Data Science Commons^™

Feature Engineering Vs Feature Selection Vs Hyperparameter Optimization In The Spotify Song Popularity Dataset, Alan Cueva Mora, Brendan Tierney

Conference Papers

Research in Featuring Engineering has been part of the data pre-processing phase of machine learning projects for many years. It can be challenging for new people working with machine learning to understand its importance along with various approaches to find an optimized model. This work uses the Spotify Song Popularity dataset to compare and evaluate Feature Engineering, Feature Selection and Hyperparameter Optimization. The result of this work will demonstrate Feature Engineering has a greater effect on model efficiency when compared to the alternative approaches.

Crest Or Trough? How Research Libraries Used Emerging Technologies To Survive The Pandemic, So Far, Scout Calvert

University of Nebraska-Lincoln Libraries: Faculty Publications

Introduction

In the first months of the COVID-19 pandemic, it was impossible to tell if we were at the crest of a wave of new transmissions, or a trough of a much larger wave, still yet to peak. As of this writing, as colleges and universities prepare for mostly in-person fall 2021 semesters, case counts in the United States are increasing again after a decline that coincided with easier access to the COVID vaccine. Plans for a return to campus made with confidence this spring may be in doubt, as we climb the curve of what is already the second …

The Classification Of Basket Neural Cells In The Mammalian Neocortex, Sreya Pudi

Senior Theses

Basket neuronal cells of the mammalian neocortex have been classically categorized into two or more groups. Originally, it was thought that the large and small types are the naturally occurring groups that emerge from reasons that relate to neurobiological function and anatomical position. Later, a study based on anatomical and physiological features of these neurons introduced a third type, the net basket cell which is intermediate in size as compared to the large and small types. In this study, multivariate analysis was used to test the hypothesis that the large and small types are morphologically distinct groups. The results of …

The Labyrinth Of Data Collection For Humanitarian Project Funding And Implementation, Maria Alejandra Pulido

Independent Study Project (ISP) Collection

My research concentrates on four NGOs: IOM, IDMC, JIPS, and OCHA which use different tools to collect data and translate the information into evidence for data-driven decision making (DDDM) for the implementation of humanitarian assistance projects. I focus on the importance, advantages, and various data collection tools which help ameliorate the humanitarian sector since it does not have a current professionalized path to enter the workforce. I incorporated four interviews, attended two conferences and analyzed multiple online sources during my project.

Science Is For Everybody: A Resource For Understanding Glaciers, Climate, And Modeling, Emma Watson

Independent Study Project (ISP) Collection

Climate change threatens the existence of glaciers worldwide. In order to properly interact with these changing systems, we must first understand them. Glacial models provide an excellent way to do this; however, the language and mathematical concepts used in their creation is generally inaccessible to a common audience. This project presents an online resource for a general audience to interact with climate science, glaciology, and glacial modeling. Long term goals for the project include the incorporation of a glacial model of Drangajökull, Vestfirðir, NW Iceland. As such, focus for the project includes a literature review of glaciers, Drangajökull in particular, …

Identification Of Factors Associated With Fume Events Using Text Mining And Data Mining Methods, Mary B. O'Connor

Doctoral Dissertations and Master's Theses

Pilots, flight attendants, and passengers can be exposed to toxic compounds when the bleed air that supplies the cabin and flight deck is contaminated with pyrolyzed hydraulic fluid or oil from turbine jet engines. These fume events occur sporadically and can result in acute or chronic exposure in air crews and can have catastrophic consequences if flight crew members become impaired or incapacitated. The purpose of this research was to explore unstructured textual data and identify important factors associated with these events. Models using machine learning algorithms were developed and tested using variables gleaned from the text mining process and …

Towards Source-Aligned Variational Models For Cross-Domain Recommendation, Aghiles Salah, Thanh-Binh Tran, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Data sparsity is a long-standing challenge in recommender systems. Among existing approaches to alleviate this problem, cross-domain recommendation consists in leveraging knowledge from a source domain or category (e.g., Movies) to improve item recommendation in a target domain (e.g., Books). In this work, we advocate a probabilistic approach to cross-domain recommendation and rely on variational autoencoders (VAEs) as our latent variable models. More precisely, we assume that we have access to a VAE trained on the source domain that we seek to leverage to improve preference modeling in the target domain. To this end, we propose a model which learns …

Data Analysis Of The “2021 Covid, Equity And Social Justice Showcase”, Cristo Leon, James Lipuma

STEM Month

During the “2021 STEM for All Video Showcase” (NSF, 2021) funded by the National Science Foundation, 287 short videos showcasing federally funded projects aimed at improving STEM and CS education were presented.

