Data Science Commons^™

Assessing And Forecasting Chlorophyll Abundances In Minnesota Lake Using Remote Sensing And Statistical Approaches, Ben Von Korff

All Graduate Theses, Dissertations, and Other Capstone Projects

Harmful algae blooms (HABs) can negatively impact water quality, lake aesthetics, and can harm human and animal health. However, monitoring for HABs is rare in Minnesota. Detecting blooms which can vary spatially and may only be present briefly is challenging, so expanding monitoring in Minnesota would require the use of new and cost efficient technologies. Unmanned aerial vehicles (UAVs) were used for bloom mapping using RGB and near-infrared imagery. Real time monitoring was conducted in Bass Lake, in Faribault County, MN using trail cameras. Time series forecasting was conducted with high frequency chlorophyll-a data from a water quality sonde. Normalized …

Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman

Pitzer Senior Theses

This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white …

"Who Can Help Me?'': Knowledge Infused Matching Of Support Seekers And Support Providers During Covid-19 On Reddit, Manas Gaur, Kaushik Roy, Aditya Sharma, Biplav Srivastava, Amit Sheth

Publications

During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs). Currently, knowledgeable human moderators match an SS with a user with relevant experience, i.e, an SP on these subreddits. This unscalable process defers timely care. We present a medical knowledge-infused approach to efficient matching of SS and SPs validated by experts for the users affected by anxiety and depression, in the context of with COVID-19. After matching, each SP to …

Uncovering Object Categories In Infant Views, Naiti S. Bhatt

Scripps Senior Theses

While adults recognize objects in a near-instant, infants must learn how to categorize the objects in their visual environments. Recent work has shown that egocentric head-mounted camera videos contain rich data that illuminate the infant experience (Clerkin et al., 2017; Franchak et al., 2011; Yoshida & Smith, 2008). While past work has focused on the social information in view, in this work, we aim to characterize the objects in infants’ at-home visual environments by modifying modern computer vision models for the infant view. To do so, we collected manual annotations of objects that infants seemed to be interacting within a …

Feature Investigation For Stock Returns Prediction Using Xgboost And Deep Learning Sentiment Classification, Seungho (Samuel) Lee

CMC Senior Theses

This paper attempts to quantify predictive power of social media sentiment and financial data in stock prediction by utilizing a comprehensive set of stock-related fundamental and technical variables and social media sentiments. For conducting sentiment analysis, this study employs a pretrained finBERT model that provides three different sentiment classifications and respective softmax scores. Hence, the significance of these variables is evaluated with XGBoost regression and Shapley Additive exPlanations (SHAP) frameworks. Through investigating feature importance, this study finds that statistical properties of sentiment variables provide a stronger predictive power than a weighted sentiment score and that it is possible to quantify …

A Global Ecological Classification Of Coastal Segment Units To Complement Marine Biodiversity Observation Network Assessments, Roger Sayre, Kevin Butler, Keith Van Graafeiland, Sean Breyer, Dawn Wright, Charlie Frye, Deniz Karagulle, Madeline Martin, Jill Cress, Tom Allen, Rebecca J. Allee, Rost Parsons, Bjorn Nyberg, Mark J. Costello, Peter Harris, Frank E. Muller-Karger

Political Science & Geography Faculty Publications

A new data layer provides Coastal and Marine Ecological Classification Standard (CMECS) labels for global coastal segments at 1 km or shorter resolution. These characteristics are summarized for six US Marine Biodiversity Observation Network (MBON) sites and one MBON Pole to Pole of the Americas site in Argentina. The global coastlines CMECS classifications were produced from a partitioning of a 30 m Landsat-derived shoreline vector that was segmented into 4 million 1 km or shorter segments. Each segment was attributed with values from 10 variables that represent the ecological settings in which the coastline occurs, including properties of the adjacent …

Ensemble Encoder-Decoder Models For Predicting Land Transformation, Pariya Pourmohammadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In studying dynamic and complex processes which are influenced by a system of inter-connected driving variables, it is crucial to apply models that can learn the complexity of the interactions. Land transformation is one of such complex processes, prediction of which can help to mitigate severe climate situations and improve the resiliency of communities. In this study, a multi-spectral set of data cubes is used to capture various characteristics of a geographic region. Based on the data cube, a feature space is constructed using socio-economic attributes, terrain characteristics, and landscape traits of the study region. Two-dimensional and three-dimensional convolutional neural …

Why We Need Better Corporate Governance Data, Jens Frankenreiter, Cathy Hwang, Yaron Nili, Eric L. Talley

Scholarship@WashULaw

Three decades of finance, economics, and legal studies in corporate governance have been built substantially on data sets with nearly unknown provenance. A new paper sets to correct this fatal flaw of contemporary corporate governance research by debuting a brand new resource—the Cleaning Corporate Governance database.

