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Full-Text Articles in Statistics and Probability

Delay Dynamic Equations On Isolated Time Scales And The Relevance Of One-Periodic Coefficients, Martin Bohner, Tom Cuchta, Sabrina Streipert Jul 2022

Delay Dynamic Equations On Isolated Time Scales And The Relevance Of One-Periodic Coefficients, Martin Bohner, Tom Cuchta, Sabrina Streipert

Mathematics and Statistics Faculty Research & Creative Works

We are motivated by the idea that certain properties of delay differential and difference equations with constant coefficients arise as a consequence of their one-periodic nature. We apply the recently introduced definition of periodicity for arbitrary isolated time scales to linear delay dynamic equations and a class of nonlinear delay dynamic equations. Utilizing a derived identity of higher order delta derivatives and delay terms, we rewrite the considered linear and nonlinear delayed dynamic equations with one-periodic coefficients as a linear autonomous dynamic system with constant matrix. As the simplification of a constant matrix is only obtained for one-periodic coefficients, dynamic …


Effect Of Phylogeny Misestimation On Estimating Trait Evolution Parameters, Tabytha Ariel Perez Jul 2022

Effect Of Phylogeny Misestimation On Estimating Trait Evolution Parameters, Tabytha Ariel Perez

Mathematics & Statistics ETDs

Biologists are interested in estimating trait evolution models from phylogenies. However, phylogenies are imperfectly estimated, generally from DNA sequence data. In this study, true phylogenies are simulated to understand whether errors in phylogeny estimation affect inference of the trait evolution model. Given the tree, DNA sequences as well as traits are then simulated from the true phylogeny; both are simulated independently from the other. After the simulation, the DNA sequences were used to estimate trees using the UPGMA method without utilizing the trait information. The estimated trees combined with the traits are used to infer the evolutionary trait models, specifically …


Consequences Of Gulf Of Mexico Estuarine Tropical Cyclone Disturbance Regimes For Fish Assemblage Dynamics Conditionally Depend On Life-History Traits And Niche Characteristics, Stephen Edward Potts Jul 2022

Consequences Of Gulf Of Mexico Estuarine Tropical Cyclone Disturbance Regimes For Fish Assemblage Dynamics Conditionally Depend On Life-History Traits And Niche Characteristics, Stephen Edward Potts

LSU Doctoral Dissertations

Tropical cyclones (TC) are intense, localized disturbances that can potentially cause extensive damage to ecosystems. This dissertation is motivated by a need for interdisciplinary study of TC-ecosystem dynamics with applications to ecology, geography, and analytical methodology. I explore concept linkages between TC dynamics and ecosystems to characterize TC-ecosystem relationships as ecological disturbance regimes. This dissertation tests hypotheses and relationships of TC effects on estuarine fish assemblages in the north-western Gulf of Mexico. I explore concepts in TC-ecosystem relationships to link biotic dynamics with physical disturbance.

In Chapter 2, I compared spatial performance of generalized linear models (GLMs) and generalized additive …


Impact Of Oil And A Tropical Cyclone On An Omnivore And Herbivore Population In Salt Marshes Of Louisiana, Hannah K. Gordon Jul 2022

Impact Of Oil And A Tropical Cyclone On An Omnivore And Herbivore Population In Salt Marshes Of Louisiana, Hannah K. Gordon

LSU Master's Theses

Terrestrial arthropods are the ideal ecological indicators for the health of a salt marsh. Salt marshes are under extreme continuous stressors including climate change, land loss, oil spills, and tropical cyclones. Such stressors impact trophic and species level interactions, food resources, dispersal and population size of insects. In the present study, we collected terrestrial arthropods from eleven sites around Barataria Bay, five sites were oiled and five sites were unoiled, to determine the impact of the redistribution of oil from the Deepwater Horizon oil spill. Site C6 was excluded from the oiled and unoiled data because it was in close …


Talking About Statistical Significance In Numeracy, Nathan D. Grawe, Gizem Karaali Jul 2022

Talking About Statistical Significance In Numeracy, Nathan D. Grawe, Gizem Karaali

Numeracy

In recent years, much debate has surrounded the potential for audiences to be mislead by several common practices when reporting statistical significance tests. Two editors of Numeracy share the journals perspectives on these questions. As an interdisciplinary journal, we recognize and honor the genre differences represented by our authors and audience members. As a consequence, the journal is open to many practices. Still, we acknowledge the concerns raised by the American Statistical Association and others and encourage authors to write with care and clarity, however results may be represented.


