Digital Commons Network^™

Chatgpt Didn’T Write This: Evaluating The Impact Of Llms With A Case Study In Grading Cuny Language Immersion Program Student Essays, Benjamin Inbar

Dissertations, Theses, and Capstone Projects

This study evaluates the capabilities and limitations of large language models (LLMs), specifically OpenAI’s ChatGPT-4o, in grading essays from students in the City University of New York’s Language Immersion Program. The program serves English language learners with diverse linguistic and demographic backgrounds, offering intensive language instruction to prepare students for academic success in college. Using a dataset of 30 pre- and post-program essays scored by program instructors and ChatGPT-4o under three paradigms, this research explores the alignment between human and AI-generated scores across five rubric-based competency areas. Findings reveal that ChatGPT-4o aligns moderately with human grading, with the strongest agreement …

Bayesian Belief Networks: Redefining Wholesale Electricity Price Modelling In High Penetration Non-Firm Renewable Generation Power Systems, Martin J. Maticka, Thair S. Mahmoud

Research outputs 2022 to 2026

The transition of electricity generation from firm to non-firm renewable generation is driving changes in wholesale electricity price dynamics that are increasingly challenging to model due to the stochastic nature of wind and solar as the primary energy source. Robust pricing models are essential for optimising financial performance in liberalised electricity markets. The novelty of this paper is the application of Bayesian Belief Networks in the modelling of wholesale electricity price formation, specifically in power systems with a high penetration of non-firm renewable generation. This paper links the mathematical Bayesian representation to established statistical and computational approaches using a functional …

An Investigation Of Travel Distance And Timeliness Of Breast Cancer Treatment Among A Diverse Cohort In The United States, Swann Arp Adams, Oluwole Adeyemi Babatunde, Whitney Zahnd, Peiyin Hung, Karen E. Wickersham, Nathaniel Bell Ph.D., Jan M. Eberth Ph.D.

Publications

Travel to and from distant cancer treatment facilities can place a significant burden on cancer patients, particularly rural and minority survivors. Thus, the purpose of our investigation was to examine the association between patient travel distance and delays in types of treatment for breast cancer (surgery, radiation, chemotherapy, and hormonal therapy) and treatment delays. Using a novel linkage between the state cancer registry and administrative data from Medicaid and a private insurance plan, 2155 BC patients were successfully linked to create the cohort. ArcGIS was used to geocode all case residences and treatment facility addresses and calculate network distance between …

Ethnic Disparities In Hba1c And Hypoglycemia Among Youth With Type 1 Diabetes: Beyond Access To Technology, Social Deprivation And Mean Blood Glucose, J. Pemberton, Zhide Fang, Stuart Chalew, S. Uday

School of Public Health Faculty Publications

Introduction The UK national pediatric diabetes audit reports higher HbA1c for children and young people (CYP) with type 1 diabetes (T1D) of Black ethnicity compared with White counterparts. This is presumably related to higher mean blood glucose (MBG) due to lower socioeconomic status (SES) and less access to technology. We aimed to determine if HbA1c ethnic disparity persists after accounting for the above variables. Research design and methods A retrospective analysis of participants who received structured education in continuous glucose monitoring (CGM) use was conducted at a tertiary center. HbA1c was paired with glucose metrics from 90-day CGM data. The …

Racial Disparities Of Type 2 Diabetes Through Exercise: The Multi-Ethnic Study Of Atherosclerosis, Tong Xia, Roch A. Nianogo, Qingzhao Yu, Tamara Horwich, Preethi Srikanthan, Kosuke Inoue, Matthew Allison, Zuo-Feng Zhang, Karol E. Watson, Liwei Chen

School of Public Health Faculty Publications

Introduction: Persistent racial and ethnic disparities exist for Type 2 diabetes in the U.S. Racial and ethnic minorities have a higher risk of Type 2 diabetes, and studies suggest that they engage in less exercise than White population. This study examined whether and to what degree racial differences in Type 2 diabetes were explained by exercise. Methods: Adults aged 45–84 years without Type 2 diabetes at baseline (2000–2002) were included from the Multi-Ethnic Study of Atherosclerosis cohort and followed through 2020. Associations between race and Type 2 diabetes were examined using multivariable Cox proportional hazard regression. The effects of exercise …

