Statistics and Probability Commons^™

Identifying A Group Of Factors Predicting Cognitive Impairment Among Older Adults, Longgang Zhao, Yuan Wang, Eric Mishio Bawa, Zichun Meng, Jingkai Wei, Sarah Newman-Norlund, Tushar Trivedi, Hatice Hasturk, Roger Newman-Norlund, Julius Fridriksson Ph.D., Anwar T. Nerchant

Faculty Publications

Background

Cognitive impairment has multiple risk factors spanning several domains, but few studies have evaluated risk factor clusters. We aimed to identify naturally occurring clusters of risk factors of poor cognition among middle-aged and older adults and evaluate associations between measures of cognition and these risk factor clusters.

Methods

We used data from the National Health and Nutrition Examination Survey (NHANES) III (training dataset, n = 4074) and the NHANES 2011–2014 (validation dataset, n = 2510). Risk factors were selected based on the literature. We used both traditional logistic models and support vector machine methods to construct a composite score …

Gender And The Billboard Top 40 Charts Between 1958 And 2023, Brileigh Cates, Justin W. Pope

Undergraduate Research Conference at Missouri S&T

Is there an inherent bias towards male artists in the music industry? Evidence has been shown in previous studies, the most recent being from 2017, that there may be bias towards male artists appearing in Billboard Magazine s Hot 100 list. This study not only updates previous data to include 2017 through 2023, but also looks at the top 40 charts on a week-by-week bias as opposed to the year-end charts that other studies used for their data. We coded each song so as to indicate the gender of the artist(s) as well as whether or not the artists appeared …

The History Of The Billboard Hot 100 And Its Process, Brileigh Cates

Undergraduate Research Conference at Missouri S&T

The Billboard Hot 100 has been around for decades, and it is believed without much accreditation. What really is Billboard, and why is it so popular? Why have other charting companies not taken up as much popularity? How does Billboard determine the popularity of artists? How has this changed with the introduction of the internet? This research project addresses all of these question, allowing the validity of the data collection to be addressed.

Numerical Studies On Bose-Einstein Condensates, Megan Benkendorf

Undergraduate Research Conference at Missouri S&T

Bose-Einstein condensate (BEC) is a state of matter near absolute zero temperature for which all atoms lose their individual properties and condense into a macroscopic coherent "super-wave". The superfluidity of BEC has been the focus of active research since the first experimental realization of BEC in 1995. The recent launch of the Cold Atom Laboratory to the space station on May 21, 2018, has once again drawn spotlights to these fascinating properties of BEC. In this project, we will carry out numerical studies to understand the behavior of exciton-polariton BECs. A modified Gross-Pitaevskii equation is used to model the dynamics …

Numerical Studies On Bose–Einstein Condensates, Megan Benkendorf

Undergraduate Research Conference at Missouri S&T

Bose-Einstein condensate (BEC) is a state of matter near absolute zero temperature for which all atoms lose their individual properties and condense into a macroscopic coherent "super-wave". The superfluidity of BEC has been the focus of active research since the first experimental realization of BEC in 1995. The recent launch of the Cold Atom Laboratory to the space station on May 21, 2018, has once again drawn spotlights to these fascinating properties of BEC. In this project, we will carry out numerical studies to understand the behavior of exciton-polariton BECs. A modified Gross-Pitaevskii equation is used to model the dynamics …

Towards Fast, Realistic Gas Plume Simulation For Lwir Hyperspectral Images To Improve Deep Learning Identification Models, Scout Jarman

Student Research Symposium

• Longwave infrared (LWIR) hyperspectral images (HSI) are taken from airborne platforms and can be used to find gas plumes.
• Detection and identification of gas plumes has applications in environmental monitoring, disaster response, and national security
• Deep learning can be used to identify gases from a large library of materials,  but can be difficult to apply in practice

Genomic Population Structure Of Great Hammerhead Sharks (Sphyrna Mokarran) Across The Indo-Pacific, Naomi L. Brunjes, Samuel M. Williams, Alexis L. Levengood, Matt K. Broadhurst, Vincent Raoult, Alastair V. Harry, Matias Braccini, Madeline E. Green, Julia L. Y. Spaet, Michael J. Travers, Bonnie J. Holmes

Fisheries Research Articles

Context

Currently, little information exists describing the population structure of great hammerhead sharks (Sphyrna mokarran) in Australian waters. Aims

This study used single nucleotide polymorphisms to investigate fine-scale population structure in S. mokarran across the Indo-Pacific. Methods

