Physical Sciences and Mathematics Commons^™

Rocket Learn, Daanesh Ibrahim, Jules Stacy, David Stroud, Yusi Zhang

SMU Data Science Review

Abstract. This paper covers the development, testing, and implementation of Reinforcement Learning methods designed to autonomously learn and optimize Rocket League play. This study aims to analyze and benchmark model frameworks commonly used in Reinforcement Learning applications. These models can be applied to tasks ranging in difficulty from simple to superhumanly complex, and this study will begin with and build upon simple models performing simple tasks. It will result in complex models performing difficult tasks. Models will be allowed to train autonomously on the game using mass parallelization to expedite training times with the goal of maximizing reward function scores. …

Real-Time Voice Biometric Speaker Verification, Inderbir Dhillon, Jason Rupp, Aniketh Vankina, Robert Slater

SMU Data Science Review

Abstract. Automated speaker verification has been an area of increased research in the last few years, with a special interest in metric learning approaches that compute distances between speaker voiceprints. In this paper, three metric learning systems are built and compared in a one-shot speaker verification task using contrastive max-margin loss, triplet loss, and quadruplet loss. For all the models, spectrograms are created from speaker audio. Convolutional Neural Network embedding layers are trained to produce compact voiceprints that allow users to be distinguished using distance calculations. Performances of the three models were similar, but the model with the best EER …

Pokégan: P2p (Pet To Pokémon) Stylizer, Michael B. Hedge, Morgan Nelson, Thomas Pengilly, Michael Weatherford

SMU Data Science Review

This paper covers the development, testing, and implementation of an automatic framework for converting common images of pets into a Pokémon cartoon with the style of a Pokémon trading card. The technique will first implement object detection for common animals to facilitate image segmentation and apply the appropriate style transfer model to ensure the most aesthetic stylization. It explores various methods to address artifacts in the results of common neural style transfer techniques using Generative Adversarial Networks (GANs). This research sets up a framework to create an app that converts user-submitted pet pictures to Pokémon styled images using the most …

Machine Learning Approach To Distinguish Ulcerative Colitis And Crohn’S Disease Using Smote (Synthetic Minority Oversampling Technique) Methods, Kris Ghimire, Walter Lai, Yasser Omar, Thad Schwebke, Jamie Vo

SMU Data Science Review

Irritable Bowel Disease (IBD) affects a sizable portion of the US population, causing symptoms such as vomiting, abdominal pain, and diarrhea. Despite the disease’s prevalence, the precise cause is not fully understood. This study consists of endoscopic and histological data from patients diagnosed with IBD and a control population for reference. The machine learning models' focus is to classify patients into IBD types. Several models were analyzed, including decision trees, logistic regression, and k-nearest neighbors. In addition, various methods of SMOTE were applied to determine the most effective transformation and ensuring that the dataset is balanced. The best model with …

Urban Traffic Simulation: Network And Demand Representation Impacts On Congestion Metrics, Aaron Faltesek, Balasubramaniam Dakshinamoorthi, Sreeni Prabhala, Akbar Thobani, Anu Kuncheria, Jane Macfarlane

SMU Data Science Review

Traffic simulations are often used by city planners as a basis for predicting the impact of policies, plans, and operations. The complexities underpinning traffic simulations are often not described in detail yet can significantly impact the simulation outcome. Conflating underlying data for simulations is complex and hinders the interest in this type of exploration. This paper aims to elucidate critical features of traffic simulations that drive the generated metrics of the modeled urban environment. Specifically, this paper examines differences in two road graph networks for the metropolitan region of Houston, TX: a reduced network composed of 45,675 road links and …

Intelligent Investment Portfolio Management Using Time-Series Analytics And Deep Reinforcement Learning, Sachin Chavan, Pradeep Kumar, Tom Gianelle

SMU Data Science Review

Abstract. – With globalization, the capital markets have exploded in size and value, making them exceedingly difficult to predict. These days the public has access to real-time data of the market-leading to more participation. As a positive step, this might lead to better wealth distribution in the society, and it also adds to the random nature of the market, making it more unpredictable. The portfolio accounts consisting of stocks and bonds are considered serious investment assets. They can make or break a person’s future. It is also a way of shielding one against market risk or rising inflation. These accounts, …