Meditation In Qualitative Research For Bracketing And Beyond, Katalin Grajzel

Research Methods and Statistics: Graduate Student Scholarship

In this study, I recounted my experience using mantra meditation during a phenomenological study for the purposes of bracketing. The efficacy and purpose of bracketing have been debated from Husserl (1931), whose aimed was to achieve objectivity, to Heidegger (1962) who advocated for immersion of the researcher, through the French school (Merleau-Ponty, 1964) of middle ground, by whom bracketing was seen as the process to unearth and suspend biases for the better understanding of participants’ experiences (Arsel, 2017; Creswell & Creswell, 2017; Creswell & Poth, 2016; Fischer & Guzel, 2023). In this study, however, I propose another approach to bracketing …

Associations Between Social Determinants Of Health And Mental Health Disorders Among U.S. Population: A Cross-Sectional Study, S. Tanarsuwongkul

Faculty Publications

Aims

The impact of social determinants of health (SDOH) on mental health is increasingly realized. A comprehensive study examining the associations of SDOH with mental health disorders has yet to be accomplished. This study evaluated the associations between five domains of SDOH and the SDOH summary score and mental health disorders in the United States.

Methods

We analyzed data from a diverse group of participants enrolled in the All of Us research programme, a research programme to gather data from one million people living in the United States, in a cross-sectional design. The primary exposure was SDOH based on Healthy …

Kroger Post-Pandemic Customer Segmentation, Mario Mata, Joey Truitt, Renn Spigelmyer, Dhanuja Kasturiratna, Lisa Holden, Nitish Baidya, Hanna Tafari

Posters-at-the-Capitol

The grocery retail industry landscape has changed greatly in the wake of the pandemic. Specifically, delivery and pickup services have become more popular and customer buying habits have evolved. At the same time, improvements in data collection and analysis have allowed grocery marketing strategies to become highly individualized.

We worked with 84.51, an analytics firm, to identify customer segments for the Kroger Company based on data from 2023. Using clustering techniques, we organized customers into groups, or segments, based on similar characteristics. We identified and profiled four distinct groups of customers. Three segments were characterized by high frequency and spending …

Supplementary Files For: "Structure Identification For High-Dimensional Data In The Vicinity Of Bear Lake", Ben Shaw, Haley Burger, Brennan Bean, Kevin Moon

Browse all Datasets

This report focuses on seven water quality measurements taken at 43 different depths on the Bear Lake for the months of June - November in the years 2018 - 2023. These measurements create a high-dimensional dataset on which we apply state-of-the-art machine learning (ML) techniques to look for low-dimensional structure in the data. A similar effort was made for weather measurements taken near the lake. Our analysis revealed that water quality measurements tend to cluster (i.e., group together) by year, while weather measurements tend to cluster by time of the year. This suggests that the structure observed in the water …

Massera’S Theorem On Arbitrary Discrete Time Domains, Martin Bohner, Jaqueline G. Mesquita, Sabrina Streipert

Mathematics and Statistics Faculty Research & Creative Works

We present a general version of Massera's theorems for arbitrary discrete domains, based on a newly introduced definition for both linear and nonlinear equations. For scalar nonlinear equations, we identify sufficient conditions that ensure each µ-bounded solution approaches a periodic solution asymptotically. In the case of linear systems, we prove that the presence of a µ-bounded solution necessarily leads to a periodic solution. We also provide some examples to show the practical implications of our findings.

A Monte Carlo Study Of The Efficacy Of The Mantel-Haenszel Method At Detecting Item Bias, Macy Daulton

Masters Theses & Specialist Projects

The Mantel-Haenszel (MH) method is a statistical method used for differential item functioning analysis. Previous differential item functioning (DIF) research of the MH method focused on Type I error rates and statistical power. Not yet studied in the literature is whether excessive numbers of biased items may cause the MH method to fail to identify biased items. The proposed study employed a Monte Carlo design to determine the extent of bias in the match items necessary for the MH method to fail to identify a biased item. Results showed that the threshold was greater than was hypothesized, requiring nearly all …

On The Hölder Continuity Of The Brascamp-Lieb Constant, Ori Friesen

Mathematics, Statistics, and Computer Science Honors Projects

The Brascamp-Lieb inequality is a generalization of many well-known multilinear functional inequalities. The Brascamp-Lieb constant is the best constant that works for the Brascamp-Lieb inequality for a given tuple of input linear maps and powers. If we keep the powers constant while varying the input linear maps, the Brascamp-Lieb constant becomes a function of the linear maps. In this thesis, we explore the Hölder continuity of the Brascamp-Lieb constant. Specifically,we prove that the general 4-linear case of the Brascamp-Lieb inequality is locally Lipschitz continuous. Additionally, we provide an improvement of a previous result on the local Hölder continuity of the …

