Digital Commons Network^™

Mark Wollaeger, Kurt Koenigsberger

James Joyce Literary Supplement

No abstract provided.

Susan Stanford Friedman, Christine Froula

James Joyce Literary Supplement

No abstract provided.

Genetic Joyce, Emma-Louise Silva

James Joyce Literary Supplement

No abstract provided.

Irish Populism, Maxwell Woods

James Joyce Literary Supplement

No abstract provided.

Irish Environmental Humanities, Emily Reiff

James Joyce Literary Supplement

No abstract provided.

A Line Made By Farming, Seungho Lee

James Joyce Literary Supplement

No abstract provided.

Joyce, Emotion, And Belonging, Jason Parks

James Joyce Literary Supplement

No abstract provided.

Joyce’S Genealogy, Ryan Kerr

James Joyce Literary Supplement

No abstract provided.

Modern/Traditional/Radical, Shantam Goyal

James Joyce Literary Supplement

No abstract provided.

Albert L. Altman: A Political Model For Leopold Bloom, Shelly Harder

James Joyce Literary Supplement

No abstract provided.

Radio Empire, Alex Fabrizio

James Joyce Literary Supplement

No abstract provided.

Criticism By Other Means, Ericson Charlie

James Joyce Literary Supplement

No abstract provided.

High Hopes, Jack Dudley

James Joyce Literary Supplement

No abstract provided.

The Death Of Joyce: From Author To Reader, Trisevgeni Bilia

James Joyce Literary Supplement

No abstract provided.

House, Richard C. Crepeau

On Sport and Society

With the settlement in the House Case finally being accepted by U.S. District Judge Claudia Wilken, five years of litigation has come to a close. It might be tempting to say, “the other shoe has dropped.” Unfortunately, College Athletics is not a biped, but rather a centipede. It is likely then that hundreds of more shoes are yet to drop.

Comparative Analysis Of Matrix Factorization And Neural Collaborative Filtering For Movie Recommendation Systems, Mahyar Alinejad

Data Science and Data Mining

This paper presents a comparative study of two recommendation system approaches for predicting movie ratings: Matrix Factorization with Stochastic Gradient Descent (SGD) optimization and Neural Collaborative Filtering (NCF) using Tensor Flow. The study aims to evaluate the effectiveness of these methods in recommending movies to users based on the MovieLens 100K dataset. The Matrix Factorization approach utilizes latent features to model user preferences and item characteristics, optimizing parameters through SGD. On the other hand, NCF integrates traditional collaborative filtering with neural networks to capture complex user-item interactions. Experimental results demonstrate the performance of both models in terms of Root Mean …

Diopside-Based Bioactive Glass-Ceramic Nanoparticles For Osteoimmunomodulation, Sun Latt, Pedram Sotoudehbagha, Valeria Cardenas, Andres Larraza, Mehdi Razavi

Research Data and Datasets

This dataset corresponds to the original data for the manuscript titled Diopside-based Bioactive Glass-Ceramic Nanoparticles for Osteoimmunomodulation.

Detecting Physical Activity Using Wearable Sensor Data, Dipok Deb

Data Science and Data Mining

This study focuses on detecting physical activity using wearable sensor data, specifically distinguishing between walking and running. A dataset comprising accelerometer and gyroscope readings is used to train and evaluate various machine learning models, including logistic regression, random forest, k-nearest neighbors, naïve Bayes, and XGBoost. Extensive preprocessing, such as creating lag features and rolling statistics, is performed to enhance temporal data representation. The models are evaluated using metrics like accuracy, precision, recall, and F1 score. Incorporating lag and rolling features significantly improves model performance, with logistic regression achieving perfect scores across all metrics. These findings demonstrate the effectiveness of enhanced …

Public Health Simulation Infused Program (Pship) Toolkit, Desiree A. Díaz, Mindi Anderson, Francisco Guido-Sanz, Peggy Hill, Samantha Stephenson, Heather Peralta, Syretta Spears, Geraldine Luzincourt

Faculty Scholarship and Creative Works

Project Narrative

PURPOSE AND NEED

Purpose: Priorities set forth by the Health Resources & Services Administration (HRSA) are addressed in the proposed simulation program in an effort to meet curricular needs and foster care to the medically underserved in Florida, further exposing students to public healthcare needs. Interprofessional (nursing and social work) and intraprofessional (undergraduate nurse and Nurse Practitioner [NP]) instruction is essential in the simulation-based education (SBE) program, promoting important content on identifying risk factors and health assessment of the medically underserved community (MUC) (Education Priority 2, §831). Coordination of medical care is a vicarious learning opportunity for all …

2025 Coloring Pages

Special Collections & University Archives Coloring Pages (Text)

No abstract provided.