The videos highlight strategies to engage students during COVID-19 and address educational inequities.

Deep Fakes: The Algorithms That Create And Detect Them And The National Security Risks They Pose, Nick Dunard

James Madison Undergraduate Research Journal (JMURJ)

The dissemination of deep fakes for nefarious purposes poses significant national security risks to the United States, requiring an urgent development of technologies to detect their use and strategies to mitigate their effects. Deep fakes are images and videos created by or with the assistance of AI algorithms in which a person’s likeness, actions, or words have been replaced by someone else’s to deceive an audience. Often created with the help of generative adversarial networks, deep fakes can be used to blackmail, harass, exploit, and intimidate individuals and businesses; in large-scale disinformation campaigns, they can incite political tensions around the …

Infer: An R Package For Tidyverse-Friendly Statistical Inference, Simon P. Couch, Andrew P. Bray, Chester Ismay, Evgeni Chasnovski, B. Baumer, Mine Cetinkaya-Rundel

Statistical and Data Sciences: Faculty Publications

infer implements an expressive grammar to perform statistical inference that adheres to the tidyverse design framework (Wickham et al., 2019). Rather than providing methods for specific statistical tests, this package consolidates the principles that are shared among common hypothesis tests and confidence intervals into a set of four main verbs (functions), supplemented with many utilities to visualize and extract value from their outputs.

The Concurrence Of Dna Methylation And Demethylation Is Associated With Transcription Regulation, Jiejun Shi, Jianfeng Xu, Yiling Elaine Chen, Jason Sheng Li, Ya Cui, Lanlan Shen, Jingyi Jessica Li, Wei Li

Children’s Nutrition Research Center Staff Publications

The mammalian DNA methylome is formed by two antagonizing processes, methylation by DNA methyltransferases (DNMT) and demethylation by ten-eleven translocation (TET) dioxygenases. Although the dynamics of either methylation or demethylation have been intensively studied in the past decade, the direct effects of their interaction on gene expression remain elusive. Here, we quantify the concurrence of DNA methylation and demethylation by the percentage of unmethylated CpGs within a partially methylated read from bisulfite sequencing. After verifying 'methylation concurrence' by its strong association with the co-localization of DNMT and TET enzymes, we observe that methylation concurrence is strongly correlated with gene expression. …

Comprehensive Characterization Of Covid-19 Patients With Repeatedly Positive Sars-Cov-2 Tests Using A Large Us Electronic Health Record Database, Rebecca Stern, David M Aronoff, Hua Xu, Loren Lipworth

Faculty, Staff and Student Publications

In the absence of genome sequencing, two positive molecular tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) separated by negative tests, prolonged time, and symptom resolution remain the best surrogate measure of possible reinfection. Using a large electronic health record database, we characterized clinical and testing data for 23 patients with repeatedly positive SARS-CoV-2 PCR test results ≥60 days apart, separated by ≥2 consecutive negative test results. The prevalence of chronic medical conditions, symptoms, and severe outcomes related to coronavirus disease 19 (COVID-19) illness were ascertained. The median age of patients was 64.5 years, 40% were Black, and 39% …

Estimation Of Conditional Power For Cluster-Randomized Trials With Interval-Censored Endpoints, Kaitlyn Cook, Rui Wang

Statistical and Data Sciences: Faculty Publications

Cluster-randomized trials (CRTs) of infectious disease preventions often yield correlated, interval-censored data: dependencies may exist between observations from the same cluster, and event occurrence may be assessed only at intermittent study visits. This data structure must be accounted for when conducting interim monitoring and futility assessment for CRTs. In this article, we propose a flexible framework for conditional power estimation when outcomes are correlated and interval-censored. Under the assumption that the survival times follow a shared frailty model, we first characterize the correspondence between the marginal and cluster-conditional survival functions, and then use this relationship to semiparametrically estimate the cluster-specific …