Estimation And Model Misspecification For Recurrent Event Data With Covariates Under Measurement Errors, Ravinath Alahakoon, Gideon K.D. Zamba, Xuerong Meggie Wen, Akim Adekpedjou

Mathematics and Statistics Faculty Research & Creative Works

For subject i, we monitor an event that can occur multiple times over a random observation window [0, (Formula presented.)). At each recurrence, p concomitant variables, (Formula presented.), associated to the event recurrence are recorded—a subset ((Formula presented.)) of which is measured with errors. To circumvent the problem of bias and consistency associated with parameter estimation in the presence of measurement errors, we propose inference for corrected estimating equations with well-behaved roots under an additive measurement errors model. We show that estimation is essentially unbiased under the corrected profile likelihood for recurrent events, in comparison to biased estimations under a …

Multi-Valued Variational Inequalities For Variable Exponent Double Phase Problems: Comparison And Extremality Results, Siegfried Carl, Vy Khoi Le, Patrick Winkert

Mathematics and Statistics Faculty Research & Creative Works

We prove existence and comparison results for multi-valued variational inequalities in a bounded domain Ω of the form (Formula presented.) where A:W1,H(Ω)→W1,H(Ω)∗ given by (Formula presented.) for u∈W1,H(Ω), is the double phase operator with variable exponents and W1,H(Ω) is the associated Musielak–Orlicz Sobolev space. First, an existence result is proved under some weak coercivity condition. Our main focus aims at the treatment of the problem under consideration when coercivity fails. To this end we establish the method of sub–super-solution for the multi-valued variational inequality in the space W1, H(Ω) based on appropriately defined sub- and super-solutions, which yields the existence …

Existence Results For A Discrete Fractional Boundary Value Problem, David Barilla, Martin Bohner, Giuseppe Caristi, Shapour Heidarkhani, Shahin Moradi

Mathematics and Statistics Faculty Research & Creative Works

In this study, we investigate the existence of at least one solution and the existence of an infinite number of solutions for a discrete fractional boundary value problem. Requiring an algebraic condition on the nonlinear term for small values of the parameter and requiring an additional asymptotical behavior of the potential at zero, we investigate the existence of at least one nontrivial solution for the problem. Moreover, under suitable assumptions on the oscillatory behavior of the nonlinearity at infinity, for exact collections of the parameter, we discuss the existence of a sequence of solutions for the problem. We also present …

On The Gumbel-Weibull{Cauchy} Distribution, Jennifer D. Pippin

Theses, Dissertations and Capstones

Developing new statistical distributions and seeking higher flexibility in modeling different shapes of data remain a strong emphasis in research. The T-R{Y } framework, introduced in [3], utilizes three statistical distributions in order to generate a new distribution. Many research papers appeared in literature to develop distributions based on the T-R{Y } framework. In this thesis, a member of the T-R{Y } framework, namely the Gumbel-Weibull{Cauchy} (GWC), is introduced. Statistical properties of the GWC are studied, such as the quantile function, the hazard function, transformations, Shannon entropy, the …

Floquet Theory For First-Order Delay Equations And An Application To Height Stabilization Of A Drone’S Flight, Martin Bohner, Alexander Domoshnitsky, Oleg Kupervasser, Alex Sitkin

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we proposed a version of the Floquet theory for delay differential equations. We demonstrated that very natural assumptions for control in technical applications can lead us to a one-dimensional fundamental system. This approach allowed researchers to work with classical methods used in the case of ordinary differential equations. On this basis, new original unexpected results on the exponential stability were proposed. For example, in the equation x' (4)+a(t)x(t—-T(7)) = 0, t € [0, co), we avoided the assumption on the smallness of the product sup,j9,.) 41 SUP;< {9,00) TD) < 3/2 for asymptotic stability. We obtained that in the case of w-periodic coefficient and delay, the fact that the period w was situated in a corresponding interval can lead to exponential stability. We then applied our new tests of stability to the stabilization of a drone's flight, where smallness of the noted above product could not be achieved from a technical point of view. For an equation with periodic coefficient and delay, we got a formula of the solution's representation on the semiaxis.

