Categorical Data Analysis Commons^™

Data Driven Analysis Of Samara Seed Kinematics And Dynamics, Shashwat Sparsh

Master's Theses

Samara Seeds are a class of fruit most famously belonging to the Acer species and are characterized by their single-bladed geometry and their auto-rotation response during descent. This steady-state auto-rotation response is the subject of aerodynamic analysis which aim to quantify the performance. The period prior to the beginning of steady-state auto-rotation is classified as the transition regime and has not been the subject of intense scrutiny.

This thesis employs a data-driven approach to analyzing the kinematic and dynamic response of these seeds during both the transition and auto-rotation stages of flight to quantify the performance with respect to the …

Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach, Daniel C. Tisdale

Master's Theses

We introduce a novel integration of real-time, predictive eye-gaze tracking models into a multimodal dialogue system tailored for remote health assessments. This system is designed to be highly accessible requiring only a conventional webcam for video input along with minimal cursor interaction and utilizes engaging gaze-based tasks that can be performed directly in a web browser. We have crafted dynamic subsystems that capture high-quality data efficiently and maintain quality through instances of user attrition and incomplete calls. Additionally, these subsystems are designed with the foresight to allow for future re-analysis using improved predictive models, as well as enable the creation …

Node Classification On Relational Graphs Using Deep-Rgcns, Nagasai Chandra

Master's Theses

Knowledge Graphs are fascinating concepts in machine learning as they can hold usefully structured information in the form of entities and their relations. Despite the valuable applications of such graphs, most knowledge bases remain incomplete. This missing information harms downstream applications such as information retrieval and opens a window for research in statistical relational learning tasks such as node classification and link prediction. This work proposes a deep learning framework based on existing relational convolutional (R-GCN) layers to learn on highly multi-relational data characteristic of realistic knowledge graphs for node property classification tasks. We propose a deep and improved variant, …

Analyzing Student Experience On Group Work With The Application Of Different Group Allocation Approaches, An Yee Tan

Management and HR

Working as a group can be as challenging as working by oneself. Common issues like ineffective group work, unequal work contribution, and poor communication are believed to be the reasons why many students preferred to work individually. The purpose of this study is to understand if there is a disparity in student experience on group work by implementing different methods of group formation, which are, intentional group formation and random assignment. Topics around team well-being, team communication, and team effectiveness are the main focus of this study. The second emphasis of this study is students’ opinions on whether or not …

Analysis Of The Precipitation Detection Algorithm For The Geonor T-200b Precipitation Gauge To Improve Accuracy, Megan Lerman, Robert K. Goodrich

STAR Program Research Presentations

In an effort to improve the precipitation detection algorithm for the Geonor All Weather Precipitation Gauge, an automated truth algorithm has been created to detect errors in the original algorithm. The original algorithm detects precipitation in real time and uses the rate of precipitation to indicate an event. The automated truth does not detect in real time, and focuses on precipitation accumulation to indicate an event. Since the automated truth is delayed, it is able to consider the data collected before and after the point it is analyzing. The automated truth is already more accurate than the original algorithm but …

Mapping Open Water Bodeis With Optical Remote Sensing, Mary Ellen O'Donnell, Erika Podest

STAR Program Research Presentations

There is interest in mapping open water bodies using remote sensing data. Coverage and persistence of open water is currently a poorly measured variable due to its spatial and temporal variability across landscapes, especially in remote areas. The presence and persistence of open water is one of the primary indicators of conditions suitable for mosquito breeding habitats. Predicting the risk of mosquito caused disease outbreaks is a required step towards their control and eradication. Satellite observations can provide needed data to support agency decisions for deployment of preventative measures and control resources. This study, which will try to map open …

Using Remote Sensing Data To Predict The Spread Of Mosquito Borne Disease, Mary Ellen O'Donnell, Erika Podest

STAR Program Research Presentations

There is interest in how environmental variables derived from satellite data such as temperature, vegetation cover, and precipitation correlate to vector borne disease occurrence such as malaria and dengue fever. This study will be carried out using a decision tree based open source software called Random Forests to find correlations between the remote sensing variables and mosquito abundance. Software will be written in C# to take large amounts of data from the NASA satellite database and automatically format it for the Random Forest Software input. Correlations found, using Random Forests, between disease incidence and the variables can be used as …

A Comparison Of Prenatal Alcohol, Tobacco, And Other Drug Use Between San Luis Obispo County And Ventura County, Dana M. Williamson

Statistics

Prenatal substance abuse is a growing issue in America. It can lead to fetal alcohol spectrum disorder, long term growth, behavior, and executive functioning problems, and creates a predisposition for drug use for the child.

