Digital Commons Network^™

Bridging The Gap Between Career Expectations Versus Labor Market Realities, Reinette P. Madrid, Grethel T. Ledesma, Ignatius Aryono Putranto, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Most students lack awareness regarding the labor market outcomes for their chosen college majors. This study aims to answer what factors affect the career expectations of graduating students at Quezon City University and how these expectations align with the prevailing labor market situation. It employed descriptive, causal, and explanatory research using a sample of 108 respondents from fourth-year information technology students for the school year 2021 to 2022. Eight of the nine null hypotheses were rejected by employing multinomial logistic and linear regression. Student fixed effects and other labor market outcomes significantly predicted salary, estimated stability, and estimated skills in …

Time Series Mediation Analysis With Non-Linear And Machine Learning Methods, Timothy Marsh

Theses and Dissertations (Comprehensive)

Non-linearity in mediation analysis has been primarily studied in the context of binary variables which encode a treatment and control, estimating a `direct` and `indirect` effect of a covariate (a.k.a. treatment) X on a response Y, with a third variable M (the `mediator`) that is affected by X and in turn affects Y. The focus of mediation analysis in general is to quantify the overall effect of X on Y, including the effect through M. This presentation will focus on one or more continuous treatments and apply non-linear methods, including splines and machine learning models, to mediation analysis in a …

Robust Statistical Methods For Microbiome Abundance Data, Yiming Shi

WUSM Theses and Dissertations – All Programs

Differential abundance analysis in microbiome studies aims to identify taxa whose abundance differs across biological or clinical conditions. The observed data are typically taxon-specific sequencing read counts, representing reads assigned to different taxa within each sample. These counts are indirect measurements of the underlying microbial abundance profile and are constrained by sample-specific library sizes. Microbiome count data are also typically sparse, overdispersed, and heteroscedastic. Together, these characteristics create substantial challenges for differential abundance analysis and make the results highly sensitive to normalization procedures, model specification, and the statistical methods used for inference.

Normalization defines the scale on which samples are …

Revisiting Ulam Stability For Boundary Value Problems, Martin Bohner, Snezhana Hristova, Agnieszka B. Malinowska, Ewa Girejko

Mathematics and Statistics Faculty Research & Creative Works

The main goal of this paper is to apply Ulam stability theory to boundary value problems for dynamic equations, while addressing several common misconceptions found in the existing literature. We identify the key issues that arise when applying Ulam stability to such problems and propose three distinct approaches to overcome them. To enhance clarity and accessibility, we begin with nonlinear ordinary differential equations and subsequently extend the analysis to nonlinear dynamic equations on time scales. Since a time scale is defined as any nonempty closed subset of the real numbers, our results are applicable to dynamic equations on continuous, discrete, …

Mapping St. Louis History: Slavery, Redlining, And The May 16th Tornado, Safa M. Altamimi, Aster Horbanova, Riley J. Bearden, Vivian B. Rhodes, Bridget Ragan

Undergraduate Research Symposium

For this project, our group members are traveling across St.Louis to areas that are affected by the May 16th tornado. We will be taking pictures and using ArcGIS survey123 to input data connecting the tornado to historical forces such as Redlining and Slavery. Using this data, we will be creating an ArcGIS StoryMap and presenting our findings.

Mathematical Modelling For Optimizing Predator–Prey Networks In A Resilient Wildlife Ecosystem: A Systematic Literature Review, Thadei Damas Sagamiko

Tanzania Journal of Science

The resilience of wildlife networks hinges on the adaptability and stability of complex predator-prey interactions. Mathematical modelling offers a crucial approach for examining and optimizing these dynamics under biological invasions and environmental pressures. This systematic literature review (SLR) employs a bibliometric analysis approach to synthesize global research on mathematical models applied to predator-prey network optimization, with an emphasis on their ecological implications, computational approaches, and modelling strategies. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 50 peer- reviewed studies (2000–2025) were analyzed using the Scopus and Google Scholar databases. The study identifies classical models, such as the …

Clustering Of Potable Water Sources In Rural Oyo State, Nigeria: Implications For Equitable Distribution And Sustainability, Adesola Adediran, Ibrahim O. Raufu