Heterogeneity Of Gene Trees, Jonathan Nenye Odumegwu Unm Jul 2022

Heterogeneity Of Gene Trees, Jonathan Nenye Odumegwu Unm

Mathematics & Statistics ETDs

Multilocus phylogenetic studies often show a high degree of gene tree heterogeneity —gene trees that have different topologies from each other as well as from the species tree topology. In some cases, this can lead to studies with hundreds of loci having distinct gene tree topologies. The degree of heterogeneity is expected to increase when there is a high degree of incomplete lineage sorting due to short branches (as measured in coalescent units) in the species tree. Other potential sources of heterogeneity include other biological processes such as introgression, recombination within genes, ancestral population structure, gene duplication and loss, and …


Reply To Response By Fbi Laboratory Filed In Illinois V. Winfield And Affidavit By Biederman Et Al. (2022) Filed In Us V. Kaevon Sutton (2018 Cf1 009709), Susan Vanderplas, Kori Khan, Heike Hofmann, Alicia Carriquiry Jul 2022

Reply To Response By Fbi Laboratory Filed In Illinois V. Winfield And Affidavit By Biederman Et Al. (2022) Filed In Us V. Kaevon Sutton (2018 Cf1 009709), Susan Vanderplas, Kori Khan, Heike Hofmann, Alicia Carriquiry

Department of Statistics: Faculty Publications

1 Preliminaries

1.1 Scope

The aim of this document is to respond to issues raised in Federal Bureau of Investigation1 and Alex Biedermann, Bruce Budowle & Christophe Champod.2

1.2 Conflict of Interest

We are statisticians employed at public institutions of higher education (Iowa State University and University of Nebraska, Lincoln) and have not been paid for our time or expertise when preparing either this response or the original affidavit.3 We provide this information as a public service and as scientists and researchers in this area.

1.3 Organization

The rest of the document precedes as follows: we begin …


Derivation And Analysis Of A Discrete Predator–Prey Model, Sabrina H. Streipert, Gail S.K. Wolkowicz, Martin Bohner Jul 2022

Derivation And Analysis Of A Discrete Predator–Prey Model, Sabrina H. Streipert, Gail S.K. Wolkowicz, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

We derive a discrete predator–prey model from first principles, assuming that the prey population grows to carrying capacity in the absence of predators and that the predator population requires prey in order to grow. The proposed derivation method exploits a technique known from economics that describes the relationship between continuous and discrete compounding of bonds. We extend standard phase plane analysis by introducing the next iterate root-curve associated with the nontrivial prey nullcline. Using this curve in combination with the nullclines and direction field, we show that the prey-only equilibrium is globally asymptotic stability if the prey consumption-energy rate of …


The Prevalence And Impact Of Adolescent Hospitalization To Adult Psychiatric Units., Samantha Mcrae, Jordan Edwards, Kathy N Speechley, Javeed Sukhera, Guangyong Zou, Kelly K. Anderson Jul 2022

The Prevalence And Impact Of Adolescent Hospitalization To Adult Psychiatric Units., Samantha Mcrae, Jordan Edwards, Kathy N Speechley, Javeed Sukhera, Guangyong Zou, Kelly K. Anderson

Epidemiology and Biostatistics Publications

BACKGROUND: With increasing psychiatric hospitalizations among adolescents and constrained hospital resources, there are times when youth are hospitalized in adult inpatient psychiatry units. Evidence on the prevalence of this practice and associated impacts is lacking.

AIMS: We sought to explore the prevalence, determinants, and outcomes related to the hospitalization of adolescents aged 12-17 years on adult inpatient psychiatry units in Ontario.