Piecewise Linear Manifold Clustering, Artyom Diky

Dissertations, Theses, and Capstone Projects

This work studies the application of topological analysis to non-linear manifold clustering. A novel method, that exploits the data clustering structure, allows to generate a topological representation of the point dataset. An analysis of topological construction under different simulated conditions is performed to explore the capabilities and limitations of the method, and demonstrated statistically significant improvements in performance. Furthermore, we introduce a new information-theoretical validation measure for clustering, that exploits geometrical properties of clusters to estimate clustering compressibility, for evaluation of the clustering goodness-of-fit without any prior information about true class assignments. We show how the new validation measure, when …

Making Space For Unquantifiable Data: Hand-Drawn Data Visualization, Eva Sibinga

Dissertations, Theses, and Capstone Projects

This project makes space for personal “data” around labor and care, prompting users to consider the concrete and abstract (quantifiable and unquantifiable) forms labor and care take in their lives. The interactive, subjective data visualization uses hand-drawn visual elements to foreground that data about care and human interaction will always be ambiguous and complex, that they may never be satisfactorily or universally quantified, and that they will always be out of reach of perfect categorization.

The project provides an alternative to prescriptive truth-telling with data. Instead of using a dataset to provide data-driven answers and insights to users, the interactive …

Detecting Stance On Covid-19 Vaccine In A Polarized Media, Rodica Ceslov

Dissertations, Theses, and Capstone Projects

The growing polarization in the United States has been widely reported. Media coverage plays an important role in shaping public opinion and influences public debates on complex and unfamiliar topics. There are some benefits to individuals and society from political polarization and conflict between opposing viewpoints. However, recent research has primarily highlighted the negative consequences of polarization which reached an all-time high. One such topic is the Covid-19 vaccine which was developed in record time, and the public learned about its safety and possible risks through the media coverage.

In this capstone, we examine U.S. news media coverage on the …

Anti-Vaxxers: Parents Fighting Science, Katie West

Symposium of Student Scholars

Immunizing children helps protect the health of our community, especially those people who cannot be immunized. Yet, since 1996 after a study was released that linked autism to vaccinations, there has been a trend of parents refusing to vaccinate their children. What are the demographics of the parents who believe their children are better off without vaccines? By knowing where these parents live and what decisions they make for their children’s education, counties and medical professionals can provide education and address their concerns.

My research involves data on 116,141 kindergarten classes from 2000-2015 in California. The two vaccine exemption options …

Opioid Abuse: Are Doctors Creating The Problem?, Nguyen Tran

Symposium of Student Scholars

Opioid abuse and overdose are serious health problems in the United States. Current research has concentrated on the treatment and prevention of opioid abuse. Using data from the Controlled Substance Utilization Review and Evaluation System (CURES) for California zip codes, my research focuses on the causes of opioid overdose by considering the relationships between the following variables within each zip code: population size, average number of prescriptions per doctor, percentage of people who receive opioid prescriptions, percentage of people receiving the same prescription drug from 3 or more doctors, average number of opioid pills per prescription and number of people …

Market Research: How To Keep And Gain Customers, Chris Mccall

Symposium of Student Scholars

Customer-centered market research is essential to the creation and management of successful marketing campaigns. A company that understands their customers will be able to provide those customers with products and services that fit their needs better than the competition, and ultimately increase profits. My research focuses on a database containing customer information for a telecommunications company called Telco. Within this research, I will focus on a number of customer attributes including demographics, services provided, payment methods, contract lengths, monthly charges, and tenure with the company. Considering how these attributes relate to one another will give me a better understanding of …

Food Deserts: Hungry For Answers, Lawren Cumberbatch

Symposium of Student Scholars

In 2010, the United States Department of Agriculture (USDA) reported that 23.5 million people in the United States live in food deserts. As defined by the USDA, a “food desert” is a neighborhood that lacks healthy food sources. This can be measured by distance to a store, number of stores in an area, individual-level resources such as family income or vehicle availability, and neighborhood-level resources such as availability of public transportation. Past research provides evidence that food deserts are especially likely to occur in communities heavily populated by minorities. As a Black Indian pre-med student aiming to join the world …