Bridging The Gap Between Career Expectations Versus Labor Market Realities,
2027
Ateneo de Manila University
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 …
When Three Points Aren't Enough: Parameter Estimation In Newton's Law Of Cooling,
2026
Florida Gulf Coast University
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,
2026
Physiotherapy Department, Technical Health and Medical College, Erbil Polytechnic University, 44001, Erbil- Kurdistan region, Iraq
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 …
Mapping The Water Quality Of Jamaica Bay, New York (1996-2024): Principal Component Analysis And K-Means Clustering,
2026
CUNY Graduate Center
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 …
Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024,
2026
Embry-Riddle Aeronautical University
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 …
Bounded Thunderstorm Tracking Of Lightning Events With Muon Detection,
2026
Embry-Riddle Aeronautical University
Bounded Thunderstorm Tracking Of Lightning Events With Muon Detection, Skylar Wardlaw, Ainsley Helgerson, Maria Kaminska, Logan Velvet, Georgii Dubrov, Jackson Stewart, Aaron Jung, Nathaniel O’Hara, Amelia Koth, Nash Mcleod, Emaleth Wyckoff
Discovery Day - Daytona Beach
The muon is a high-energy particle that can be produced by cosmic rays and trigger upper-atmospheric particle cascades and energetic processes. It has been hypothesized that such cascades are at the onset of lightning. As such, muons serve as a valuable probe for investigating the underlying mechanisms of its initiation, whose full governing dynamics remain vastly unknown despite extensive research. Traditional approaches to lightning research involve simulations and observations of the discharge itself, but the role of high-energy particle interactions has yet to be fully constrained. The CosmicWatch Muon Detector design enables the detection of atmospheric muons through scintillation events, …
Statistical Methodologies For Count Time Series Analysis And Topological Data Analysis Of Medical Images,
2026
Southern Methodist University
Statistical Methodologies For Count Time Series Analysis And Topological Data Analysis Of Medical Images, Yuhyeong Jang
Statistical Science Theses and Dissertations
This dissertation addresses two distinct topics related to count time series analysis and topological medical image analysis, respectively. The first part of the dissertation comprises an application of a count time series model to analysis of US monthly sex trafficking data and development of a new model for multivariate count data that exhibits serial dependence and overdispersion. By imposing a family of multivariate mixed Poisson distributions on the count random vector, the proposed model can accommodate a broad range of overdispersion as well as positive contemporaneous correlations. For maximum likelihood estimation, a computationally feasible EM-type algorithm is derived based on …
Ground To Roof Snow Load Ratio (Gr) Data Release,
2026
Utah State University
Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire
Browse all Datasets
This data release provides historical ground-to-roof snow load ratio (GR) datasets used for snow load research and model development. The release includes original referenced datasets, cleaned country specific datasets, and a master dataset that combines Canadian and United States datasets into a standardized format for research and engineering applications.
Modeling Mean And Variability Of Anxiety In Ecological Momentary Assessment Data Using Mixed-Effects Location–Scale Models,
2026
East Tennessee State University
Modeling Mean And Variability Of Anxiety In Ecological Momentary Assessment Data Using Mixed-Effects Location–Scale Models, Trenzy Odero
Electronic Theses and Dissertations
Ecological Momentary Assessment is a method of collecting repeated measures of people in real time within natural environments. This results in hierarchical data that has a significant amount of variation at the person level. The traditional linear mixedeffects models assume that the residual variance is constant, which might not be true when the residual variance varies among individuals as well as in time. This thesis uses mixed-effects location-scale (MELS) models to model the mean and variance of an EMA outcome together. By introducing the possibility of variability in residual variance within and across individuals and with covariates, the MELS framework …
Volatility Spillovers Between Stock Prices And Exchange Rates: Insights For Risk Management And Investment Strategies: Evidence From China, India, And Pakistan Using Bekk-Garch Models,
2026
University of Karachi
Volatility Spillovers Between Stock Prices And Exchange Rates: Insights For Risk Management And Investment Strategies: Evidence From China, India, And Pakistan Using Bekk-Garch Models, Samreen Fatima, Humera Sultana, Muhammad Najamuddin Dr., Saba Naz
The Indonesian Capital Market Review
This study investigates the dynamics of volatility and its spillover effects between the stock markets of China, India, and Pakistan, and their respective exchange rates (USD/CNY, USD/INR, and USD/ PKR). Volatility is modeled using the Symmetric and Asymmetric BEKK-GARCH (1,1) and DCCGARCH (1,1) models, based on daily return series covering the period from January 1, 2019, to January 31, 2025. The empirical results indicate that both the employed models are adequate for capturing the volatility dynamics. The findings reveal that the highest value of portfolio weights and hedging efficiency of KSE-100 Index–USD/PKR provide optimal portfolio allocation and highest hedging performance …
What We Know About Accounting Ratios: Methodological Considerations,
2026
Faculty of Management, University of Warsaw, Poland
What We Know About Accounting Ratios: Methodological Considerations, Wojciech Kuryłek, Oskar Kowalewski
Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski
Purpose: This paper provides a comprehensive literature review of the methodological aspects of financial ratio analysis, consolidating dispersed knowledge on the computation, statistical properties, and appropriate usage of accounting ratios.