This project summarizes the statistical analyses comparing alcohol, tobacco, and other drug use by pregnant women between San Luis Obispo County and Ventura County. The main goal of these analyses is to determine if there is a difference between San Luis Obispo County and Ventura County. This is an interesting comparison because these counties are neighboring counties, and past data have shown that the rate …

An Analysis Of Risk Reduction Choices In Dcis Breast Cancer Patients, Lauren Soltesz

Statistics

The main focus of this paper was to evaluate possible demographic and clinical characteristics associated with a woman’s choice of breast conserving surgery (BCS), unilateral mastectomy (ULM), or bilateral risk reduction mastectomy (BRRM). The cohort consisted of patients presenting to the City of Hope National Medical Center with ductal carcinoma in situ breast cancer who elected to have cancer directed surgery (N=305). Analyses to examine associations of patient characteristics with type of surgery were conducted using a multinomial logistic regression. Results showed that older women were more likely to choose breast conserving surgery over bilateral risk reduction mastectomy than younger …

Analysis Of Alcohol Use Among Pregnant Women In San Luis Obispo County, Samantha Law

Statistics

Drinking alcohol during pregnancy is harmful to the fetus, and can lead to serious alcohol related developmental birth defects. Utilizing prenatal screening, such as the 4P’s Plus© screening tool, during a woman’s first prenatal doctors visit can help educate women and reduce continued alcohol use during pregnancy. Currently the CDC reports that 1 in 13 women in the US drink alcohol while pregnant compared to local reports that 1 in 3 women in San Luis Obispo County continue to drink alcohol during pregnancy. A primary concern for many local county health care experts and organizations is to raise awareness that …

Comparative Analysis Of Dispersion Parameter Estimates In Loglinear Modeling: Applied To E-Commerce Sales And Customer Data, Scott Davis

Statistics

When loglinear models are applied to count data the issue of over-dispersion often arises. Moment and maximum likelihood estimation methods in accounting for over-dispersion are widely used because they allow for model checking tools such as Chi-square, F, and likelihood ratio tests. Here is a comparison between R functions that each uses one method; glm.nb uses MLE, and glm.poisson.disp uses MME. The Index of Dissimilarity and visual model selection (ECDF plots) are also incorporated. These are applied to sales data using product and customer information compiled over the last five years that was generously provided by an e-commerce company.

Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison

Statistics

As a student, I noticed that the statistical package R (http://www.r-project.org) would have several benefits of its usage in the classroom. One benefit to the package is its free and open-source nature. This would be a great benefit for instructors and students alike since it would be of no cost to use, unlike other statistical packages. Due to this, students could continue using the program after their statistical courses and into their professional careers. It would be good to expose students while they are in school to a tool that professionals use in industry. R also has powerful …

Using Etf Data To Monitor Systemic Risk, Melissa A. Siemer, Brett Amidan

STAR Program Research Presentations

In 2010, President Obama signed The Dodd-Frank Wall Street Reform and Consumer Protection Act, which requires financially based government agencies and 35 major US banks to monitor systemic risk. This was in response to the recent near financial collapse due to major mistakes made by organizations generally considered "too big to fail". Systemic risk is the risk of the collapse of an entire financial system or market. It refers to the risks imposed by interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a cascading failure. In April 2011, the …

How To Combine Independent Data Sets For The Same Quantity, Theodore P. Hill, Jack Miller

Research Scholars in Residence

This paper describes a new mathematical method called conflation for consolidating data from independent experiments that measure the same physical quantity. Conflation is easy to calculate and visualize and minimizes the maximum loss in Shannon information in consolidating several independent distributions into a single distribution. A formal mathematical treatment of conflation has recently been published. For the benefit of experimenters wishing to use this technique, in this paper we derive the principal basic properties of conflation in the special case of normally distributed (Gaussian) data. Examples of applications to measurements of the fundamental physical constants and in high energy physics …

Like Mother Like Child: An Investigation Of Mother Characteristics And Child Temperaments, Tempus Fugitt

Statistics

Much research has gone into what biological and social factors raise the risk of children developing cognitive, social, or behavioral problems. This project looks at what characteristics of the mother are significantly associated with different temperaments in the child which may predict problems developed in the child later in life. These characteristics include mother’s age, her education level, household income, parenting attitudes, involvement with the child, and drug and alcohol use. Data was used from the Fragile Families and Child Wellbeing Study conducted by the Office of Population Research at Princeton University. Cumulative logistic regression was used to analyze the …

Investigating Relationships In The Flash Pilot Study For Stride, Mathew R. Adams, Katrina J. Jackson, Andrew J. Zbin

Statistics

No abstract provided.

Software Internationalization: A Framework Validated Against Industry Requirements For Computer Science And Software Engineering Programs, John Huân Vũ

Master's Theses

View John Huân Vũ's thesis presentation at http://youtu.be/y3bzNmkTr-c.

In 2001, the ACM and IEEE Computing Curriculum stated that it was necessary to address "the need to develop implementation models that are international in scope and could be practiced in universities around the world." With increasing connectivity through the internet, the move towards a global economy and growing use of technology places software internationalization as a more important concern for developers. However, there has been a "clear shortage in terms of numbers of trained persons applying for entry-level positions" in this area. Eric Brechner, Director of Microsoft Development Training, suggested …