Categorical Data Analysis Commons^™

Bubble Stream Production By Belugas (Delphinapterus Leucas), Megan Slack

Theses

Bubble stream production in belugas has been poorly characterized and its function is not well understood. I examined behavioral states when producing bubble streams (“bubbling”), and when bubbling calls, to determine whether bubbling was significantly associated with a particular call category or behavioral state. Using 19 hours of video and audio recordings collected over a two-day period, I quantified bubble streams of a 4-month old calf and an unrelated adult female housed together. Based on the overall activity budgets and pool of vocalizations for both animals, I calculated the expected counts of bubble streams with and without vocalizations, assuming that …

Efvs Effects On Pilot Performance, Michael Campbell, Nsikak Udo-Imeh, Steven J. Landry

The Summer Undergraduate Research Fellowship (SURF) Symposium

Flight tests have been conducted at Purdue University using a computer-based flying simulator in an attempt to determine and measure the effects of Enhanced Flight Vision Systems (EFVS) on the performance of pilots during landing. Knowledge of these effects could help guide future design and implementation of EFVS in modern commercial aircraft, and further increase pilots’ ability to control the aircraft in low-visibility conditions. The problem that has faced researchers in the past has revolved around the difficulty in interpreting the data which is generated by these tests. The difficulty in making a generalized conclusion based on the large amount …

Generalized Non-Inferential Approach To Modeling Restricted Discrete Choice For The Case Of The Spatial Random Utility, Elena Labzina

Arts & Sciences Electronic Theses and Dissertations

Multinomial logistic regression model (MNL) is a powerful and easily tractable way for measuring the probabilistic impact of input variables on individual categorical choices. Crucially, the standard MNL assumes that all subjects of the study have the same choice sets. In the meanwhile, especially in political science and economics, this condition is frequently violated. Probably, the most graphical example of varying choice sets (VCS) is partially contested elections. Furthermore, the MNL implicitly implies the Independence of the Irregular Alternatives (IIA) assumption by requiring i.i.d errors that contrasts the MNL and the multinomial probit (MNP) and mixed logit (MXL) models. In …

Pretrial Release And Failure-To-Appear In Mclean County, Il, Jonathan Monsma

Stevenson Center for Community and Economic Development—Student Research

Actuarial risk assessment tools increasingly have been employed in jurisdictions across the U.S. to assist courts in the decision of whether someone charged with a crime should be detained or released prior to their trial. These tools should be continually monitored and researched by independent 3^rd parties to ensure that these powerful tools are being administered properly and used in the most proficient way as to provide socially optimal results. McLean County, Illinois began using the Public Safety Assessment-Court^TM (PSA-Court or simply PSA) risk assessment tool beginning in 2016. This study culls data from the McLean County Jail …

Data Center Application Security: Lateral Movement Detection Of Malware Using Behavioral Models, Harinder Pal Singh Bhasin, Elizabeth Ramsdell, Albert Alva, Rajiv Sreedhar, Medha Bhadkamkar

SMU Data Science Review

Data center security traditionally is implemented at the external network access points, i.e., the perimeter of the data center network, and focuses on preventing malicious software from entering the data center. However, these defenses do not cover all possible entry points for malicious software, and they are not 100% effective at preventing infiltration through the connection points. Therefore, security is required within the data center to detect malicious software activity including its lateral movement within the data center. In this paper, we present a machine learning-based network traffic analysis approach to detect the lateral movement of malicious software within the …

Predicting Game Day Outcomes In National Football League Games, Josh Klein, Anna Frowein, Chris Irwin

SMU Data Science Review

In this paper, we present a model for predicting the game day outcomes of National Football League games. 3 of the most popular sources for game day predictions are analyzed for comparison. Player data and outcomes from previous games are used, but we also incorporate several weather factors into our models. Over 1,700 games were incorporated and 3 separate models are created using simple regression, principal component analysis, and a recursive model. We also discuss the ethicality of using data science techniques by individuals with the knowledge in order to gain an advantage over a population lacking this specialized training.