Gompertz Distribution On Time Scales, Wasiu Sule

Theses, Dissertations and Capstones

We shall investigate Gompertz dynamic equations within the context of time scales calculus, by exploring the mathematical foundations and applications of the Gompertz model, which is commonly used to describe growth phenomena in various fields such as biology and economics. This research seeks to analyze the Gompertz cumulative distribution functions (CDF) and probability density functions (PDF) across different time scales, including the real numbers R and integer multiples hN. Probability techniques will be used to derive the CDF and PDF associated with the Gompertz dynamic equations, and we will examine how varying the time scale impacts the characteristics …

A Unified Concept Of Periodicity On Any Time Scale And Applications, Martin Bohner, Jaqueline G. Mesquita, Sabrina H. Streipert

Mathematics and Statistics Faculty Research & Creative Works

We introduce a novel definition of periodicity on arbitrary time scales, dependent on a strictly increasing and differentiable function. This removes the commonly used and restrictive assumption of a periodic time scale to define periodic functions. Our new definition furthermore allows for a wider class of functions to be studied using the theory of periodic systems. After providing crucial properties of these periodic functions, such as the translation invariance of integrals of periodic functions, we apply the concept of this new periodicity to linear dynamic equations. We provide necessary and sufficient conditions for a linear dynamic equation to have such …

Empirical Vulnerability Function Development Based On The Damage Caused By The 2014 Chiang Rai Earthquake, Thailand, Patcharavadee Hong, Masashi Matsuoka

Institute for Innovation & Entrepreneurship Publications

Seismic hazards in Thailand are frequently overlooked in disaster management planning, leading to insufficient research and significant economic losses during earthquake events. The 2014 Chiang Rai earthquake exposed critical vulnerabilities in Thailand's building practices due to widespread non-compliance with building codes and limited preparedness. This exposure prompted the development of empirical vulnerability functions using loss data from 15,031 damaged residences. The study analyzed government compensation records, which were standardized using replacement cost metrics. Three distinct models were developed through probabilistic and possibilistic modeling approaches. Residual analysis demonstrated the superior performance of the possibilistic approach, with the Possibilistic-based Vulnerability Function achieving …

Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman

Data Science and Data Mining

We study prediction of superconducting critical temperature (Tc) from 81 composition-derived descriptors across 21,263 materials. To keep the analysis transparent and repro- ducible, we focus on linear models: Ordinary Least Squares (OLS), Ridge, Lasso, and Elastic Net (ENet). All models share a single evaluation protocol (5-fold cross-validation with standardized inputs) and are compared on RMSE, MAE, and R2. On this feature set, OLS attains the best cross-validated performance (RMSE = 17.6 K, MAE = 13.3 K , R2 = 0.735), with Lasso/ENet essentially tied next (RMSE ≈ 17.7 K , R2 ≈ 0.734); Ridge underperforms (RMSE = 18.9 K , …

Comparative Analysis Of Lasso, Ridge, And Elastic Net For Variable Selection In High-Dimensional Maize Data, Md Ahiduzzaman

Data Science and Data Mining

In high-dimensional genomic data analysis, traditional linear regression techniques often struggle due to the presence of a large number of predictor variables relative to observations. Penalized regression methods such as LASSO, Ridge, and Elastic Net have emerged as effective solutions by imposing regularization, which helps in managing multicollinearity and enhancing prediction accuracy. This study applies these techniques to the Maize dataset to model the time to male flowering, selecting relevant genetic markers as predictors. Our findings suggest that Elastic Net is particularly effective for high-dimensional data with correlated variables, achieving a balance between prediction accuracy and variable selection. The results …

Enhanced Kneser-Type Oscillation Criteria For Second-Order Functional Quasilinear Dynamic Equations On Time Scales, Taher S. Hassan, Elvan Akın, Bassant M. El-Matary, Ioan Lucian Popa, Mouataz Billah Mesmouli, Ismoil Odinaev, Akbar Ali

Mathematics and Statistics Faculty Research & Creative Works

This work presents new Kneser-type oscillation criteria for second-order quasilinear functional dynamic equations defined on arbitrary unbounded above time scales. Our approach employs the Riccati transformation technique in conjunction with the integral averaging method. The results show a significant improvement over recent Kneser-type oscillation criteria. We provided several illustrative examples to highlight the importance of our findings.

