Physical Sciences and Mathematics Commons^™

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

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

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 …

A Bayesian Programming Approach To Car-Following Model Calibration And Validation Using Limited Data, Franklin Abodo

FIU Electronic Theses and Dissertations

Traffic simulation software is used by transportation researchers and engineers to design and evaluate changes to roadway networks. Underlying these simulators are mathematical models of microscopic driver behavior from which macroscopic measures of flow and congestion can be recovered. Many models are intended to apply to only a subset of possible traffic scenarios and roadway configurations, while others do not have any explicit constraint on their applicability. Work zones on highways are one scenario for which no model invented to date has been shown to accurately reproduce realistic driving behavior. This makes it difficult to optimize for safety and other …

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 …

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.

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 …

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 …

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

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 …

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 (PM_2.5), 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

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 …

Adjusting Community Survey Data Benchmarks For External Factors, Allen Miller, Nicole M. Norelli, Robert Slater, Mingyang N. Yu

SMU Data Science Review

Abstract. Using U.S. resident survey data from the National Community Survey in combination with public data from the U.S. Census and additional sources, a Voting Regressor Model was developed to establish fair benchmark values for city performance. These benchmarks were adjusted for characteristics the city cannot easily influence that contribute to confidence in local government, such as population size, demographics, and income. This adjustment allows for a more meaningful comparison and interpretation of survey results among individual cities. Methods explored for the benchmark adjustment included cluster analysis, anomaly detection, and a variety of regression techniques, including random forest, ridge, decision …

Sparse Spectral-Tau Method For The Two-Dimensional Helmholtz Problem Posed On A Rectangular Domain, Gabriella M. Dalton

Mathematics & Statistics ETDs

Within recent decades, spectral methods have become an important technique in numerical computing for solving partial differential equations. This is due to their superior accuracy when compared to finite difference and finite element methods. For such spectral approximations, the convergence rate is solely dependent on the smoothness of the solution yielding the potential to achieve spectral accuracy. We present an iterative approach for solving the two-dimensional Helmholtz problem posed on a rectangular domain subject to Dirichlet boundary conditions that is well-conditioned, low in memory, and of sub-quadratic complexity. The proposed approach spectrally approximates the partial differential equation by means of …

Investigation Of The Association Of Exposures To Fire-Related Hazards With Pulmonary Function Of Firefighters, David G. Goldfarb

Dissertations and Theses

Background. Firefighters are habitually exposed to hazardous toxicants which place them at an elevated risk for numerous adverse health outcomes. An example of this is the associations observed in other works between inhalation of combustion byproducts from urban structural fires and both acute and chronic pulmonary dysfunction. To-date, the characterization of firefighters’ exposures to dangerous chemicals in smoke from non-wildfire incidents, both directly through personal monitoring and indirectly from work-related records is scarce. Prior works investigating the association between routine firefighting and pulmonary function have relied on crude metrics such as years of service and numbers of responses to …

A Bayesian Latent Scale Model For Multivariate Longitudinal Data, Kruti Pandya

Dissertations and Theses

In order to understand the entire course of slow progressing diseases like Alzheimer's dementia or multiple sclerosis, it is essential to characterize long term disease dynamics from a healthy stage to a late disease stage. Cohort studies typically recruit subjects at different stages of the disease and then follow them for a relatively short period of time. In this dissertation, we propose a novel Bayesian nonlinear mixed effects model with latent time scale to characterize long term disease dynamics using the observed short term longitudinal data from cohort studies without relying on clinical diagnosis. This model can accommodate noisy longitudinal …

(R1881) Impatient Customers In Queueing System With Optional Vacation Policies And Power Saving Mode, Poonam Gupta, Rajni Gupta, Sangeeta Malik

Applications and Applied Mathematics: An International Journal (AAM)

In this manuscript, a queueing system with two optional vacation policies, power-saving mode under reneging and retention of reneged customers in both vacations is analyzed. If the server is free, it chooses either of the vacations, classical vacation or working vacation. During vacations, the customers may get impatient due to delays and may leave the system, but they are retained in the system with some convincing mechanisms. On vacation completion, if the system is empty, the server is turned off to facilitate better utilization of the resources. Some of the operating system characteristics are derived using the probability generating functions …

Nonoscillatory Solutions Of Higher-Order Fractional Differential Equations, Martin Bohner, Said R. Grace, Irena Jadlovská, Nurten Kılıç

Mathematics and Statistics Faculty Research & Creative Works

This paper deals with the asymptotic behavior of the nonoscillatory solutions of a certain forced fractional differential equations with positive and negative terms, involving the Caputo fractional derivative. The results obtained are new and generalize some known results appearing in the literature. Two examples are also provided to illustrate the results.