DNA was extracted from 235 individuals across six Australian locations and a Red Sea outgroup. Population parameters were calculated and visualised to test structuring across locations. Key results

No fine-scale population structuring was observed for S. mokarran across the Indo-Pacific. However, population structuring occurred for all Australian locations when compared to the Red Sea outgroup. Conclusions

Findings suggest a single stock …

Optimizing Nba Roster Construction, Nick R. Riccardi

Sport Management - All Scholarship

This study aims to quantify the effect that complementary player types have on team success in the National Basketball Association. Using cluster analysis, player-seasons are redefined from their traditional basketball positions to better encompass the roles that players play. For the 10 seasons of data, the best player for each of the 30 teams in the league is determined and teams are grouped based on the cluster of their best player. Ordinary Least Squares regressions are performed to test what player types fit together best. The results of this study show the importance of complementary workers to a firm’s success.

Artificial Intelligence Could Probably Write This Essay Better Than Me, Claire Martino

Augustana Center for the Study of Ethics Essay Contest

No abstract provided.

The Social And Economic Dimensions Of One Of The World’S Longest-Operating Shark Fisheries, Matias Braccini, Maddison Watt, Clinton Syers, Nick Blay, Matthew Navarro, Michael Burton

Fisheries Research Articles

Context

Social and economic information is limited for coastal commercial and recreational fisheries, particularly shark fisheries, which are perceived as unsustainable and as targeting sharks for fins.

Aims

To characterise the social and economic dimensions of one of the world’s few long-standing sustainable shark fisheries.

Methods

We reviewed historic data and surveyed stakeholders to understand the economic and social dimensions of the shark fishery currently operating in Western Australia.

Key results

Since the fishery’s historic peak, there has been a substantial reduction in the number of operating vessels and ports due to management intervention. For the vessels that have remained, …

Comparative Analysis Of Time Series Models On U.S. Stock And Exchange Rates: Bayesian Estimation Of Time Series Error Term Model Versus Machine Learning Approaches, Young Keun Yang

USF Tampa Graduate Theses and Dissertations

This study presents a comparative analysis of contemporary applications of time series models, focusing on the Bayesian approach. In contrast to many nonparametric studies, the Bayesian approach circumvents the common issue of bandwidth selection by offering systematic estimation and avoiding ad hoc methods. Specifically, we delve into the Bayesian approach for estimating the autocovariance function of a time series model’s error term. Traditional time series models often make the unrealistic assumption of a constant error term. Furthermore, models such as autoregressive conditional heteroskedasticity (ARCH) and general autoregressive conditional heteroskedasticity (GARCH) address the limitation of constant variance by assuming an autoregressive …

Effects Of Sars-Cov-2 Variants On Cd8+ T Cell Epitope Diversity: Estimating Clinical Severity In The United States, Grace Kim, Jacob Elnaggar, Maya Sevalia, Najah Nicholas, Mallory Varnado, Judy Crabtree, Lucio Miele

School of Medicine Faculty Publications

Association for Clinical and Translational Science 2024; April 3 - April 5, 2024; Las Vegas, NV

How Generative Ai Models Such As Chatgpt Can Be (Mis)Used In Spc Practice, Education, And Research? An Exploratory Study, Fadel M. Megahed, Ying-Ju (Tessa) Chen, Joshua A. Ferris, Sven Knoth, L. Allison Jones-Farmer

Mathematics Faculty Publications

Generative Artificial Intelligence (AI) models such as OpenAI's ChatGPT have the potential to revolutionize Statistical Process Control (SPC) practice, learning, and research. However, these tools are in the early stages of development and can be easily misused or misunderstood. In this paper, we give an overview of the development of Generative AI. Specifically, we explore ChatGPT's ability to provide code, explain basic concepts, and create knowledge related to SPC practice, learning, and research. By investigating responses to structured prompts, we highlight the benefits and limitations of the results. Our study indicates that the current version of ChatGPT performs well for …

Uncertainty Analysis In Machine Learning Models, Ayorinde E. Olatunde, Weiqi Yue, Pawan K. Tripathi, Roger H. French, Anirban Mondal

Faculty Scholarship

No abstract provided.