Regression Analysis For Ordinal Outcomes In Matched Study Design: Applications To Alzheimer's Disease Studies, Elizabeth Austin

Masters Theses

Alzheimer's Disease (AD) affects nearly 5.4 million Americans as of 2016 and is the most common form of dementia. The disease is characterized by the presence of neurofibrillary tangles and amyloid plaques [1]. The amount of plaques are measured by Braak stage, post-mortem. It is known that AD is positively associated with hypercholesterolemia [16]. As statins are the most widely used cholesterol-lowering drug, there may be associations between statin use and AD. We hypothesize that those who use statins, specifically lipophilic statins, are more likely to have a low Braak stage in post-mortem analysis.

In order to address this hypothesis, …

Australian Herring And West Australian Salmon Scientific Workshop Report, October 2017, Department Of Primary Industries And Regional Development, Western Australia

Fisheries research reports

No abstract provided.

Examining Multimorbidities Using Association Rule Learning, Kaylee Dudley

Undergraduate Honors Theses

All insurance companies, regardless of the kind of insurance they offer, do their best to predict the future by comparing current to historical information. Any statistically significant correlation, regardless of expectations and hidden factors, can help to actuarially model future behavior. Using deidentified data from over 6 million health insurance policies over one year, we looked for any significant groupings of medical issues. The medical issues are defined based on the commercial “Episode Treatment Groups” (ETGs) classification, and our claims contain 347 different ETGs. We performed different kinds of analysis, including Bayesian posterior cluster analysis, k-means cluster analysis, and association …

Resistance To Peer Influence Moderates The Relationship Between Perceived (But Not Actual) Peer Norms And Binge Drinking In A College Student Social Network, Graham T. Diguiseppi, Matthew K. Meisel, Sara G. Balestrieri, Miles Q. Ott, Melissa J. Cox, Melissa A. Clark, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Introduction: Adolescent and young adult binge drinking is strongly associated with perceived social norms and the drinking behavior that occurs within peer networks. The extent to which an individual is influenced by the behavior of others may depend upon that individual’s resistance to peer influence (RPI).

Methods: Students in their first semester of college (N = 1323; 54.7% female, 57% White, 15.1% Hispanic) reported on their own binge drinking, and the perceived binge drinking of up to 10 important peers in the first-year class. Using network autocorrelation models, we investigated cross-sectional relationships between participant’s binge drinking frequency and the perceived …

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …

Under The Influence, Leonardo Cavicchio

Honors Projects in Mathematics

The purpose of this Honors Capstone entitled Under the Influence is to assess the validity of claims concerning the possible influence of roommates on one another, concerning alcohol on college campuses. This will be done by examining data collected in a prior study conducted over a two-year period. This analysis will focus on how alcohol consumption changes in correlation with the personality factors of roommates over an extended period of time. This secondary analysis of de-identified data will focus on primary and secondary subquestions. The primary question that will be addressed with the data set collected from the University of …

A Convolutional Neural Network Model For Species Classification Of Camera Trap Images, Annie Casey

Mathematics Undergraduate Theses

The overall purpose of this study was to automate the manual process of tagging species found in camera trap images using machine learning. The basic design of this study was to implement a Convolutional Neural Network model in Python using the Keras and Tensorflow modules that learn to recognize patterns in images in order to classify what species is in a given image and to label it accordingly. Results of the analysis highlight the importance of a large sample size, the degree of accuracy according to various arguments in the model, effectiveness of multiple layers that include Max Pooling, and …

An Event- And Network-Level Analysis Of College Students’ Maximum Drinking Day, Matthew K. Meisel, Angelo M. Dibello, Sara G. Balestrieri, Miles Q. Ott, Graham T. Diguiseppi, Melissa A. Clark, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Background—Heavy episodic drinking is common among college students and remains a serious public health issue. Previous event-level research among college students has examined behaviors and individual-level characteristics that drive consumption and related consequences but often ignores the social network of people with whom these heavy drinking episodes occur. The main aim of the current study was to investigate the network of social connections between drinkers on their heaviest drinking occasions.

