Physical Sciences and Mathematics Commons^™

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 …

Likelihood-Based Inference For The Poisson–Tweedie Family, Si Chen

Theses and Dissertations (Comprehensive)

This thesis develops likelihood-based methodology for flexible modeling and inference for heterogeneous count data within and adjacent to the Poisson–Tweedie family. A mean–dispersion regression framework is introduced to jointly relate the mean and dispersion to covariates, enabling separation of covariate-driven heterogeneity from distributional parameters. Likelihood inference is implemented using recursive probability mass function evaluation, and performance is assessed through simulation and applications including RNA-sequence counts. The framework is extended to accommodate excess zeros via zero-inflated Poisson–Tweedie models, with full likelihood-based estimation and improved risk estimation illustrated using insurance claim data. Finally, boundary behaviour is investigated through the discrete stable distribution …

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, …

Visualizing The Regression Lines And The Correlation Coefficient For Bivariate Discrete Random Variables Authors, Mamunur Rashid, Jyotirmoy Sarkar

Mathematics Faculty Publications

Sarkar and Rashid (2024) visualized the joint probabilities of two discrete random variables using a 2D disc plot from which they graphically obtained the conditional distributions of 𝑌 given 𝑋=𝑎, and 𝑋 given 𝑌=𝑏; and the marginal distributions of 𝑋, 𝑌, 𝑋+𝑌, 𝑋−𝑌, and 𝑐𝑋+𝑑𝑌. Sarkar and Rashid (2025) visualized the mean, mean deviation, and standard deviation of any discrete random variable using a disc plot. Here, starting with the 2D disc plot, we visualize the correlation coefficient between X and Y, and the linear regression of one variable from the other. Such visualizations help users better comprehend these concepts. …

Statistical Modeling Of Solar Flares During Solar Cycle 24 (2010–2015), Walae Dahmany '28

Annual Student Research Poster Session

Solar flares are energetic events driven by the rapid release of magnetic energy in the solar atmosphere and are an important source of space-weather disturbances. This study examined six years of solar flare activity during Solar Cycle 24 (2010–2015) using GOES X-ray observations and NOAA solar activity data. Flare frequency and intensity were analyzed alongside sunspot number, F10.7 cm radio flux, solar-cycle phase, Hale magnetic classification, previous flare activity, and waiting times between major flares. Statistical methods, including correlation and regression analyses, Cox proportional hazards modeling, and ARIMAX time-series forecasting, were used to investigate relationships between solar conditions and flare …

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 …

Graph-Theoretic Analysis Of Function Call Graphs Using L-Moments For Malware Detection, Anthony J. Rose, Wayne C. Henry, Scott R. Graham, Christine M. Schubert Kabban, Christopher M. Rondeau

Faculty Publications

Most malware detection continues to rely on signature matching, which struggles with obfuscated or novel variants. This research presents a malware detector that instead relies on the static structure of function call graphs, summarized using L-moments of the degree, betweenness, closeness, and clustering measures into compact, interpretable descriptors that persist across malware variants. Evaluated on 175,633 binaries spanning many families under balanced, natural-prevalence, and prevalence-weighted training regimes, ensemble methods achieved Area Under the Curve (AUC) values up to 0.98 on the full-corpus random split, while a feed-forward neural network remained robust across regimes with AUC 0.92–0.95. Linear baselines were far …

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 …

A Database Of Reliability-Targeted Snow Loads For The United States, Nicholas Brimhall, Cameron Swapp, Brennan Bean

Browse all Datasets

This data release provides the data and code necessary to create a database of 10,625 site-specific Reliability-Targeted Snow Loads (RTSLs) for locations in the Conterminous United States and Alaska. RTSLs are the design snow load requirements necessary to achieve the reliability targets set forth in Chapter 1 of the ASCE 7 Standard, which is the national standard that largely governs hazards-based design in the United States. The data and methods used in this data release are based upon the methods described in Bean et al. (2021), with updated data and refined methodology as applicable.

A Global Database Of Winter Wind Values, Jayden Gardner, Hannah Fluckiger, Nicholas Brimhall, Brennan Bean

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This repository contains the data and code necessary to create winter wind (W2) estimates for international locations. It is an extension of the approach outlined in Bean et al. (2025) to include additional data from European locations. Winter wind is defined as the proportion of time that the wind speed exceeds 10 mph during the months of October to April, which is used in snow load design to calculate the potential severity of drifting on a roof.

Base Maps And Other Source Files For: A Global Database Of Reliability-Targeted Snow Loads, Shaveen Britto, Nicholas Brimhall, Cameron Swapp, Brennan Bean, Jayden Gardner, Hannah Fluckiger

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The 2022 edition of ASCE 7 introduced reliability-targeted snow loads (RTSLs) for structural design. The development of design snow loads for locations outside the Conterminous United States (OCONUS) requires methods that can provide reliable estimates in regions with varying station density and climatic conditions. This repository contains the data and code used to develop and evaluate a climate-analog approach for estimating RTSLs at international locations. The climate-analog method identifies reference stations with similar climatic and geographic characteristics and uses their estimated RTSLs to predict snow loads at locations where direct observations are limited or unavailable. The methodology relies on station-level …

A Global Database Of Reliability-Targeted Snow Loads, Nicholas Brimhall, Cameron Swapp, Brennan Bean, Shaveen Britto, Jayden Gardner, Hannah Fluckiger

Browse all Datasets

This data release provides the data and code necessary to create a database of 18,809 site-specific Reliability-Targeted Snow Loads (RTSLs) for locations outside of the United States. RTSLs are the design snow load requirements necessary to achieve the reliability targets set forth in Chapter 1 of the ASCE 7 Standard, which is the national standard that largely governs hazards-based design in the United States. The intent of this release is to provide engineers seeking to use US-based design standards in international settings a database of snow load values consistent with the methodologies used to establish ground snow loads in ASCE …

Base Maps And Other Source Files For: A Database Of Reliability-Targeted Snow Loads For The United States, Nicholas Brimhall, Cameron Swapp, Brennan Bean

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This data release provides the supporting data and files to create a database of 10,625 site-specific Reliability-Targeted Snow Loads (RTSLs) for locations in the Conterminous United States and Alaska (see Brimhall et al. (2026)). RTSLs are the design snow load requirements necessary to achieve the reliability targets set forth in Chapter 1 of the ASCE 7 Standard, which is the national standard that largely governs hazards-based design in the United States. The data and methods used in this data release are based upon the methods described in Bean et al. (2021), with updated data and refined methodology as applicable.

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 …

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 …

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 …

Behind The Score: The Influence Of Neighborhood Policy Contexts On New York Regents Exam Performance Across New York City Public High Schools, Philip J. Kovacevic

Dissertations, Theses, and Capstone Projects

This study used a two-level hierarchical linear model (HLM) to test whether New York City neighborhood zoning and land-use characteristics independently predict school-level performance on the New York State Regents Examinations, after controlling for school demographic and organizational characteristics, and Regents mean scores, both drawn from the NYC DOE's Regents Exam Results file (NYC Public Schools InfoHub, 2024). Using NYC Primary Land Use Tax Lot Output (PLUTO) 2025 data, a Neighborhood Educational Quality (NEQ) index was built for each of the city’s 42 community districts by combining the commercial floor area ratio (CommFAR) and the proportion of lots zoned residential …

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

Dissertations

No abstract provided.

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, …

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 …

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, …

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 …