Advancing Text Summarization And Classification: Deep Insights From Transformer-Based Statistical Learning, Kun Bu

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) is a part of human's daily life nowadays. Machine Learning (ML) as one aspect from AI has been rapidly developing during the past two decades, especially from the statistical learning approaches, which emphasized the use of probability and statistics to model data, such as Support Vector Machines (SVMs) for classification and regression tasks to the ensemble learning techniques, such as Random Forest, Gradient Boosting Machine (GBM), and stacking. Ensemble learning has evolved into a pivotal concept in contemporary machine learning, empowering practitioners to amalgamate multiple models to enhance generalization, accuracy, and robustness. As the field of machine …

Associations Between Sleep Duration, Sleep Disturbance And Cardiovascular Disease Biomarkers Among Adults In The United States, Prince Nii Ossah Addo, Paddington T. Mundagowa, Longgang Zhao, Mufaro Kanyangarara, Monique J. Brown Ph.D., Mph, Jihong Liu Sc.D.

Faculty Publications

Background

Sleep problems are associated with abnormal cardiovascular biomarkers and an increased risk of cardiovascular diseases (CVDs). However, studies investigating associations between sleep problems and CVD biomarkers have reported conflicting findings. This study examined the associations between sleep problems and CVD biomarkers in the United States.

Methods

Data were from the National Health and Nutrition Examination Survey (NHANES) (2007–2018) and analyses were restricted to adults ≥ 20 years (n = 23,749). CVD biomarkers [C-reactive Protein (CRP), low-density lipoproteins, high-density lipoproteins (HDL), triglycerides, insulin, glycosylated hemoglobin (HbA1c), and fasting blood glucose] were categorized as abnormal or normal using standardized cut-off …

A Systematic Review: Mirror Neurons & Schizophrenia, Yashesvi Sharma, Surajit Dey

Annual Research Symposium

This research project establishes a link between Mirror Neuron System (MNS) activity and this information's implications in treating and understanding schizophrenia, specifically, schizophrenic patients with negative symptoms.

Variable-Order Fractional Laplacian And Its Accurate And Efficient Computations With Meshfree Methods, Yixuan Wu, Yanzhi Zhang

Mathematics and Statistics Faculty Research & Creative Works

The variable-order fractional Laplacian plays an important role in the study of heterogeneous systems. In this paper, we propose the first numerical methods for the variable-order Laplacian (-Δ) α (x) / 2 with 0 < α (x) ≤ 2, which will also be referred as the variable-order fractional Laplacian if α(x) is strictly less than 2. We present a class of hypergeometric functions whose variable-order Laplacian can be analytically expressed. Building on these analytical results, we design the meshfree methods based on globally supported radial basis functions (RBFs), including Gaussian, generalized inverse multiquadric, and Bessel-type RBFs, to approximate the variable-order Laplacian (-Δ) α (x) / 2. Our meshfree methods integrate the advantages of both pseudo-differential and hypersingular integral forms of the variable-order fractional Laplacian, and thus avoid numerically approximating the hypersingular integral. Moreover, our methods are simple and flexible of domain geometry, and their computer implementation remains the same for any dimension d ≥ 1. Compared to finite difference methods, our methods can achieve a desired accuracy with much fewer points. This fact makes our method much attractive for problems involving variable-order fractional Laplacian where the number of points required is a critical cost. We then apply our method to study solution behaviors of variable-order fractional PDEs arising in different fields, including transition of waves between classical and fractional media, and coexistence of anomalous and normal diffusion in both diffusion equation and the Allen–Cahn equation. These results would provide insights for further understanding and applications of variable-order fractional derivatives.

Can Compiled Player War Predict Mlb Team Win Percentage?, Thomas Hertel

Mathematics Senior Capstone Papers

The baseball statistic Wins Above Replacement (WAR) is a complex yet effective metric for approximating the contribution of a player to his team through representing how many more wins his team ought to earn than with a AAAA player in his stead. The intent of this paper is to test whether the accumulation of player’s WAR can be extended to satisfy another discipline of SABRmetrics, i.e. predicting an entire team’s future performance, through modeling the sum’s correspondence (or lack thereof) to wins. If WAR is shown to extend in this way then franchise front offices could feasibly isolate it as …

Using Multiple Regression Analysis To Determine The Strength Of Certain Factors On Student Absenteeism, Emmitt Antwine

Mathematics Senior Capstone Papers

During the 2015-16 academic year, approximately 16% of the student population—exceeding 7 million students—were absent from school for 15 days or more. The escalation in chronic absenteeism is influenced by various factors, including poor health conditions, nonstandard work schedules of parents, socioeconomic disadvantages, changes in household compositions, frequent residential relocation, and substantial family responsibilities. Previous research on student absenteeism has examined the negative impacts that chronic absenteeism has had on students in diverse communities such as racial minorities, students with disabilities, and English Language Learners communities. We utilized information obtained from the U.S. Department of Education’s Civil Rights Data Collection …