METHODS: Using health administrative data, we constructed a cohort of adolescents with an inpatient psychiatric admission in Ontario (2007-2011). We classified adolescents as having an admission to an adult psychiatry unit or to other inpatient units. Multivariable regression models …


Modified Em Algorithm In Smcure Package Based On Proportional Hazards Mixture Cure Model With Offset Terms, Jiaying Yi Jul 2022

Modified Em Algorithm In Smcure Package Based On Proportional Hazards Mixture Cure Model With Offset Terms, Jiaying Yi

Theses and Dissertations

Mixture cure model is a useful method of survival analysis for population including cured proportion and uncured proportion. The R package SMCURE applies EM algorithm to estimate the coefficients of covariates in the mixture cure model. Although an offset term is specified in the SMCURE statement, the offset term is not appropriately handled in the algorithm. This thesis aims to adjust the EM algorithm for the proportional hazards mixture cure model in the SMCURE package. In addition, the offset term can be specified separately in the incidence part or the latency part. The numerical experiments include simulation study and real …


Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang Jul 2022

Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …


Statistical Methods For Analyzing Dependence Structures With Applications In Single-Cell Experiments, Zhen Yang Jul 2022

Statistical Methods For Analyzing Dependence Structures With Applications In Single-Cell Experiments, Zhen Yang

Theses and Dissertations

This dissertation focuses on studying methods in dependence structure analysis. In particular, it consists of two topics: (1) modeling dynamic correlation in zero-inflated bivariate count data; and (2) gene co-expression latent factor analysis for cell-type clustering.

In Chapter 2, a zero-inflated negative binomial model for analyzing the dynamic correlation in zero-inflated bivariate count data is proposed. Interactions between biological molecules in a cell are tightly coordinated and often highly dynamic. As a result of these varying signaling activities, changes in gene co-expression patterns could often be observed. The advancements in next-generation sequencing tech-nologies bring new statistical challenges for studying these …


Quality And Transparency, Christopher J. Smiley Dds Jul 2022

Quality And Transparency, Christopher J. Smiley Dds

The Journal of the Michigan Dental Association

In a recent JDR Clinical & Translational Research report, the American Dental Association's clinical practice guidelines (CPGs) were determined to offer high-quality guidance for the dental profession. The study employed the AGREE II tool to validate the ADA's guidelines’ methodological rigor and transparency, ensuring their quality. This external review is promising for the profession, as it indicates that the ADA has developed reliable CPGs that support advocacy and implementation. However, the article raises questions about consumer-targeted quality scores for dentist providers, such as DentaQual by P&R Dental Strategies LLC. It suggests that for such scoring systems to be credible, they …


Complex Functional Joint Models For Longitudinal Electronic Health Record, Siyuan Guo Jul 2022

Complex Functional Joint Models For Longitudinal Electronic Health Record, Siyuan Guo

Theses and Dissertations

Longitudinal measurements are important components in electronic health record (EHR) data. In practice, using longitudinal EHR history is expected to improve the estimation or prediction performance when studying some outcomes of interest, such as binary outcome or time to event outcome. However, the longitudinal observations in EHR data is complex due to irregular and sparse EHR visits. Therefore, modelling longitudinal data and further incorporating them with different types of outcomes is challenge. In this dissertation, we aim to develop methodology to first, describe the pattern of the longitudinal predictors with continuous or binary observations, and second, model the longitudinal predictors …


Statistical Methods For Analyzing Multi-Omics Data: Dependence Structure And Missing Values, Wenda Zhang Jul 2022

Statistical Methods For Analyzing Multi-Omics Data: Dependence Structure And Missing Values, Wenda Zhang

Theses and Dissertations

The advancements in high-throughput technologies have made it possible to generate a huge number of "omics'' data, including genomics, proteomics, transcriptomics, epigenomics, metabolomics, and microbiomics. Combining multiple data sources and performing joint analyses with all available information and the phenotypic outcome can reflect various aspects in complex biological systems, such as revealing regulation processes, discovering novel associations between biological entities, and identifying relevant biomarkers for certain diseases or phenotypic outcomes. This dissertation focuses on developing statistical models for analyzing multi-omics data. It is comprised of three topics: (1) integrative analysis for multi-omics data with missing observations in intermediate variables; (2) …