Identifying Vacant Lots To Reduce Violent Crime In Dallas, Texas, Laura Lazarescou, Andrew Mejia, Tina Pai, Sabrina Purvis, Robert Slater, Owen Wilson-Chavez

SMU Data Science Review

Vacant lots have been associated with community violence for many years. Researchers have confirmed a positive correlation between vacant lots and vacant buildings with increased violence in urban and rural geographies. However, identifying vacant lots has been a challenge, and modeling methods were largely manual and time-intensive. This prevented cities and non-profit organizations from acting on the information since it was expensive and high-risk to develop remediation programs without clearly understanding where or how many vacant lots existed.

The primary objective of this study was to provide a predictive model that accelerates and improves the accuracy of prior land classification …

Identification And Characterization Of Forest Fire Risk Zones Leveraging Machine Learning Methods, Joshua Balson, Matt Chinchilla, Cam Lu, Jeff Washburn, Nibhrat Lohia

SMU Data Science Review

Across the United States, record numbers of wildfires are observed costing billions of dollars in property damage, polluting the environment, and putting lives at risk. The ability of emergency management professionals, city planners, and private entities such as insurance companies to determine if an area is at higher risk of a fire breaking out has never been greater. This paper proposes a novel methodology for identifying and characterizing zones with increased risks of forest fires. Methods involving machine learning techniques use the widely available and recorded data, thus making it possible to implement the tool quickly.

Qualitative Leveraging Natural Language Processing To Establish Judge Incrimination Statistics To Educate Voters In Re-Elections, Aurian Ghaemmaghami, Paul Huggins, Grace Lang, Julia Layne, Robert Slater

SMU Data Science Review

The prevalence of data has given consumers the power to make informed choices based off reviews, ratings, and descriptive statistics. However, when a local judge is coming up for re-election there is not any available data that aids voters in making data-driven decision on their vote. Currently court docket data is stored in text or PDFs with very little uniformity. Scaling the collection of this information could prove to be complicated and tiresome. There is a demand for an automated, intelligent system that can extract and organize useful information from the datasets. This paper covers the process of web scraping …

The Fierce Green Fire: Vol. 12 Issue 9, Wofford College. Department Of Environmental Studies

The Fierce Green Fire

No abstract provided.

The Emission Spectrum Of The Hot Jupiter Wasp-79b From Hst/Wfc3, Trevor O. Foote, Nikole K. Lewis, Brian M. Kilpatrick, Jayesh M. Goyal, Giovanni Bruno, Hannah R. Wakeford, Nina Robbins-Blanch, Tiffany Kataria, Ryan J. Macdonald, Mercedes López-Morales, David K. Sing, Thomas Mikal-Evans, Vincent Bourrier, Gregory Henry, Lars A. Buchhave

Information Systems and Engineering Management Research Publications

Here we present a thermal emission spectrum of WASP-79b, obtained via Hubble Space Telescope Wide Field Camera 3 G141 observations as part of the PanCET program. As we did not observe the ingress or egress of WASP-79b's secondary eclipse, we consider two scenarios: a fixed mid-eclipse time based on the expected occurrence time, and a mid-eclipse time as a free parameter. In both scenarios, we can measure thermal emission from WASP-79b from 1.1 to 1.7 μm at 2.4σ confidence consistent with a 1900 K brightness temperature for the planet. We combine our observations with Spitzer dayside photometry (3.6 and 4.5 …

The Effects Of Hydrologic Heterogeneity On Harmful Algal Blooms In Freshwater Reservoir, Lake Sinclair, Georgia, Margaret Blackledge

Biology Theses

Aquatic habitats are frequently studied after a major water quality problem like the occurrence of an algal bloom. In this study, A proactive rather than a reactive response was considered, where the complexity of conditions conducive to uncontrolled cell growth were studied before a bloom took place by sampling regularly. This study aimed to monitor water quality by monthly sampling of algal communities for approximately one year. As the base of the aquatic food web, algae are a highly diverse group of organisms with varying sensitivity to physical and chemical changes in the environment. Four shallow sites were monitored at …