Tanzania Journal of Science

Adequate and equitable access to potable water remains a major challenge in rural communities of Oyo State, Nigeria, with uncoordinated provision leading to widespread shortages. This study employs geospatial techniques to assess the spatial distribution of water supply sources across five purposively selected rural communities in Olorunsogo Local Government Area (OLGA). Geographic coordinates of boreholes, hand-dug wells, and other potable water sources were collected using a handheld Garmin GPS 76S device. Spatial analysis was conducted using ArcGIS, and Nearest Neighbour Analysis (NNA) was applied to evaluate the pattern of distribution. Results indicate a strong tendency toward clustering, with a Nearest …

When Three Points Aren't Enough: Parameter Estimation In Newton's Law Of Cooling, Alberto A. Condori, Cara D. Brooks, Madeline R. Goldberg

CODEE Journal

We begin with a paradoxical three-point problem where the standard parameter estimation formula fails because temperature data must satisfy a concavity condition reflecting Newton's Law of Cooling's exponential structure. Although a closed-form solution for A exists for equally-spaced measurements, high sensitivity to error motivates the use of overdetermined systems with many measurements. The "profiling over A" technique transforms this three-parameter nonlinear problem into a sequence of simple linear regressions, providing computational efficiency and conceptual transparency. This approach can be generalized to many parameter estimation problems in science and engineering, making it a valuable tool for undergraduates interested in applied mathematics. …

Analysis Of The Influence Of Anthropometric Dimensions Of Postural Ergonomics Using Multiple Linear Regression, Gashbeen Faisal Najmaddin, Edrees Muhammed Tahir Harki

Al-Bahir

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary …

The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban

Faculty Publications

Nondestructive evaluation (NDE) methods are powerful tools for detecting and characterizing flaws in structural components, but their reliability must be evaluated before they can be used in critical applications. For more than 50 years, probabilistic and statistical methods have been used effectively to estimate reliability by describing an NDE system’s Probability of Detection (POD) for flaws of realistic sizes. The POD methods used by the USAF and NASA, like Hit/Miss, Signal-Response (â vs. a), and Point Estimate method (PEM, a.k.a. 29/29) have evolved, alongside newer approaches like Limited Sample POD (LS-POD) method, and Model Assisted Probability of Detection …

Mapping The Water Quality Of Jamaica Bay, New York (1996-2024): Principal Component Analysis And K-Means Clustering, Sneha Srivastava

Dissertations, Theses, and Capstone Projects

Jamaica Bay, located along the southeastern coast of New York City, acts as a biodiverse estuary of wetlands, meadows, and salt marsh islands. The purpose of this study is to analyze the water quality conditions of the region over time, comparing locations around the bay to identify hyperlocal features that influence larger trends in the hydrological system. Ten variables were used as water quality indicators, including total Kjeldahl nitrogen, salinity, pH, Secchi disk depth, and total phosphorus, among others, across five stations in the bay, between 1994 and 2024. After data cleaning and standardization methods were applied, principal component analysis …

Rethinking Road Racing Standards: Comparing New York Road Runners Race Results To Running Industry Standards, Jennie Coughlin

Dissertations, Theses, and Capstone Projects

Running has undergone a third boom in participation since 2020, driven largely by people seeking fitness options that were outside and socially distanced during the COVID-19 pandemic. Social media has also allowed runners from groups that did not traditionally participate to find community. As the road racing population has expanded to include more people, some road racing industry standards have not kept up. This project assesses what the road racing community looks like and measures industry standards against the community of participants to see what changes in those standards would be needed to make them inclusive for all participants.

To …

Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Parkinson's disease (PD) is a complex neurodegenerative disorder with a significant genetic component. While genome-wide association studies (GWAS) have been instrumental in identifying genetic variants associated with PD, the reliance on large sample sizes and population-level analyses may overlook variants with lower minor allele frequencies or individual-specific relevance. Individualized Bayesian Inference (IBI) offers a promising method to complement GWAS by identifying and prioritizing candidate genetic markers at both the individual and patients-like-me subgroup levels. This study evaluates the application of IBI to PD genetics, using GWAS as a baseline for comparison. We analyzed genetic data from the Fox Insight online …

Bank Soundness Index For Indonesia: The Generalized Dynamic Principal Component Analysis Approach, Yusita Octina Budiyanti, Nasrudin Nasrudin