Genomic Prediction Accuracy Of Stripe Rust In Six Spring Wheat Populations By Modeling Genotype By Environment Interaction, Kassa Semagn, Muhammad Iqbal, Diego Jarquin, Harpinder Randhawa, Reem Aboukhaddour, Reka Howard, Izabela Ciechanowska, Momna Farzand, Raman Dhariwal, Colin W. Hiebert, Amidou N’Diaye, Curtis Pozniak, Dean Spaner Jun 2022

Genomic Prediction Accuracy Of Stripe Rust In Six Spring Wheat Populations By Modeling Genotype By Environment Interaction, Kassa Semagn, Muhammad Iqbal, Diego Jarquin, Harpinder Randhawa, Reem Aboukhaddour, Reka Howard, Izabela Ciechanowska, Momna Farzand, Raman Dhariwal, Colin W. Hiebert, Amidou N’Diaye, Curtis Pozniak, Dean Spaner

Department of Statistics: Faculty Publications

Some previous studies have assessed the predictive ability of genome-wide selection on stripe (yellow) rust resistance in wheat, but the effect of genotype by environment interaction (GEI) in prediction accuracies has not been well studied in diverse genetic backgrounds. Here, we compared the predictive ability of a model based on phenotypic data only (M1), the main effect of phenotype and molecular markers (M2), and a model that incorporated GEI (M3) using three cross-validations (CV1, CV2, and CV0) scenarios of interest to breeders in six spring wheat populations. Each population was evaluated at three to eight field nurseries and genotyped with …


Numerical Solutions To The Robin Inverse Problem With Nonnegativity Constraints, Weifu Fang, Fu-Rong Lin Jun 2022

Numerical Solutions To The Robin Inverse Problem With Nonnegativity Constraints, Weifu Fang, Fu-Rong Lin

Mathematics and Statistics Faculty Publications

We present iterative numerical methods for solving the inverse problem of recovering the nonnegative Robin coefficient from partial boundary measurement of the solution to the Laplace equation. Based on the boundary integral equation formulation of the problem, nonnegativity constraints in the form of a penalty term are incorporated conveniently into least-squares iteration schemes for solving the inverse problem. Numerical implementation and examples are presented to illustrate the effectiveness of this strategy in improving recovery results.


Statistical Extensions Of Multi-Task Learning With Semiparametric Methods And Task Diagnostics, Nikolay Miller Jun 2022

Statistical Extensions Of Multi-Task Learning With Semiparametric Methods And Task Diagnostics, Nikolay Miller

Mathematics & Statistics ETDs

In this dissertation, I propose new approaches to multi-task learning, inspired by statistical model diagnostics and semiparametric and additive modeling. The newly designed additive multi-task model framework allows for flexible estimation of multi-task parametric and nonparametric effects by using an extension of the backfitting algorithm. Further, I propose new methods for statistical task diagnostics, which allow for the identification and remedy of outlier tasks, based on task-specific performance metrics and their empirical distributions. I perform a deep examination of the well-established multi-task kernel method and achieve theoretical and experimental contributions. Lastly, I propose a two-step modeling approach to multi-task modeling, …


Applications Of Machine Learning Algorithms In Materials Science And Bioinformatics, Mohammed Quazi Jun 2022

Applications Of Machine Learning Algorithms In Materials Science And Bioinformatics, Mohammed Quazi

Mathematics & Statistics ETDs

The piezoelectric response has been a measure of interest in density functional theory (DFT) for micro-electromechanical systems (MEMS) since the inception of MEMS technology. Piezoelectric-based MEMS devices find wide applications in automobiles, mobile phones, healthcare devices, and silicon chips for computers, to name a few. Piezoelectric properties of doped aluminum nitride (AlN) have been under investigation in materials science for piezoelectric thin films because of its wide range of device applicability. In this research using rigorous DFT calculations, high throughput ab-initio simulations for 23 AlN alloys are generated.

