjunction spaces. We use this to redefine coarse CW complexes and to construct a coarse version of the mapping cylinder. We then prove various pairs of spaces have …

Examination Of Chemical Variations In Fossil Resin With Two-Photon Excitation Fluorescence And Paleobotanical Inventory Reports On National Park Service Units, Katherine Mae Maxine Bober

Theses and Dissertations

Fossil resin can be difficult to chemically characterize due to its complex chemistry which can be complicated by a unique chemistry for each fossil resin sample. Using two-photon excitation fluorescence micro-spectroscopy, we measured the wavelengths at peak emission intensity: we compared these fluorescence results to FTIR spectra. There are variations in fluorescence which indicate differences in botanic origin. This method may be used in future research to better understand botanic origin when more traditional analyses fail.There has been a need for a comprehensive paleobotanical inventory report for NPS units. Four teams consisting of graduate students and mentors are completing the …

Utilizing Arma Models For Non-Independent Replications Of Point Processes, Lucas M. Fellmeth

Theses and Dissertations

The use of a functional principal component analysis (FPCA) approach for estimatingintensity functions from prior work allows us to obtain component scores of replicated point processes under the assumption of independent replications. We show these component scores can be modeled using classical autoregressive moving average (ARMA) models, thus allowing us to also apply the FPCA model to non-independent replications. The Divvy bike-sharing system in the city of Chicago is showcased as an application.

An Assessment Of The High-Resolution Rapid Refresh Model’S Ability To Resolve The Great Lakes Marine Atmospheric Boundary Layer And Lake-Breeze Front, Collin Paul Deyoung

Theses and Dissertations

We determined the ability of the High-Resolution Rapid Refresh (HRRR) mesoscale model to predict the lake-breeze front’s structure and faithfully represent the marine atmospheric boundary layer (MABL) behind it. First, two field missions were completed during the 2023 warm season over Lake Michigan to characterize the spatiotemporal evolution of the MABL and validate HRRR forecasts. We found the Lake Michigan MABL was characterized by minimal thermodynamic and kinematic variability on diurnal time scales, regardless of the stability or flow regime. Additionally, the HRRR was able to resolve MABL thermodynamic structures effectively but underestimated the vertical temperature distribution, leading to a …

Rapid Parameter Estimation Of Compact Binary Coalescences With Gravitational Waves, Caitlin Rose

Theses and Dissertations

In the age of multi-messenger astrophysics, fast, reliable information about gravitational-wave candidates is crucial for electromagnetic follow-up observations. While sky localization tells astronomers where to observe an event, source classification estimates the probability that the event might have an electromagnetic counterpart. Furthermore, astronomers need to have enough time to point their telescopes towards the fading light. Rapid PE is a low-latency parameter estimation scheme which parallelizes Bayesian inference by fixing the intrinsic parameters to a grid, and marginalizing over the extrinsic parameters at each grid point via Monte Carlo sampling. The gravitational-wave search pipelines identify the highest signal-to-noise ratio (SNR) …

Bayesian Change Point Detection In Segmented Multi-Group Autoregressive Moving-Average Data For The Study Of Covid-19 In Wisconsin, Russell Latterman

Theses and Dissertations

Changepoint detection involves the discovery of abrupt fluctuations in population dynamics over time. We take a Bayesian approach to estimating points in time at which the parameters of an autoregressive moving average (ARMA) change, applying a Markov chain Monte Carlo method. We specifically assume that data may originate from one of two groups. We provide estimates of all multi-group parameters of a model of this form for both simulated and real-world data sets. We include a provision to resolve the problem of confounding ARMA parameter estimates and variance of segment data. We apply our model to identify points in time …

A Statistical Fetch Model For Water Wave Glint Correction Using Worldview-3 Imagery, Amanda Jade Quintanilla

Theses and Dissertations

Sun glint in satellite imagery of the water surface contaminates the upwelling signal received by a detector. Many models exist that attempt to correct for this wave facet effect and phenomena. In this work a model for sun glint correction is created using the comparison of image transects between two nearly simultaneously collected images of the same area, although with differing sensor geometry. One image utilized in this research is almost entirely glint free while the other is contaminated by water wave facet glint. Although many models for removing sun glint exist based on various techniques, none are completely accurate, …

Deep Learning In Indus Valley Script Digitization, Deva Munikanta Reddy Atturu

Theses and Dissertations

This research introduces ASR-net(Ancient Script Recognition), a groundbreaking system that automatically digitizes ancient Indus seals by converting them into coded text, similar to Optical Character Recognition for modern languages. ASR-net, with an 95% success rate in identifying individual symbols, aims to address the crucial need for automated techniques in deciphering the enigmatic Indus script. Initially Yolov3 is utilized to create the bounding boxes around each graphemes present in the Indus Valley Seal. In addition to that we created M-net(Mahadevan) model to encode the graphemes. Beyond digitization, the paper proposes a new research challenge called the Motif Identification Problem (MIP) related …

Modelling Terrestrial And Potential Extraterrestrial Photopigments Via Density Functional Theory, Dorothea Illner

Theses and Dissertations

In the search for extraterrestrial life, biosignatures play a crucial role in identifying its putative traces. A commonly known and robust biosignature is the Vegetation Red Edge (VRE), which can be described as a sharp increase of reflectance observed from a planet and stems from the light absorption of photopigments in specific regions in the electromagnetic spectrum. For Earth, this VRE is known to occur around 700 nm, however, if the photopigments absorb light in different regions and have different structures the VRE could experience a wavelenght shift.

In this work, Chlorophyll a and a potential photopigment precursor called Phot0 …

Space Transformation For Open Set Recognition, Atefeh Mahdavi

Theses and Dissertations

Open Set Recognition (OSR) is about dealing with unknown situations that were not learned by the models during training. In OSR, only a limited number of known classes are available at the time of training the model and the possibility of unknown classes never seen at training time emerges in the test environment. In such a setting, the unknown classes and their risk should be considered in the algorithm. Such systems require not only to identify and discriminate instances that belong to the source domain (i.e., the seen known classes contained in the training dataset) but also to reject unknown …