Design/Methodology/Approach: The study adopts a narrative literature review methodology, systematically surveying published research on financial ratio distributions, normality testing, data transformations, outlier handling, the proportionality assumption, dimensionality reduction techniques, compositional data analysis, and recommended ratio sets for corporate financial research.
Findings: Financial ratios predominantly deviate from normal distributions, exhibiting skewness, excess kurtosis, and sensitivity to outliers. Transformation techniques such as logarithmic, square root, and Box‑Cox methods yield mixed results in …
Statistical Evaluation Of A New Orleans Historic Rainfall Dataset (1840–1893),
2026
Louisiana State University and Agricultural and Mechanical College
Statistical Evaluation Of A New Orleans Historic Rainfall Dataset (1840–1893), Arielle C. Filostrat
LSU Master's Theses
This study evaluates the climatic credibility of a newly identified historical rainfall dataset for New Orleans, Louisiana, spanning 1840–1893. The New Orleans Historical Dataset (NOHD) is compared to a modern observational record from the Audubon rain gauge (1893–2024) to determine whether nineteenth-century rainfall observations are consistent with known precipitation behavior in the region. Establishing the reliability of early records is critical for extending climatological baselines and improving understanding of long-term rainfall variability.
Historical rainfall observations were first evaluated through archival review using the New Orleans Medical and Surgical Journal and other nineteenth-century meteorological records to verify notable rainfall events. Daily …
Mengukur Capaian Dan Identifikasi Konvergensi Pembangunan Infrastruktur Antarprovinsi Di Indonesia,
2026
Kementerian Usaha Mikro Kecil dan Menengah, Jakarta, Indonesia
Mengukur Capaian Dan Identifikasi Konvergensi Pembangunan Infrastruktur Antarprovinsi Di Indonesia, Ressa Isnaini Arumnisaa', Aisyah Fitri Yuniasih
Jurnal Ekonomi dan Pembangunan Indonesia
Indonesia’s economic challenges are characterized by stagnant economic growth and regional development disparities. This study analyzes the achievement and convergence of infrastructure development across provinces in Indonesia during 2011–2021 through the construction of an Infrastructure Development Index (IPI). The study employs panel data from 33 provinces, using factor analysis to construct the IPI and the First Difference Generalized Method of Moments (FD-GMM) to examine convergence and its determinants. The results show that many provinces still have IDI scores below the national average. Furthermore, the FD-GMM model shows that σ-convergence and β-convergence occur in Indonesia. In addition, GRDP per capita, inflation, …
It's All In The (Exponential) Family: An Equivalence Between Maximum Likelihood Estimation And Control Variates For Sketching Algorithms,
2026
Bucknell University
It's All In The (Exponential) Family: An Equivalence Between Maximum Likelihood Estimation And Control Variates For Sketching Algorithms, Keegan Kang, Kerong Wang, Ding Zhang, Rameshwar Pratap, Bhisham Dev Verma, Benedict Wong
Faculty Conference Papers and Presentations
Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching algorithms and applications in machine learning. We prove that under certain conditions in an exponential family, an optimal CVE will achieve the same asymptotic variance as the MLE, giving a fixed point algorithm for the MLE. Experiments show the fixed point algorithm is faster and numerically stable compared to other root finding algorithms for the MLE for the bivariate Normal distribution, and we expect this to hold across distributions satisfying these conditions. We show how this algorithm leads to reproducibility for …
Estimasi Underground Economy Triwulanan Di Indonesia Pada Tahun 2010–2023,
2026
Program Studi Statistika, Politeknik Statistika STIS, Jakarta, Indonesia
Estimasi Underground Economy Triwulanan Di Indonesia Pada Tahun 2010–2023, Ghina Anandhia, Hardius Usman
Jurnal Ekonomi dan Pembangunan Indonesia
Underground economics have a significant impact on economy. Underground economy leads to low potential state revenues from the tax sector. This study estimates the quarterly value of the underground economy in Indonesia from 2010 to 2023 using the Error Correction Model (ECM) method. The results show that the average value of the underground economy in Indonesia is IDR138,392.32 billion, equivalent to 5.36 percent of Gross Domestic Product (GDP) and 35.72 percent of tax revenue from 2010 to 2023. GDP and tax burden variables have a positive influence on currency demand.