Agenda 2025-06, Staff Council

Staff Advisory Council Meeting Agendas

A meeting agenda is a list of the topics that will be discussed during a meeting, along with other details. The agenda is usually shared with participants before the meeting so they can prepare. The agenda's purpose is to give participants a clear outline of what should happen in the meeting, who will lead each task, and how long each step should take.

Meeting Minutes 05-21-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

Using Mini-Datasets To Build Quantitative Research Skills, Julio Montanez

Teaching Online Pedagogical Repository

This resource provides a gentle introduction to undergraduate students on the intricacies of creating quantitative datasets.

The Fundamentals To Reintroducing Fun At Work: A Collaborative Team Approach To Addressing Library Staff Dissatisfaction, Unhappiness, And Burnout, Chereeka Garner, Cynthia Dancel, Jason D. Phillips, Christopher Saclolo

Faculty Scholarship and Creative Works

"Having fun isn't hard when you've got a library card" (Arthur Read) but can be quite a challenge when you work at the library. Check out this session to discover ways an employee driven, administration supported library committee has worked to increase employee morale, build community among new and veteran library staff members, and provide off campus networking opportunities with minimal planning, building wide collaboration, and budget limitations.

Rose, The Commissioner, And The Hall, Richard C. Crepeau

On Sport and Society

It seems that the biggest news in baseball this week is off the field. Usually, that is not a good thing. Yesterday, the Commissioner of Baseball, Rob Manfred, announced that Pete Rose and sixteen other players have been re-instated from baseball’s “permanently ineligible” list. Among the sixteen others are several players caught up in the Black Sox scandal of 1919.

Microstructure Refinement And In Vivo Evaluation Of Biodegradable Magnesium Metal Matrix Composites, Pedram Sotoudehbagha, Alison Grise, Andrew Romero, Andres Larraza, Sun Latt, Abel Córdova Flores, Kayley Romero, John Lovejoy, Mehdi Razavi

Research Data and Datasets

This dataset corresponds to the original data for the manuscript titled Microstructure Refinement and In Vivo Evaluation of Biodegradable Magnesium Metal Matrix Composites.

The Power Of Preference: How Assignment Choice Shapes Learning In Statistics, Joshua Guillemette, Charlotte A. Jones-Roberts

Research Data and Datasets

Assignment choice is an increasingly explored instructional strategy in undergraduate education, particularly in courses where students often struggle to find personal relevance or maintain motivation. In statistics education, where conceptual abstraction and perceived difficulty are common barriers, offering structured choices in group formation and dataset selection may enhance engagement and learning outcomes. This study investigates the effects of assignment choice on student self-efficacy, performance, and group behavior within a large introductory statistics course. Using a one-way ANOVA design, the study compared academic outcomes across three conditions: randomly assigned groups, self-selected groups, and independent work. Students completed six scaffolded projects over …

Performance Of Lasso And Ridge Regression For Variable Selection In Genome-Wide Association Studies Of Maize Flowering Time, Dipok Deb

Data Science and Data Mining

Genome-Wide Association Studies (GWAS) are instrumental in identifying genetic variants linked to complex traits, providing valuable insights into trait heritability and biological mechanisms. This study applies GWAS to investigate flowering time in maize, a critical adaptive trait, using a diverse dataset of 5,000 recombinant inbred lines across eight environments. Traditional GWAS methods often encounter challenges in high-dimensional datasets due to the presence of multiple small-effect genetic loci. To address this, we compared two penalized regression methods—LASSO and Ridge regression—to perform variable selection and regression analysis within a GWAS framework. LASSO effectively reduced the number of predictors by selecting the most …

Data Science Job Salary Prediction Using Linear Regression, Dipok Deb

Data Science and Data Mining

In the evolving landscape of data science, accurate salary prediction plays a crucial role in shaping career expectations, informing educational strategies, and guiding organizational hiring decisions. This study investigates the key factors influencing entry-level data science salaries in the United States by applying a multiple linear regression model to a recent dataset spanning from 2020 to 2024. Through data preprocessing, transformation, and diagnostic evaluation, we identify how job roles, experience levels, employment types, work arrangements, residency status, and company size impact compensation. Despite challenges such as outliers, heteroscedasticity, and non-normal residuals, model refinements like the Box-Cox transformation and variable selection …

Handwritten Digit Recognition Using Machine Learning, Dipok Deb

Data Science and Data Mining

Handwritten Digit Recognition (HDR) remains a fundamental benchmark in pattern recognition and machine learning due to its practical applications and inherent classification challenges posed by diverse handwriting styles. This study investigates and compares two classical statistical classifiers—Gaussian Naive Bayes (GNB) and Linear Discriminant Analysis (LDA)—to recognize the digits from the MNIST dataset. Both models assume underlying normality in feature distributions and offer computational efficiency, making them suitable for high-dimensional input such as image pixels. Using 60,000 training and 10,000 test samples, we evaluate model performance through accuracy, precision, recall, F1 score, and confusion matrices. The results reveal that while GNB …