Analysis Of Ibnr Liabilities With Interevent Times Depending On Claim Counts, Daniel J. Geiger, Akim Adekpedjou

Mathematics and Statistics Faculty Research & Creative Works

We extend a recently proposed stochastic loss reserving model for liabilities from incurred but not reported (IBNR) micro-level claims. We propose viewing the number of claims from an event as a measure of catastrophic severity. This view covers catastrophes with arbitrarily many classes of magnitude. Our Markovian model allows the time between disasters to depend on the previous event's level of severity. Simultaneously, we let the discount rate vary in the same manner. First, we find the moments of IBNR liabilities in our model. Then, we permit a later time horizon for IBNR claims when considered jointly with incurred and …

(R1510) A Special Case Of Rodriguez-Lallena And Ubeda-Flores Copula Based On Ruschendorf Method, Marvin G. Pizon, Rolando N. Paluga

Applications and Applied Mathematics: An International Journal (AAM)

Measure of dependence is a particular way of looking at the association between random variables, and one way to capture stochastic dependence is through the use of copula. In this study, a Rushendorf Method was applied to a bivariate function to obtain a copula through the use of a special case of Rodriguez-Lallena and Ubeda-Flores (RLUF) copula. Properties of the RLUF copula such as the density, measures of dependence, and lower and upper tail dependence were studied. In particular, measures of dependence such as Spearman’s rho, Kendall’s tau and Blomqvist’s beta of RLUF copula are given. Moreover, the Root-Mean-Square Error …

A Global Ecological Signal Of Extinction Risk In Terrestrial Vertebrates, M. J. Munstermann, N. A. Heim, D. J. Mccauley, J. L. Payne, N. S. Upham, Steve C. Wang

Mathematics & Statistics Faculty Works

To determine the distribution and causes of extinction threat across functional groups of terrestrial vertebrates, we assembled an ecological trait data set for 18,016 species of terrestrial vertebrates and utilized phylogenetic comparative methods to test which categories of habitat association, mode of locomotion, and feeding mode best predicted extinction risk. We also examined the individual categories of the International Union for Conservation of Nature Red List extinction drivers (e.g., agriculture and logging) threatening each species and determined the greatest threats for each of the four terrestrial vertebrate groups. We then quantified the sum of extinction drivers threatening each species to …

(R1503) Numerical Ultimate Survival Probabilities In An Insurance Portfolio Compounded By Risky Investments, Juma Kasozi

Applications and Applied Mathematics: An International Journal (AAM)

Probability of ultimate survival is one of the central problems in insurance because it is a management tool that may be used to check on the solvency levels of the insurer. In this article, we numerically compute this probability for an insurer whose portfolio is compounded by investments arising from a risky asset. The uncertainty in the celebrated Cramér-Lundberg model is provided by a standard Brownian motion that is independent of the standard Brownian motion in the model for the risky asset. We apply an order four Block-by-block method in conjunction with the Simpson rule to solve the resulting Volterra …

Joint Control Of Manufacturing And Onsite Microgrid System Via Novel Neural-Network Integrated Reinforcement Learning Algorithms, Jiaojiao Yang, Zeyi Sun, Wenqing Hu, Louis Steinmeister

Mathematics and Statistics Faculty Research & Creative Works

Microgrid is a promising technology of distributed energy supply system, which consists of storage devices, generation capacities including renewable sources, and controllable loads. It has been widely investigated and applied for residential and commercial end-use customers as well as critical facilities. In this paper, we propose a joint state-based dynamic control model on microgrids and manufacturing systems where optimal controls for both sides are implemented to coordinate the energy demand and supply so that the overall production cost can be minimized considering the constraint of production target. Markov Decision Process (MDP) is used to formulate the decision-making procedure. The main …