Methods—Sociocentric network methods were used to collect information from individuals in the first-year class (N=1342) at one university. Past-month drinkers (N=972) reported on the characteristics of their heaviest drinking occasion …

Satellite Communications In The V And W Band: Tropospheric Effects, Bertus A. Shelters

Theses and Dissertations

An investigation into the use of Weather Cubes compiled by the atmospheric characterization package, Laser Environmental Effects Definition and Reference (LEEDR), to develop accurate, long-term attenuation statistics for link-budget analysis is presented. A Weather Cube is a three-dimensional mesh of numerical weather prediction (NWP) data plus LEEDR calculations that allows for the quantification of rain, cloud, aerosol, and molecular effects at any UV to RF wavelength on any path contained within the cube. The development of this methodology is motivated by the potential use of V (40-75 GHz) and W (75-110 GHz) band frequencies for the satellite communication application, as …

Default Priors For The Intercept Parameter In Logistic Regressions, Philip S. Boonstra, Ryan P. Barbaro, Ananda Sen

The University of Michigan Department of Biostatistics Working Paper Series

In logistic regression, separation refers to the situation in which a linear combination of predictors perfectly discriminates the binary outcome. Because finite-valued maximum likelihood parameter estimates do not exist under separation, Bayesian regressions with informative shrinkage of the regression coefficients offer a suitable alternative. Little focus has been given on whether and how to shrink the intercept parameter. Based upon classical studies of separation, we argue that efficiency in estimating regression coefficients may vary with the intercept prior. We adapt alternative prior distributions for the intercept that downweight implausibly extreme regions of the parameter space rendering less sensitivity to separation. …

Building A Better Risk Prevention Model, Steven Hornyak

National Youth Advocacy and Resilience Conference

This presentation chronicles the work of Houston County Schools in developing a risk prevention model built on more than ten years of longitudinal student data. In its second year of implementation, Houston At-Risk Profiles (HARP), has proven effective in identifying those students most in need of support and linking them to interventions and supports that lead to improved outcomes and significantly reduces the risk of failure.

Exploring Quantitative Timed Up And Go Sensor Data With Statistical Learning Techniques, Anthony Wright

Major Papers

Injuries and hospitalizations due to accidental falls among seniors represent a major expense for the Canadian public health system. It is highly desirable to be able to predict risk of falls for senior individuals in order to place them in prevention programs. Recently, sensor technologies have been used to predict risk of falls and levels of frailty of individuals. A commonly used test for assessing risk of falls is known as QTUG (Quantitative `Timed Up and Go'). The QTUG data often consist of a small set of survey answers about the individuals' historic variables (e.g., number of falls in the …

Building Connected Communities: Halton, Burlington – 2016 Census Older Immigrants, Sheridan Centre For Elder Research

Data Sheets

This data sheet provides a picture of the available relevant characteristics of the community at the time of the census (2016). We have included data both from those individuals over the age of 65 at the time of the census, as well as those who are in the age cohort just below (50 – 64), so those engaged in planning for future community needs can anticipate where growth or reduction in needs may be.

These numbers may be used to provide an overall picture of the municipality or region as a whole, and may be used to help guide municipality/region-wide …

Building Connected Communities: Halton – 2016 Census Older Immigrants, Sheridan Centre For Elder Research

Data Sheets

This data sheet provides a picture of the available relevant characteristics of the community at the time of the census (2016). We have included data both from those individuals over the age of 65 at the time of the census, as well as those who are in the age cohort just below (50 – 64), so those engaged in planning for future community needs can anticipate where growth or reduction in needs may be.

These numbers may be used to provide an overall picture of the municipality or region as a whole, and may be used to help guide municipality/region-wide …