Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach,
2022
Sacred Heart University
Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit
WCBT Faculty Publications
In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors’ political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. …
Learning From Public Spaces In Historic Cities,
2022
Kennesaw State University
Learning From Public Spaces In Historic Cities, Cody Josh Kucharski
Symposium of Student Scholars
Successful public spaces in cities are key for enhancing social cohesion and improving health and safety. Learning from historic cities involves the development of representational and analytical tools aimed at capturing their essence as places of human interaction. The research reports findings of the spatial analysis of twenty Adriatic and Ionian coastal cities, which addresses the question of how the network of public spaces calibrates different degrees of spatial enclosure necessary for creating successful social interactions. Cities in the littoral region include well-preserved historic centers that are renowned for the successful integration of urban squares into the urban fabric. For …
Classification Of Breast Cancer Histopathological Images Using Semi-Supervised Gans,
2022
Southern Methodist University
Classification Of Breast Cancer Histopathological Images Using Semi-Supervised Gans, Balaji Avvaru, Nibhrat Lohia, Sowmya Mani, Vijayasrikanth Kaniti
SMU Data Science Review
Breast cancer is diagnosed more frequently than skin cancer in women in the United States. Most breast cancer cases are diagnosed in women, while children and men are less likely to develop the disease. Various tissues in the breast grow uncontrollably, resulting in breast cancer. Different treatments analyze microscopic histopathology images for diagnosis that help accurately detect cancer cells. Deep learning is one of the evolving techniques to classify images where accuracy depends on the volume and quality of labeled images. This study used various pre-trained models to train the histopathological images and analyze these models to create a new …
Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray,
2022
Southern Methodist University
Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray, Aswini Thota, Ololade Awodipe, Rashmi Patel
SMU Data Science Review
Since the pandemic started, researchers have been trying to find a way to detect COVID-19 which is a cost-effective, fast, and reliable way to keep the economy viable and running. This research details how chest X-ray radiography can be utilized to detect the infection. This can be for implementation in Airports, Schools, and places of business. Currently, Chest imaging is not a first-line test for COVID-19 due to low diagnostic accuracy and confounding with other viral pneumonia. Different pre-trained algorithms were fine-tuned and applied to the images to train the model and the best model obtained was fine-tuned InceptionV3 model …
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning.,
2022
University of Louisville
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Electronic Theses and Dissertations
The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …
Why, New York City? Gauging The Quality Of Life Through The Thoughts Of Tweeters,
2022
The Graduate Center, City University of New York
Why, New York City? Gauging The Quality Of Life Through The Thoughts Of Tweeters, Sheryl Williams
Dissertations, Theses, and Capstone Projects
As a resource for social data, Twitter’s platform has been used to measure the quality of life through sentiment analysis. This capstone project explores another methodological technique—querying Twitter data around specific keyword terms to determine dominant topics, word patterns, and sentiment leanings in a geographical area. Focusing on New York City and Los Angeles for comparative analysis, the keyword term “why” will be used to build a Python analysis around topic modeling and sentiment analysis. Using this approach, the analysis reveals social and cultural differences, the overall sentiment of tweets, and subjects of interest to tweeters.
GitHub Repository for all …
Optimal Time-Dependent Classification For Diagnostic Testing,
2022
Johns Hopkins University
Optimal Time-Dependent Classification For Diagnostic Testing, Prajakta P. Bedekar, Paul Patrone, Anthony Kearsley
Biology and Medicine Through Mathematics Conference
No abstract provided.