Bootstrapped Fractional Designs Applied To Models With Both Mixture And Process Variables, Laura Vinton

Honors Theses

Mixture variables are unique as the components must sum to 1, causing problems when there is interaction between mixture and process variables. The best model is the fully linearized model, but this can get large quickly. We began by comparing models on multiple data sets. These models include linear and nonlinear models. After seeing that nonlinear models appear to be the best alternatives, we used the systematically selected fractions of each data set in order to obtain an in and out of sample RMSE. This allows us to see if there is evidence of overfitting, how well the model predicts …

Mixture Of Functional Graphical Models, Qihai Liu

Dissertations

With the development of data collection technologies that use powerful monitoring devices and computational tools, many scientific fields are now obtaining more detailed and more complicatedly structured data, e.g., functional data. This leads to increasing challenges of extracting information from the large complex data. Making use of these data to gain insight into complex phenomena requires characterizing the relationships among a large number of functional variables. Functional data analysis (FDA) is a rapidly developing area of statistics for data which can be naturally viewed as a smooth curve or function. It is a method that changes the frame of data …

Air Pollutant Levels And Asthma Emergency Room Visits In A Highly Populous Us Urban County During 2018-19, Osaremhen Ikhile, Jingjing Yin, Atin Adhikari

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Objective: Air pollutants are linked to asthma exacerbation. The study purpose was to demonstrate an association between air pollutants levels and asthma emergency room (ER) visit trends in a highly populated US urban county in Georgia during 2018-2019.

Methods: Time series analyses were conducted for the variations in daily numbers of children and adult asthma emergency room visits and changes in daily mean PM_2.5, daily mean PM₁₀ concentrations, daily max 1-hour SO₂ concentrations, daily max 1-hour NO₂ concentrations, daily max 8-hour ozone concentrations, and airborne pollen loads for 2018 to 2019 and potential trends were …

Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low

Theses and Dissertations

The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …

Data-Driven Analysis Of Drug And Substance Abuse Rates Across The Varying Regions In The United States Of America, Reem Saleh

University Honors Theses

Drugs and substance abuse is one of the leading causes of death for adolescents in the United States. The consequences of using these drugs are profound and can cause both damage to one's physical and psychological health. The rates of drug abuse in the United States continue to increase over the years. This paper analyzes the trends in rates of drug abuse in the four regions in the United States. It looks at the rates in cocaine, cigarettes, marijuana, and tobacco. A preliminary analysis was done to look at the trend in rates followed by an ARIMA time series model …

Unrestricted Factor Analysis: A Powerful Alternative To Confirmatory Factor Analysis, Jan-Benedict E.M. Steenkamp, Alberto Maydeu-Olivares

Faculty Publications

The gold standard for modeling multiple indicator measurement data is confirmatory factor analysis (CFA), which has many statistical advantages over traditional exploratory factor analysis (EFA). In most CFA applications, items are assumed to be pure indicators of the construct they intend to measure. However, despite our best efforts, this is often not the case. Cross-loadings incorrectly set to zero can only be expressed through the correlations between the factors, leading to biased factor correlations and to biased structural (regression) parameter estimates. This article introduces a third approach, which has emerged in the psychometric literature, viz., unrestricted factor analysis (UFA). UFA …

Statistical Modeling Of Longitudinal Medical Cost Data, Shikun Wang

Dissertations & Theses (Open Access)

Projecting the future cancer care cost is critical in health economics research and policy making. An indispensable step is to estimate cost trajectories from an incident cohort of cancer patients using longitudinal medical cost data, accounting for terminal events such as death, and right censoring due to loss of follow-up. Since the cost of cancer care and survival are correlated, a scientifically meaningful quantity for inference in this context is the mean cost trajectory conditional on survival. Many standard approaches for longitudinal and survival analysis are not valid for the problem. The research for my Ph.D. dissertation consists of three …