(R2174) A Stationary First-Order Autoregressive Process With New Discrete Lindley Marginal Distribution,
2026
Norbert ZONGO University Koudougou, Burkina Faso
(R2174) A Stationary First-Order Autoregressive Process With New Discrete Lindley Marginal Distribution, Tégawendé Martin Kabore, Jean-Etienne Ouindllassida Ouédraogo
Applications and Applied Mathematics: An International Journal (AAM)
This paper introduces a new stationary first-order autoregressive integer-valued process with a marginal distribution following the New Discrete Lindley distribution, referred to as NDLINAR( 1). The process is developed to model over-dispersed count time series exhibiting a mixed behavior arising from the combination of multiple distributions. Its statistical properties are thoroughly investigated, and the parameters are estimated using conditional maximum likelihood. The asymptotic properties of the estimators are also analyzed. The performance of the proposed model is evaluated by comparing it with other existing INAR(1) processes through applications to real datasets. Results demonstrate that the NDL-INAR(1) process effectively captures the …
Mycelial Modeling: Teaching Biology Students Statistical Modeling With Mushrooms,
2026
Portland State University
Mycelial Modeling: Teaching Biology Students Statistical Modeling With Mushrooms, Colette Wolf
University Honors Theses
This paper summarizes and describes the development of a set of learning materials that were created to educate students and professionals from other fields in statistical modeling techniques. These materials are primarily aimed at biology students, but are still intended to be useful for anyone who is interested in incorporating decision trees and random forest models into their personal research in the future. By directing the reader towards the JMP software, these materials navigate around the statistical knowledge base and coding implementation practices that otherwise would serve as a barrier to learning statistical modeling techniques, and instead focus on the …
Developing A Humpback Whale Vocalization Detector Using Machine Learning Models,
2026
California Polytechnic State University, San Luis Obispo
Developing A Humpback Whale Vocalization Detector Using Machine Learning Models, Lucas Kantorowski
Master's Theses
Humpback whale songs are notoriously complex. Identification of humpback whale song units requires bioacousticians to tediously listen, analyze, and annotate collected sound data. Even sparse data requires listening to the entirety of the collected acoustic data. In this study, three hours of audio containing over one-thousand humpback whale song units was collected in Monterey Bay, California.
Prior studies have seen success using convolutional neural networks by performing image classification on hundreds of hours worth of spectrograms. Our study uses traditional machine learning models, as they are less computationally demanding, and require less data.
We use time splitting and Mel-frequency cepstrum …
Muon Lifetime: Theory, Experiment, And Simulation,
2026
California Polytechnic State University, San Luis Obispo
Muon Lifetime: Theory, Experiment, And Simulation, Soren Agustin Munoz
Physics
This senior project investigates the muon lifetime through three complementary approaches: theoretical calculation, laboratory measurement, and computational simulation. The theoretical component develops the necessary background from relativistic field theory to the effective weak interaction, culminating in the leading-order Fermi-theory prediction of τ ≈ 2.2 μs, which explains why the muon lifetime lies on the microsecond scale.
The experimental component measures the lifetime of stopped cosmic-ray muons using a plastic scintillator, photomultiplier tube, and analog timing electronics. A binned Poisson likelihood fit to the primary 15-day acquisition run τ = 2.17+0.03-0.09 μs, consistent with the accepted value within the …
A Predictive Coding Account Of Spatial Working Memory Following Prophylactic Levetiracetam Administration Prior To Traumatic Brain Injury,
2026
CUNY Graduate Center
A Predictive Coding Account Of Spatial Working Memory Following Prophylactic Levetiracetam Administration Prior To Traumatic Brain Injury, Omeima Mutwali
Dissertations, Theses, and Capstone Projects
Traumatic brain injury (TBI) symptom prevention and remediation is an important area of research that would benefit vulnerable groups, including active-duty and veteran soldiers. These patients can sustain penetrative forces in fields of combat or in training, which result in focal lesions that trigger inflammatory and degenerative processes in the brain. Both primary and secondary injuries are associated with changes to cognition, behavior and affective state. This disease poses increased risk of epileptogenesis, as well. Given these outcomes, prior research has evaluated levetiracetam (LEV) as a prophylactic treatment for seizures, cognitive deficits and negative emotionality. LEV acts as a presynaptic …