An Evaluation On The Uncertainty For The Routine Of Dosimetry Calibration At The National Secondary Standard Dosimetry Laboratory, Albania, Klotilda Nikaj

International Journal of Nuclear Security

Every employer must, in relation to any work with ionizing radiation that they undertake, take all necessary steps to restrict so far as is reasonably practicable the extent to which their employees and other persons are exposed to ionizing radiation. This goal leads to an increased awareness about the proper maintenance and annual calibration of the personal dosimeters to ensure an accurate and precise radiation dose. The present work has described the performance of the radiation system of the ¹³⁷Cs source at the National Secondary Standard Dosimetry Laboratory (SSDL), located at the Institute of Applied Nuclear Physics at the …

Gaps In Knowledge: Topological Insights Into The Structure Of Science, Gavin Engelstad

Mathematics, Statistics, and Computer Science Honors Projects

Understanding scientific development is essential to ascertaining the mechanisms leading us into the future. Building this understanding requires both methodological developments and empirical research. This thesis contributes in both aspects using a topological approach to examine scientific knowledge. The first section presents a new algorithm to find optimal cycle representatives for homological features in complex networks, a context for which we demonstrate existing algorithms can be inadequate. The second section applies a number of topological methods, including our cycle optimization algorithm, to data on individual scientific fields, demonstrating the value of topological approaches and highlighting new insights about how science …

Copula-Based Bayesian Model For Detecting Differential Gene Expression, Prasansha Liyanaarachchi, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

Deoxyribonucleic acid, more commonly known as DNA, is a fundamental genetic material in all living organisms, containing thousands of genes, but only a subset exhibit differential expression and play a crucial role in diseases. Microarray technology has revolutionized the study of gene expression, with two primary types available for expression analysis: spotted cDNA arrays and oligonucleotide arrays. This research focuses on the statistical analysis of data from spotted cDNA microarrays. Numerous models have been developed to identify differentially expressed genes based on the red and green fluorescence intensities measured using these arrays. We propose a novel approach using a Gaussian …

In Search Of The Rational Voter In The 2020 Presidential Election: Understanding The Impact Of Voter Costs And Benefits On Turnout, Norou Diawara, Tiffany Henley, Samuel L. Brown, Md Iqbal Hossain

Mathematics & Statistics Faculty Publications

The ability to vote is one of the most valuable rights and privileges afforded by the Constitution of the United States to its citizens. For many, voting is not just a civic duty; it is also a choice. Voting is crucial to our democracy, and any changes to it may affect the efficiency of the democratic process. The bigger question is whether voters behave rationally by engaging in a cost-benefit calculus in deciding whether or not to vote. Using data science, this paper will examine the probability of voting and investigate its impact via cost and benefit among other variables …

Handwritten Digit Recognition Using Machine Learning Classifiers, Md Ahiduzzaman

Data Science and Data Mining

This project explores and compares the performance of various machine learning classifiers for handwritten digit recognition using the MNIST dataset. The classifiers include Logistic Regression, k-Nearest Neighbors, and Convolutional Neural Networks. Each classifier is evaluated based on accuracy, precision, recall, F1-score, and confusion matrix analysis.

Statistical Analysis Of Climate Trends And Variability In Tarrant County Using Annual, Decade, And Three-Decade Time Periods, Quinnton Debolt

Earth & Environmental Sciences Theses - Archive

This study is a statistical analysis of climate trends within the Dallas-Fort Worth metroplex according to several time-scale models to understand how the climate for the locality has changed and to provide a basis for projections of what future climate might look like. Trends in mean temperature and precipitation for North Central Texas generally correlate with corresponding global trends linked to natural variability and anthropogenic-induced climate change. Temperature rises in this region annually by 0.08°C and by 0.22°C for a three-decade average. Seasonal increases in three-decadal averages of temperature for North Central Texas relative to the average of the reference …

The Presence Of Outer Giant Planets And Their Role In Inner Planet Formation With And Without Their Influence, Mateo E. Guerra Toro

Graduate Theses/Dissertations

We performed dynamical simulations of the giant impact phase of planet formation to investigate the formation of inner terrestrial planets under the influence of 4 solar system-like outer giant planets. We developed a new code using the N-body simulation suite REBOUND and REBOUNDx (Rein et al. (2019) and Tamayo et al. (2019)) to simulate 2 stages of planetary formation: a residual gaseous protoplanetary disk phase and subsequent dynamical evolution after the disk photoevaporates. The initial conditions for the inner planetary embryos were taken by Morrison et al. (2020) based on a range of solid surface densities that produced Super-Earth terrestrial …