Eating Detection With A Head-Mounted Video Camera, Shengjie Bi, David Kotz

Computer Science Technical Reports

In this paper, we present a computer-vision based approach to detect eating. Specifically, our goal is to develop a wearable system that is effective and robust enough to automatically detect when people eat, and for how long. We collected video from a cap-mounted camera on 10 participants for about 55 hours in free-living conditions. We evaluated performance of eating detection with four different Convolutional Neural Network (CNN) models. The best model achieved accuracy 90.9% and F1 score 78.7% for eating detection with a 1-minute resolution. We also discuss the resources needed to deploy a 3D CNN model in wearable or …

Epa Region 8 Qa Document Review Crosswalk, Trec Inc., A Woodard And Curran Company, Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Residential Metals Abatement Program Quality Assurance Project Plan (Non-Residential Parcels – Indoor Dust), Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Developing Techniques For The Identification Of Non-Canonical Rna Pairing And Analysis Of Lc-Ms Datasets, Christopher Jurich

Department of Chemistry: Dissertations, Theses, and Student Research

Non-canonical pairing dynamics in ribonucleic acid (RNA) structureand statistical analysis of metabolomics liquid chromatography mass spectrometry (LC-MS) datasets are two difficult problems that stand as open challenges.

RNA folding algorithms are used across a variety of disciplines to predict structures when experimental elucidation techniques are inconvenient or impractical. Though successful and widely adopted, folding algorithms make simplifying assumptions for loop regions due to their complex interactions and associated difficulty with generating energy parameters for relevant non-canonical pairing interactions. Modeling assumptions and a lack of energy parameters for loops limit accuracy in these functional critical regions of RNA. This work describes …

Numerical Study Of The Seiqr Model For Covid-19, Caitlin Holt

Departmental Honors & Graduate Capstone Projects

In this research project, we used numerical methods to investigate trends in the susceptible, exposed, infectious, quarantined, recovered, closed cases and insusceptible populations for the COVID-19 pandemic in 2021. We used the SEIQR model containing seven ordinary differential equations, based on the SIR model for epidemics. An analytical solution was derived from a simplified version of the model, created by making various assumptions about the original model. Numerical solutions were generated for the first 100 days of 2021 using algorithms based on Euler's Method, Runge-Kutta Method, and Multistep Methods. Our goal is to show that numerical methods can help us …

Uniting Non-Empirical And Semi-Empirical Density Functional Approximation Strategies Using Constraint-Based Regularization, Trine K. Quady

University Honors Theses

In this work, we present a general framework that unites the two primary strategies for constructing density functional approximations (DFAs): non-empirical (NE) constraint satisfaction and semi-empirical (SE) data-driven optimization. The proposed method employs B-splines--bell-shaped spline functions with compact support--to construct each inhomogeneity correction factor (ICF). This choice offers several distinct advantages over a polynomial basis by enabling explicit enforcement of linear and non-linear constraints as well as ICF smoothness using Tikhonov regularization and penalized B-splines (P-splines). As proof of concept, we use this approach to construct CASE21--a Constrained And Smoothed semi-Empirical global hybrid generalized gradient approximation that completely satisfies all …

Electrocatalytic Oxidation Of Carbohydrates Via Surface Immobilized Viologen, Dallin D.V. Scott

Theses and Dissertations

Earths most abundant biomolecules, carbohydrates, offer tremendous potential forelectricity production. Carbohydrate fuel cells are electrical fuel cells that can harvest the stored electrons in carbohydrates and offer a cheap and efficient method that could help solve growing energy demands, while providing a renewable green energy source. Viologen-mediated carbohydrate fuel cells have demonstrated the ability to accelerate carbohydrate oxidation while decreasing partial or incomplete oxidation products reducing the electricity production. Subsequent studies suggested polymeric viologen compounds could improve the efficiency by increasing the local concentration of viologen. This thesis presents the utility of surface-immobilized viologen mediators for the oxidation of simple …

Galectin-1: Development Of A Novel Protein Therapy For Lgmd2b, Mary Lorena Vallecillo Munguia