This research is the first to report strong enhancements of piezoelectric properties …


Association Between The Dietary Inflammatory Index And Gastric Disease Risk: Findings From A Korean Population-Based Cohort Study, Sundara Raj Sreeja, Trong-Dat Le, Bang Wool Eom, Seung Hyun Oh, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert Scd, Mi Kyung Kim Jun 2022

Association Between The Dietary Inflammatory Index And Gastric Disease Risk: Findings From A Korean Population-Based Cohort Study, Sundara Raj Sreeja, Trong-Dat Le, Bang Wool Eom, Seung Hyun Oh, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert Scd, Mi Kyung Kim

Faculty Publications

Evidence suggests that diets with high pro-inflammatory potential may play a substantial role in the origin of gastric inflammation. This study aimed to examine the association between the energy-adjusted dietary inflammatory index (E-DIITM) and gastric diseases at baseline and after a mean follow-up of 7.4 years in a Korean population. A total of 144,196 participants from the Korean Genome and Epidemiology Study_Health Examination (KoGES_HEXA) cohort were included. E-DII scores were computed using a validated semi-quantitative food frequency questionnaire. Multivariate logistic regression and Cox proportional hazards regression were used to assess the association between the E-DII and gastric disease risk. In …


Data-Driven Analytical Predictive Modeling For Pancreatic Cancer, Financial & Social Systems, Aditya Chakraborty Jun 2022

Data-Driven Analytical Predictive Modeling For Pancreatic Cancer, Financial & Social Systems, Aditya Chakraborty

USF Tampa Graduate Theses and Dissertations

Pancreatic cancer is one of the most deathly disease and becoming an increasingly commoncause of cancer mortality. It continues giving rise to massive challenges to clinicians and cancer researchers. The combined five-year survival rate for pancreatic cancer is extremely low, about 5 to 10 percent, owing to the fact that a large number of the patients are diagnosed at stage IV when the disease has metastasized. Our study investigates if there exists any statistical significant difference between the median survival times and also the survival probabilities of male and female pancreatic cancer patients at different cancer stages, and irrespective of …


Adolescent Health Risk Behaviors, Adverse Experiences, And Self-Reported Hunger: Analysis Of 10 States From The 2019 Youth Risk Behavior Surveys, Kathryn L. Krupsky, Sarah Silwa, Hilary Seligman, Andrea D. Brown, Angela D. Liese Ph.D., Zewditu Demissie, Ellen Barnidge Jun 2022

Adolescent Health Risk Behaviors, Adverse Experiences, And Self-Reported Hunger: Analysis Of 10 States From The 2019 Youth Risk Behavior Surveys, Kathryn L. Krupsky, Sarah Silwa, Hilary Seligman, Andrea D. Brown, Angela D. Liese Ph.D., Zewditu Demissie, Ellen Barnidge

Faculty Publications

We examined associations between adolescent self-reported hunger, health risk behaviors, and adverse experiences during the 2018–2019 school year. Youth Risk Behavior Survey data were pooled from 10 states. Prevalence ratios were calculated, and we assessed effect measure modification by sex. The prevalence of self-reported hunger was 13%. Self-reported hunger was associated with a higher prevalence of every health risk behavior/adverse experience analyzed, even after adjusting for sex, grade, and race/ethnicity. Sex did not modify associations. Findings underscore needs for longitudinal research with more robust measures of adolescent food insecurity to clarify the temporality of relationships.


Nonparametric Estimation Of Transition Probabilities In Illness-Death Model Based On Ranked Set Sampling, Ying Ma Jun 2022

Nonparametric Estimation Of Transition Probabilities In Illness-Death Model Based On Ranked Set Sampling, Ying Ma

USF Tampa Graduate Theses and Dissertations

The ranked set sampling (RSS) design is applied widely in agriculture, environmental science, and medical research where the exact measurements of sampling units is costly, but sampling units can be ranked by a correlated concomitant variable. RSS is usually a cost-efficient alternate to simple random sampling (SRS) for selecting more representative samples. This study presents a novel methodology to investigate the nonparametric estimation of transition probabilities in illness-death model using the RSS design. We study the Aalen–Johansen estimator of transition probabilities in illness-death Markov model based on RSS design under random right censoring time and propose nonparametric estimators of the …


New Developments In Statistical Optimal Designs For Physical And Computer Experiments, Damola M. Akinlana Jun 2022