Attempting To Predict The Unpredictable: March Madness,
2022
University of Nebraska at Omaha
Attempting To Predict The Unpredictable: March Madness, Coleton Kanzmeier
Theses/Capstones/Creative Projects
Each year, millions upon millions of individuals fill out at least one if not hundreds of March Madness brackets. People test their luck every year, whether for fun, with friends or family, or to even win some money. Some people rely on their basketball knowledge whereas others know it is called March Madness for a reason and take a shot in the dark. Others have even tried using statistics to give them an edge. I intend to follow a similar approach, using statistics to my advantage. The end goal is to predict this year’s, 2022, March Madness bracket. To achieve …
Posterior Predictive Model Checking Of The Hierarchical Rater Model,
2022
University of Arkansas, Fayetteville
Posterior Predictive Model Checking Of The Hierarchical Rater Model, Nnamdi Chika Ezike
Graduate Theses and Dissertations
Fitting wrongly specified models to observed data may lead to invalid inferences about the model parameters of interest. The current study investigated the performance of the posterior predictive model checking (PPMC) approach in detecting model-data misfit of the hierarchical rater model (HRM). The HRM is a rater-mediated model that incorporates components of the polytomous item response theory (IRT) model, such as the partial credit model (PCM) and generalized partial credit model (GPCM), at the second level of the hierarchy, to model examinees’ responses to performance assessments. To date, the HRM has not been rigorously evaluated using PPMC techniques. Monte Carlo …
Applying Data Analytics As An Alternative To Subjective Rankings Of Players In Fantasy Basketball,
2022
United States Military Academy
Applying Data Analytics As An Alternative To Subjective Rankings Of Players In Fantasy Basketball, Christopher Collins
Mathematica Militaris
This paper demonstrates the ranking of players for fantasy basketball using one of the platforms of Multi Criteria Decision Making (MCDM), the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Specially, it compares results of TOPSIS generated fantasy rankings from the 2016-2017 NBA Season against industry fantasy experts’ 2017-2018 NBA pre-season rankings. Fantasy experts combine various techniques to create their rankings. Frequently blending quantitative and qualitative factors in order to project bottom-up rankings, they incongruently mix subjective and objective criterion. Conversely, TOPSIS is a mathematical way of doing literally what its name describes, ranking by a …
Impact Of Treatment Length On Individuals With Substance Use Disorders In Allegheny County,
2022
Duquesne University
Impact Of Treatment Length On Individuals With Substance Use Disorders In Allegheny County, Cassie Dibenedetti, Kate Rosello
Undergraduate Research and Scholarship Symposium
Auberle social services is opening the Family Healing Center (FHC), a level 3.5 treatment program in Pittsburgh, PA that provides housing and 24-hour support for families struggling with opioid addiction. We partnered with Auberle to study characteristics of individuals receiving level 3.5 treatment and to determine whether longer treatment lengths correlate with fewer adverse outcomes. We obtained data from the Allegheny County Department of Human Services on 2,016 individuals admitted to level 3.5 treatment in 2019. The data included birth year, race, gender, admittance date, discharge date, and Children Youth and Family (CYF) incidents before and after treatment. We categorized …
Machine Learning In Support Of Student Success,
2022
Stephen F Austin State University
Machine Learning In Support Of Student Success, Rachel Rucker
Undergraduate Research Conference
Our goal is to predict whether a student will finish the semester on academic probation by mid-term using university data.
Power Properties Of Ordinal Regression Models For Likert Type Data,
2022
Swedish University of Agricultural Sciences
Power Properties Of Ordinal Regression Models For Likert Type Data, Ulf Olsson
Practical Assessment, Research, and Evaluation
We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample t tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size n=10 and n=30 were generated, with three different degrees of skewness. For all sample sizes and degrees of skewness, the ordinal probit model has highest power. This is not surprising since the data was generated with this model in mind. Slightly more surprising is that the t test has higher power than the Wilcoxon test in …
Split Classification Model For Complex Clustered Data,
2022
University of Nebraska - Lincoln
Split Classification Model For Complex Clustered Data, Katherine Gerot
Honors Theses, University of Nebraska-Lincoln
Classification in high-dimensional data has generated tremendous interest in a multitude of fields. Data in higher dimensions often tend to reside in non-Euclidean metric space. This prevents Euclidean-based classification methodologies, such as regression, from reliably modeling the data. Many proposed models rely on computationally-complex embedding to convert the data to a more usable format. Others, namely the Support Vector Machine, rely on kernel manipulation to implicitly describe the "feature space" to arrive at a non-linear decision boundary. The proposed methodology in this paper seeks to classify complex data in a relatively computationally-simple and explainable manner.
Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering,
2022
Channel Partners
Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering, Edward Krueger, Landon Thompson, Josh Moore
SDSU Data Science Symposium
This presentation will focus first on providing an overview of Channel and the Risk Analytics team that performed this case study. Given that context, we’ll then dive into our approach for building the modeling development data set, techniques and tools used to develop and implement the model into a production environment, and some of the challenges faced upon launch. Then, the presentation will pivot to the data engineering pipeline. During this portion, we will explore the application process and what happens to the data we collect. This will include how we extract & store the data along with how it …
The Data Analytics And The Science Revolution,
2022
Embry-Riddle Aeronautical University
The Data Analytics And The Science Revolution, Leila Halawi, Amal Clarke, Kelly George
Publications
This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they …
Slices Of The Big Apple: A Visual Explanation And Analysis Of The New York City Budget,
2022
The Graduate Center, City University of New York
Slices Of The Big Apple: A Visual Explanation And Analysis Of The New York City Budget, Joanne Ramadani
Dissertations, Theses, and Capstone Projects
As a component of government, budgets are fundamental not only to improving the quality of a shared society, but also to understanding what our government officials consider to be their priorities. However, most budgets can be difficult to understand, using terms that are not familiar to people who have not studied finance or economics. To that end, Slices of the Big Apple is an interactive, centralized narrative website that uses visualizations at its core in order to: 1) facilitate a holistic understanding of the New York City government budget for NYC residents; and 2) conduct a five-year analysis of Community …
A Monte Carlo Simulation Of Rat Choice Behavior With Interdependent Outcomes,
2022
West Virginia University
A Monte Carlo Simulation Of Rat Choice Behavior With Interdependent Outcomes, Michelle A. Frankot
Graduate Theses, Dissertations, and Problem Reports
Preclinical behavioral neuroscience often uses choice paradigms to capture psychiatric symptoms. In particular, the subfield of operant research produces nested datasets with many discrete choices in a session. The standard analytic practice is to aggregate choice into a continuous variable and analyze using ANOVA or linear regression. However, choice data often have multiple interdependent outcomes of interest, violating an assumption of general linear models. The aim of the current study was to quantify the accuracy of linear mixed-effects regression (LMER) for analyzing data from a 4-choice operant task called the Rodent Gambling Task (RGT), which measures decision-making in the context …
Graph Neural Networks For Improved Interpretability And Efficiency,
2022
University of Central Florida
Graph Neural Networks For Improved Interpretability And Efficiency, Patrick Pho
Electronic Theses and Dissertations, 2020-
Attributed graph is a powerful tool to model real-life systems which exist in many domains such as social science, biology, e-commerce, etc. The behaviors of those systems are mostly defined by or dependent on their corresponding network structures. Graph analysis has become an important line of research due to the rapid integration of such systems into every aspect of human life and the profound impact they have on human behaviors. Graph structured data contains a rich amount of information from the network connectivity and the supplementary input features of nodes. Machine learning algorithms or traditional network science tools have limitation …
A Predictive Model To Predict Cyberattack Using Self-Normalizing Neural Networks,
2022
Marshall University
A Predictive Model To Predict Cyberattack Using Self-Normalizing Neural Networks, Oluwapelumi Eniodunmo
Theses, Dissertations and Capstones
Cyberattack is a never-ending war that has greatly threatened secured information systems. The development of automated and intelligent systems provides more computing power to hackers to steal information, destroy data or system resources, and has raised global security issues. Statistical and Data mining tools have received continuous research and improvements. These tools have been adopted to create sophisticated intrusion detection systems that help information systems mitigate and defend against cyberattacks. However, the advancement in technology and accessibility of information makes more identifiable elements that can be used to gain unauthorized access to systems and resources. Data mining and classification tools …