Bulletin of Monetary Economics and Banking

In Indonesia, the Bank Soundness Index (BSI) serves as an early warning instrument for assessing the stability of Conventional Commercial Banks (CCBs) and Islamic Commercial Banks (ICBs). This study develops the BSI employing the Generalized Dynamic Principal Component Analysis (GDPCA) methodology and incorporates the fundamental indicators from the Financial Soundness Indicators released by the IMF. The BSI for CCBs is formulated using three primary components, with the Operating Expense to Operating Income ratio assigned the greatest weight. Likewise, the BSI for ICBs is constituted by three primary components, with the Liquid Asset ratio carrying the greatest weight. The developed BSI …

Validation Of A Home-Based Tool For Preschool Children Fall Prevention: A Rasch Analysis, Devie Fitri Octaviani, Fatma Lestari, Indang Trihandini, Dadan Erwandi

Kesmas

Unintentional falls are a leading cause of injury among preschool children, primarily occurring in home environments, yet validated tools to assess household fall prevention capacity in low- and middle-income countries remain limited. This study aimed to develop and psychometrically validate the Home-Based Preschool Fall Prevention Instrument using the Rasch Measurement Model. A cross-sectional validation study was conducted in Depok City, Indonesia, involving 167 primary caregivers of preschool children enrolled in kindergartens selected through multistage cluster random sampling. The instrument was developed based on an etiological injury model, socio-ecological perspectives, and risk management principles, and comprised four main factors: child, home, …

Provincial Disparities In Adolescent Fertility In Indonesia: An Ecological Analysis Of Child Marriage, Median Age At First Marriage, And Family Development Index, Andi Nisa Fathimiyah Afidah, Milla Herdayati

Kesmas

Adolescent fertility remains a public health concern in Indonesia, with substantial variations across provinces. However, the evidence explaining provincial disparities using population-level indicators remains limited. This study aimed to examine provincial disparities in adolescent fertility and assess the association of child marriage, median age at first marriage among women, and the Family Development Index called iBangga with adolescent fertility across Indonesia. This ecological, cross-sectional study used aggregated data from 34 Indonesian provinces. Descriptive statistics, spatial visualization, Pearson’s correlation, and multiple linear regression analyses were performed. The mean adolescent fertility rate was 25.0 births per 1,000 female adolescents aged 15–19 years, …

Spatial Association Of Acute Respiratory Infection, Diarrhea, And Low Birth Weight With Stunting Prevalence In Indonesia, 2024, Dian Rosadi, Husaini Husaini, Triawanti Triawanti, Musafaah Musafaah

Kesmas

Stunting remains unevenly distributed across Indonesia, but national evidence integrating spatial analysis and spatial regression is limited. This study examined the spatial distribution of stunting and its associations with acute respiratory infection (ARI), diarrhea, and low birth weight (LBW) across Indonesian provinces. An ecological cross-sectional study used data from the 2024 Indonesian Nutritional Status Survey. Stunting-only analyses included all 38 provinces, whereas analyses involving ARI, diarrhea, and LBW included 37 provinces with complete data. Spatial analyses used a row-standardized symmetric four-nearest-neighbor spatial weights matrix and included Global Moran’s I, bivariate spatial analysis, Local Indicators of Spatial Association, ordinary least squares, …

The Association Between Rapid Growth In Children Under The Age Of Five And Adolescent Obesity, Ratu Ayu Dewi Sartika, Fadila Wirawan, Iche Andriyani Liberty, Nurul Husna Mohd Shukri, Siti Arifah Pujonarti, Edy Purwanto, Munaya Fauziah

Kesmas

Early-life nutrition is a critical predictor of long-term health, yet the association between rapid early-childhood growth and adolescent obesity, particularly in relation to the “double burden of malnutrition,” remains under-researched in Indonesia. This study aimed to analyze the association between rapid growth and adolescent obesity. Data were obtained from the 1997, 2000, and 2014 waves of the Indonesian Family Life Survey (IFLS). This study included 641 children (aged 0–23 months at baseline) with complete anthropometric measurements across all three waves. Rapid growth was defined as an increase in z-scores of >0.67 in weight-for-age (WAZ), height-for-age (HAZ), or weight-for-height (WHZ) between …