New Developments In Statistical Optimal Designs For Physical And Computer Experiments, Damola M. Akinlana

USF Tampa Graduate Theses and Dissertations

Statistical design of experiments allows for multiple factors influencing a process to be systematically manipulated in an experiment, and their effects on the output of the process to be studied via statistical modeling and analysis. Classical designs offer general nice performance but have limited applications due to restricted design size, region, and randomization structure. Computer generated optimal designs become more popular in recent decades due to the rapid growth in computing power. Most existing work in optimal design of experiments involves designing experiments with optimal performance on a single chosen objective or a single response. However, with the increasing limitation …


Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill Jun 2022

Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill

Faculty Publications

Purpose — This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict. Design/methodology/approach — In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction. Findings — In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict. Research limitations/implications — The study is based on actual historical data and is purely data driven. …


Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman Jun 2022

Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman

Faculty Publications

Purpose — Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.
Design/methodology/approach — This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the …


Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman Jun 2022

Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman

Faculty Publications

Purpose — Aircraft fail to meet mission capable rate goals due to a lack of supply of aircraft parts in inventory where the aircraft breaks. This triggers an order at the repair location. To maximize mission capable rate, the time from order to delivery needs to be minimized. The purpose of this research is to examine the case of three airfields for the order to delivery time of mission critical aircraft parts for a specific aircraft type. Design/methodology/approach — This research captured data from three information systems to assess the order fulfillment process. The data were analyzed to determine the …


Factors Associated With Covid-19 Vaccine Intentions Among South Carolina Residents, Mufaro Kanyangarara, Lauren Mcabee, Virginie G. Daguise, Melissa Nolan Ph.D., Mph Jun 2022

Factors Associated With Covid-19 Vaccine Intentions Among South Carolina Residents, Mufaro Kanyangarara, Lauren Mcabee, Virginie G. Daguise, Melissa Nolan Ph.D., Mph

Faculty Publications

Despite evidence of vaccine safety and efficacy, vaccine hesitancy remains a major global health threat. The COVID-19 vaccine has presented unique vaccine hesitancy concerns compared to parental vaccine hesitancy towards childhood vaccines. South Carolina (SC) is home to a largely conservative population and historically has some of the lowest vaccination coverage rates in the United States of America. The goal of the current study was to identify factors associated with COVID-19 vaccine intentions among SC residents. From November 2020 to September 2021, 300,000 invitations to participate in community testing and complete an online survey were mailed to randomly selected SC …


The Short-Term Effects Of Fine Airborne Particulate Matter And Climate On Covid-19 Disease Dynamics, El Hussain Shamsa, Kezhong Zhang Jun 2022

The Short-Term Effects Of Fine Airborne Particulate Matter And Climate On Covid-19 Disease Dynamics, El Hussain Shamsa, Kezhong Zhang

Medical Student Research Symposium

Background: Despite more than 60% of the United States population being fully vaccinated, COVID-19 cases continue to spike in a temporal pattern. These patterns in COVID-19 incidence and mortality may be linked to short-term changes in environmental factors.

Methods: Nationwide, county-wise measurements for COVID-19 cases and deaths, fine-airborne particulate matter (PM2.5), and maximum temperature were obtained from March 20, 2020 to March 20, 2021. Multivariate Linear Regression was used to analyze the association between environmental factors and COVID-19 incidence and mortality rates in each season. Negative Binomial Regression was used to analyze daily fluctuations of COVID-19 cases …


Video Anomaly Detection: Practical Challenges For Learning Algorithms, Keval Doshi Jun 2022

Video Anomaly Detection: Practical Challenges For Learning Algorithms, Keval Doshi

USF Tampa Graduate Theses and Dissertations

Anomaly detection in surveillance videos is attracting an increasing amount of attention. Despite the competitive performance of several existing methods, they lack theoretical performance analysis, particularly due to the complex deep neural network architectures used in decision making. Additionally, real-time decision making is an important but mostly neglected factor in this domain. Much of the existing methods that claim to be online, depend on batch or offline processing in practice. Furthermore, several critical tasks such as continual learning, model interpretability and cross-domain adaptability are completely neglected in existing works. Motivated by these research gaps, in this dissertation we discuss our …