Research Data Curation And Management Bibliography, Charles W. Bailey Jr.

Copyright, Fair Use, Scholarly Communication, etc.

Preface

The Research Data Curation and Management Bibliography includes over 800 selected English-language articles and books that are useful in understanding the curation of digital research data in academic and other research institutions.

The "digital curation" concept is still evolving. In "Digital Curation and Trusted Repositories: Steps toward Success," Christopher A. Lee and Helen R. Tibbo define digital curation as follows:

Digital curation involves selection and appraisal by creators and archivists; evolving provision of intellectual access; redundant storage; data transformations; and, for some materials, a commitment to long-term preservation. Digital curation is stewardship that provides for the reproducibility and re-use …

Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic triggered a large-scale work-from-home trend globally in recent months. In this paper, we study the phenomenon of “work-from-home” (WFH) by performing social listening. We propose an analytics pipeline designed to crawl social media data and perform text mining analyzes on textual data from tweets scrapped based on hashtags related to WFH in COVID-19 situation. We apply text mining and NLP techniques to analyze the tweets for extracting the WFH themes and sentiments (positive and negative). Our Twitter theme analysis adds further value by summarizing the common key topics, allowing employers to gain more insights on areas of …

A Transdisciplinary Analysis Of Just Transition Pathways To 100% Renewable Electricity, Adewale Aremu Adesanya

Dissertations, Master's Theses and Master's Reports

The transition to using clean, affordable, and reliable electrical energy is critical for enhancing human opportunities and capabilities. In the United States, many states and localities are engaging in this transition despite the lack of ambitious federal policy support. This research builds on the theoretical framework of the multilevel perspective (MLP) of sociotechnical transitions as well as the concept of energy justice to investigate potential pathways to 100 percent renewable energy (RE) for electricity provision in the U.S. This research seeks to answer the question: what are the technical, policy, and perceptual pathways, barriers, and opportunities for just transition to …

Introduction To Data Science Lti 110, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Introduction To Data Science, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Spatial Frequency Implications For Global And Local Processing In Autistic Children, Riya Mody, Ayra Tusneem, Louanne Boyd, Vincent Berardi

Student Scholar Symposium Abstracts and Posters

Visual processing in humans is done by integrating and updating multiple streams of global and local sensory input. Interaction between these two systems can be disrupted in individuals with ASD and other learning disabilities. When this integration is not done smoothly, it becomes difficult to see the “big picture”, which has been found to have implications on emotion recognition, social skills, and conversation skills. An example of this phenomenon is local interference, which is when local details are prioritized over the global features. Previous research in this field has aimed to decrease local interference by developing and evaluating a filter …

Factors Affecting Computer Science Research Productivity And Impact In Nigeria: A Bibliometric Evidence, Azubuike Ezenwoke

Library Philosophy and Practice (e-journal)

Computer science is a burgeoning research field and has the potential to accelerate the rate of industrialisation and subsequently, economic development. Using bibliometric data obtained from Scopus, this study employed a 15-year bibliometric analysis to highlight Nigeria’s productivity and impact trends in the computer science research landscape. Our findings are summarised as follows: First, Nigeria’s computer science research contribution and citations are meager in comparison to the global output. Secondly, international collaboration is generally weak as most collaborations are national in scope. Third, Nigeria’s computer science-related research is published in low-quality outlets, as Scopus has discontinued the indexing of most …

Viral Data, Agnieszka Leszczynski, Matthew Zook

Geography Faculty Publications

We are experiencing a historical moment characterized by unprecedented conditions of virality: a viral pandemic, the viral diffusion of misinformation and conspiracy theories, the viral momentum of ongoing Hong Kong protests, and the viral spread of #BlackLivesMatter demonstrations and related efforts to defund policing. These co-articulations of crises, traumas, and virality both implicate and are implicated by big data practices occurring in a present that is pervasively mediated by data materialities, deeply rooted dataist ideologies that entrench processes of datafication as granting objective access to truth and attendant practices of tracking, data analytics, algorithmic prediction, and data-driven targeting of individuals …