Environmental Perspective For System Dynamics Modeling Of Stunting Mitigation To Achieve The Sustainable Development Goals In West Sumatra, Indonesia, Elsa Yuniarti, Nabila Azzahra, Yulhendri Yulhendri, Heldi Heldi, Mery Delvina, Saskia Putri Azeli

Kesmas

This study developed a system dynamics model to simulate stunting reduction in West Sumatra Province, Indonesia, by integrating infant and toddler health, maternal health, and environmental determinants. Secondary data from 2020–2024 on low birth weight, immunization, malnutrition, exclusive breastfeeding, maternal chronic energy deficiency, iron and folic acid supplement distribution, sanitation, and safe drinking water access were compiled from West Sumatra Provincial Health Office and Statistics Indonesia, and validated through consultation with five stakeholder institutions. Causal Loop Diagrams mapped feedback relationships among determinants and were translated into Stock Flow Diagrams using Powersim Studio 10. The model was validated through structural verification, …

Geometric Convergence And State-Space Decompositions For Stochastic Gradient Descent Markov Chains, Philip Zaleski

Dissertations

No abstract provided.

Motor Imagery Eeg Decoding For Brain-Computer Interfaces: Structured Representation, Transfer, And Drift, Yiming Shen

Graduate Doctoral Dissertations

Motor imagery EEG decoding is often summarized by the accuracy of a final classifier, but the classifier is only the last stage of the pipeline. Before classification, the signal has already been shaped by preprocessing, feature extraction, source-session organization, and adaptation. This dissertation studies how feature representation, source-session transfer, and drift shape reliable MI-EEG decoding for brain-computer interfaces.

It first studies within-session decoding on public MI-EEG datasets using nested validation that keeps preprocessing, feature fitting, and model selection inside the training folds. This analysis separates gains from feature representation from gains due to nonlinear classification, and relates both comparisons to …

A Vision For The Future Of Academic Publishing In Sports Analytics, Ryan Elmore, B. Baumer, Brian Macdonald, Gregory J. Matthews, Michael E. Schuckers

Statistical and Data Sciences: Faculty Publications

This article introduces the Journal of Statistics and Data Science in Sports (JSDSS), a Diamond Open Access, peer-reviewed journal. The journal is founded on three core principles. First, our commitment to open access is absolute. Second, reproducibility is critical and fundamental to the journal. Third, we believe sport is a rich and underutilized laboratory for statistical and data science innovation. The aim of the Journal of Statistics and Data Science in Sports is to provide an outlet for original, rigorous, practical, state-of-the-art, reproducible, and peer-reviewed analysis of sports data as well as the data science tools (software, applications, data, etc.) …

Modeling Of Supersonic Wave And Shock Propagation Using The Lattice Boltzmann Method, Timothy P. Schroeder

Beyond: Undergraduate Research Journal

The lattice Boltzmann method (LBM) has emerged as a mesoscopic alternative to traditional Navier-Stokes solvers for modeling fluid dynamics offering advantages in computational efficiency, parallelization, and handling of complex boundaries. Despite these strengths, accurately reproducing compressible, shock-driven phenomena remains challenging. This study investigates the performance of LBM in simulating the Sod shock tube problem, a classical benchmark for compressible flow-using both single and double distribution function formulations across one- and two-dimensional lattice stencils. A MATLAB-based solver was developed to model the flow under isothermal conditions and compared to the analytical solution using the L2 norm error. The one-dimensional models achieved …

Adaptive Rational Approximation In Dynamic Economic Models: A Novel Application Of The Aaa Algorithm To Economic Growth, Adaye Sosthene Yvan N'Guettia

Mathematics, Statistics, and Computer Science Honors Projects

I study adaptive rational approximation for fixed points that arise in infinite-horizon dynamic programming. I integrate the Adaptive Antoulas–Anderson (AAA) algorithm into Bellman- and Euler-based fixed-point solvers by recomputing a barycentric rational interpolant at each update. In addition to standard AAA, which selects support points from interpolation residuals, I study a residual-weighted variant in which Bellman,Euler, or KKT diagnostics act as secondary weights on the greedy pivot rule. This alignment of approximation adaptivity with the underlying equilibrium conditions can concentrate degrees of freedom in regions of steep curvature, sharp transitions in localbehavior, and other localized features that typically degrade polynomial …

An Analysis Of The Effects And Implementations Of The Early Literacy Grant In Arizona, Alicia Severiano Perez

Mathematics, Statistics, and Computer Science Honors Projects

Over the years, states have implemented Science of Reading (SoR) frameworks to address low literacy levels. The Early Literacy Grant (ELG) in Arizona funds and supports such frameworks for schools serving low-income students. This paper is the first to explore the grant through interrupted time series modeling to evaluate effectiveness and text analysis to understand its implementation. We do not find clear evidence of positive effects caused by the grant, other than some cases, such as Yuma County. Schools typically allocate funds toward salaries and hiring instructors. These findings raise questions about whether its allocations should be closely monitored.