Theses and Dissertations

Muscular dystrophies are a heterogeneous group of genetic diseases that involve mutations in genes leading to progressive muscular weakness. Limb-Girdle Muscular Dystrophy 2B (LGMD2B) is a subset of muscular dystrophy caused by mutations in the DYSF gene, which encodes for dysferlin protein and has an incidence of 1/100,000-1/200,000 people, or 1/300 people of Libyan Jewish descent. Since there is no effective treatment that can cure or reverse effects of LGMD2B once diagnosed, our goal is to investigate and develop a protein therapy that mitigates effects of this disease in patients. Galectin-1 (Gal-1) is a small, soluble 14.5 kDa protein with …

Comparative Toxicity, Phytochemistry, And Use Of 53 Philippine Medicinal Plants, Lydia M. Clemen-Pascual, Rene Angelo S. Macahig, Nina Rosario L. Rojas

Chemistry Faculty Publications

The study compares the toxicity of 53 selected medicinal plants commonly used in the Philippines to treat various diseases. It uses as a benchmark Vitex negundo L., which was approved by the Philippine Food and Drug Administration as an herbal drug for cough and asthma after passing clinical trials for safety and efficacy. The methods were chosen for their simplicity and accessibility even for resource-limited laboratories. Extracts (95 % ethanol) of the medicinal parts of the plants were (1) chemically profiled using qualitative phytochemical tests that detect the presence of key classes of bioactive compounds; and (2) evaluated for toxicity …

Stratigraphic Analysis Of The Capps Limestone In The North Norton Oil Field In Runnels County, Texas, William Thompson

Electronic Theses and Dissertations

The Desmoinesian (Middle Pennsylvanian) Capps Limestone Member of the Mineral Wells Formation is a carbonate reservoir located in North Central Texas. It consists of interbedded limestone, sandstone, and shale units. Much of the Capps Limestone exists in the subsurface of Brown, Coleman, Runnels, Coke, Nolan, and Taylor counties, however, the Capps Limestone outcrops on the surface in Brown, Eastland, and Palo Pinto counties.

The cored interval from Runnels County was deposited in a marginal marine environment during the Middle Pennsylvanian Period. Although the Capps Limestone was first described in the 1890s, there is still much to be discovered about its …

Microwave-Promoted Iminyl Radical Fragmentations And The Total Synthesis Of Yaku'amide A And Its Simplified Analogues, Concordia Lo

Theses and Dissertations

The first project in this dissertation describes the use of microwave-promoted iminyl radical fragmentations to form functionalized nitriles. Nitrogen-centered radical chemistry is a useful tool to construct valuable C-N bonds commonly found in pharmaceuticals and biologically active molecules. Classically, these reactions require the use of toxic initiators and propagators. Iminyl radical chemistry has been gaining momentum as a means of avoiding these harsh conditions. This project utilizes the fragmentation of cyclic iminyl radicals via irradiation of O-phenyl oxime ethers to produce a synthetically useful nitrile tethered to an alkyl radical in the absence of metal catalysts and redox chemistry. The …

Disease Biomarker Discovery And Fungal Metabolites Extraction Protocol Optimization Using Gcms Based Metabolomics, Chathuri Udeshika Gamlath Mohottige

Theses and Dissertations

Metabolomics is a powerful science that can be applied for the discovery of disease biomarkers, and investigation of altered metabolomes due to abiotic and biotic perturbations. This dissertation is focused on untargeted metabolomic applications to investigate fungal metabolite alterations associated with pathogenicity, fungal disease propagations, and symbiosis. This dissertation employs qualitative analysis of metabolite mixtures using HS-SPME coupled GC-MS and TMS derivatization followed by GC-MS analytical platforms. In the first study, we discovered a biomarker combination to diagnose fungal soft tissue disease in sweet potato at an early stage of disease propagation. We used an HS-SPME GC-MS untargeted metabolomics workflow …

Basis For Changes In The Disease Burden Estimates Related To Vitamin A And Zinc Deficiencies In The 2017 And 2019 Global Burden Of Disease Studies, Sonja Y. Hess, Alexander C. Mclain, Haley Lescinsky, Kenneth H. Brown, Ashkan Afshin, Reed Atkin, Saskia Jm Osendarp