Level Sets For Lehmer Codes Of Pattern Avoiding Permutations, Avery Sinclair

Mathematics, Statistics, and Computer Science Honors Projects

We study the poset structures for two families of pattern avoiding permutations. An n-permutation is a list of the numbers [n]={1,2,...,n}. A permutation is 321-avoiding when it does not contain a decreasing subsequence of length 3. A poset (partially ordered set) is a set such that some elements can be compared with one another. Using Lehmer codes, we define a poset for 321-avoiding permutations. We then fully describe the six lowest levels of this poset. We then consider the analogous poset for 123-avoiding permutations (which don't contain an increasing subsequence of length 3) and fully describe the three lowest levels.

A Longitudinal Study Of Achilles Tendon Adaptation In Ncaa Division I Female Gymnasts: Associations With Menstrual Status, Birth Control Use, Pain, Limb Dominance, And Training Exposure, Mattie Jane Hyde

Electronic Theses and Dissertations

This longitudinal study evaluated Achilles tendon (AT) thickness in 22 NCAA Division I (DI) female gymnasts across three consecutive seasons in relation to menstruation, birth control use, pain, limb dominance, training week, and year of collegiate competition. Weekly ultrasound and athlete survey data were analyzed using mixed-effects models for absolute AT thickness and change in thickness from baseline measurements. Associations were primarily characterized by interactions rather than uniform effects of individual predictors. A Pain × Limb Dominance × Week × Year interaction was associated with both thickness outcomes across season-specific and combined analyses, with relationship directions varying by limb, season …

Predicting Remaining Useful Life Using Multivariate Time-Series Data, Anayah Smith, Victoria Gaibor

Discovery Day - Daytona Beach

Accurate prediction of Remaining Useful Life (RUL) is critical for enabling predictive maintenance, improving system reliability, and reducing operational costs in degrading systems. This project addresses the problem of modeling and predicting RUL using multivariate time-series sensor data from the NASA CMAPSS turbofan engine dataset, with a focus on understanding how predictive performance changes across datasets of varying complexity. The objective is to develop a reproducible machine learning pipeline that captures degradation patterns and produces reliable time-to-failure predictions. The approach includes data preprocessing, exploratory data analysis, feature engineering, dimensionality reduction, and model evaluation. RUL values are computed and capped to …

Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen

Discovery Day - Daytona Beach

The aviation industry relies heavily on accurate demand forecasting to guide critical decisions regarding route planning, capacity management, and pricing strategy. Misjudging passenger demand can result in significant revenue loss and operational inefficiency, making it essential for airlines and analysts to identify the key drivers of flight patronage. This study investigates the factors that most significantly predict the number of passengers on domestic flights departing from Hartsfield-Jackson Atlanta International Airport (ATL) during the 2024 calendar year. Using passenger and route data sourced from the Bureau of Transportation Statistics (BTS) and the U.S. Department of Transportation (DOT), a multiple regression analysis …

A Compact Representation Of Oscillatory Limits Via Asymptotic Value Distributions, Ibrahim Arnous, Eric M. Rodarte, Chirag Kumar

Discovery Day - Daytona Beach

Classical limits describe asymptotic behavior through convergence to a single value, but many important oscillatory functions do not converge in this sense. Standard examples such as sin(𝑥) as 𝑥→∞ and sin(1/x) as x→0 instead display stable distributions of values over time. This project examines how such behavior can be described using a measure-theoretic framework, particularly through occupation measures and, in sequence-based settings, Young measures. The objective is to present this perspective in a clear and accessible way while introducing the Ansatz representation, a compact notation for recording the support and density of an asymptotic value distribution when the limiting measure …