Faculty Publications

Background:

The Global Burden of Disease (GBD) Study provides estimates of death and disability from eighty-seven risk factors, including some micronutrient deficiencies. Objectives:

To review methodological changes that led to large differences in the disease burden estimates for vitamin A and Zn deficiencies between the GBD 2017 and 2019 Studies. Methods:

GBD publications were reviewed; additional information was provided by GBD researchers. Results:

Vitamin A deficiency prevalence is based on plasma retinol concentration, whereas the estimate for Zn deficiency prevalence uses dietary adequacy as a proxy. The estimated global prevalence of vitamin A deficiency for children aged 1–4 years in …

Quantitative Stem: A Method For Measuring Temperature And Thickness Effects On Thermal Diffuse Scattering Using Stem/Eels, And For Testing Electron Scattering Models, Paul S. Minson

Theses and Dissertations

In the last two decades, advances in the dark field detectors and microscopes of scanning transmission electron microscopy (STEM) have inspired a resurgence of interest in quantitative STEM analysis. One promising avenue is the use of STEM as a nanothermometric probe. In this application, thermal diffuse scattering, captured by a CCD camera or an annular dark field detector, acts as an indirect measurement of the specimen temperature. One challenge with taking such a measurement is achieving adequate sensitivity to quantify a change in scattered electron signal on the order of 1% or less of the full electron beam. Another difficulty …

Field Investigations And Numerical Modeling Of Earthquake And Tsunami Risk At Four Vulnerable Sites In Indonesia, Claire E. Ashcraft

Theses and Dissertations

Maps and models of seismic and tsunami risk are constructed from a variety of measurements taken in Indonesia, which have the potential to reduce loss of life and infrastructure. The first study uses the multichannel analysis of surface waves (MASW) method to calculate the time-averaged shear wave velocity to 30 m depth (Vs30). These measurements were taken at 58 sites in the city of Pacitan, Java and on the islands of Lombok, Ambon, and the Banda Islands. Vs30 calculations are compared with local geologic maps to extrapolate site class for locations not measured directly. Site class maps are then compared …

Silver Bow Creek/Butte Area Npl Site Butte Priority Soils Operable Unit, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Nuclear Transparency From Quasi-Elastic $^{12}C(E,E'P)$ Scattering Reaction Up To $Q^2=14.2 ~(Gev/C)^{2}$ In Hall C At Jefferson Lab, Deepak Kumar Bhetuwal

Theses and Dissertations

Color Transparency $(CT)$ is a unique prediction of Quantum Chromodynamics $(QCD)$ where the final (and/or initial) state interactions of hadrons with the nuclear medium are suppressed for exclusive processes at high momentum transfers. While this phenomenon has been observed for mesons, there has never been a conclusive observation for baryons. A clear signal of $CT$ for baryons would be the first evidence of baryons fluctuating to a small size in the nucleus, and the onset would show the transition from nucleon-meson picture to quark-gluon degrees of freedom. The experiment $E1206107$, searching for the onset of $CT$ in protons was completed …

1,2-Diazetidine As A New Amidomethylative Reagent To Control The Selectivity For The Synthesis Of N-Heterocycles And Ru(Ii)-Catalyzed Enantioselective Hydroarylation To Form Chromane Derivatives, Chaminda Lakmal Hetti Handi

Theses and Dissertations

1,2-Diazetidine is a four-membered ring heterocyclic compound which has two adjacent nitrogen atoms. However, the syntheses of C-unsubstituted 1,2-diazetidines are rarely reported in the literature. C-unsubstituted 1,2-diazetidines were synthesized through an operationally simple intermolecular vicinal disubstitution reaction between 1,2-dibromoethane and hydrazine with N-arylsulfonyl as the protecting group. Several different types of C-unsubstituted 1,2-diazetidines derivatives were synthesized with either two of the same or two different N-arylsulfonyl groups. The electronic and steric properties were analyzed using Raman spectroscopy and computational calculations. Then, several synthetic applications were demonstrated with 1,2-ditosyl-1,2-diazetidine (DTD). As a synthetic application, a nucleophilic ring-opening reaction of the diazetidine …