An Analysis Of Technological Components In Relation To Privacy In A Smart City, Kayla Rutherford, Ben Lands, A. J. Stiles

James Madison Undergraduate Research Journal (JMURJ)

A smart city is an interconnection of technological components that store, process, and wirelessly transmit information to enhance the efficiency of applications and the individuals who use those applications. Over the course of the 21st century, it is expected that an overwhelming majority of the world’s population will live in urban areas and that the number of wireless devices will increase. The resulting increase in wireless data transmission means that the privacy of data will be increasingly at risk. This paper uses a holistic problem-solving approach to evaluate the security challenges posed by the technological components that make up a …

Lis Online Graduate Certificate In Data Science, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Using Data Analytics To Predict Students Score, Nang Laik Ma, Gim Hong Chua

Research Collection School Of Computing and Information Systems

Education is very important to Singapore, and the government has continued to invest heavily in our education system to become one of the world-class systems today. A strong foundation of Science, Technology, Engineering, and Mathematics (STEM) was what underpinned Singapore's development over the past 50 years. PISA is a triennial international survey that evaluates education systems worldwide by testing the skills and knowledge of 15-year-old students who are nearing the end of compulsory education. In this paper, the authors used the PISA data from 2012 and 2015 and developed machine learning techniques to predictive the students' scores and understand the …

Tapping Twitter Data For Analyzing And Visualizing Public Sentiments On Censorship, Naveen Kumar Yadav, Akhilesh K.S. Yadav

Library Philosophy and Practice (e-journal)

The main objective of this research study is to analyse and visualize Twitter data with tags “#Censorship”. A connection was established with twitter using Twitter API, and receiving the tweets on Google Spreadsheets. Data visualization was performed using various tools such as Voyant Tools, Tableau, Google Spreadsheet and Orange in order to generate different visualizations based upon, language, geographical areas, retweets etc. The sentiment analysis was performed for the sentiments that were attached to the given set of data by the public in their respective tweets. The 23680 tweets were retrieved during the data collection time and there were 13,771 …

Enhancing A Cluster-Based Tdma Mac Protocol For Vehicle-To-Vehicle Communications, Abubakar Bello Tambawal

Student Works (2020-2029)

Vehicular Ad hoc Network technology (VANET) is one of the emerging and promising wireless technology, providing support for vehicles to communicate and share resources, (such as safety messages) through vehicle-to-vehicle (V2V) communications. Sequel to that the Time Division Multiple Access (TDMA) MAC protocol using a cluster-based topology has been proposed by the research community. Most of the existing research works focused on the cluster head (CH) election with very few addressing other critical issues, including cluster formation, efficient time slot allocation, and cluster maintenance. These challenges result in an unstable cluster, which could affect the timely delivery of safety applications. …

Using Spatial Analysis And Machine Learning Techniques To Develop A Comprehensive Highway-Rail Grade Crossing Consolidation Model, Samira Soleimani

LSU Doctoral Dissertations

The safety of highway-railroad grade crossings (HRGC) is still an issue in the United States of America (USA). The grade crossing is where a railroad crosses a road at the same level without any over or underpass. To improve the safety of crossings, the crossings’ condition should be explored from several aspects such as engineering design (speed limit, warning signs, etc.), road condition (number of lanes, surface markings, etc.), rail design (the type of track, ballast, etc.), temporal variables (weather, visibility, time of day, lightning, etc.), social variables (population, race, etc.), and last but not least, spatial variables (the type …

Research In Data Science Dsp 599, Harrison Dekker

Library Impact Statements

No abstract provided.

Data Science Internship Dsp 477, Harrison Dekker

Library Impact Statements

No abstract provided.

Project In Data Science Dsp 499, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Removing Racially Biased Algorithms In Policing, Andie Lee

Student Papers in Public Policy

Local police departments use algorithm-based programs to do police work and predict crime. Technology has created the police tactic of predictive crime prevention. Police work, however, requires social skills, assessment of the environment, and most importantly human interaction. Automated policing lacks these characteristics. Moreover, the algorithms used to make crime predictions and risk assessments have disproportionately affected minorities.

The Case For Online Ranked-Choice Voting, Rayyan Khan

Student Papers in Public Policy

Maine was the first to embrace ranked-choice voting on a statewide level in 2018, using it for all state and general elections. Maine voters will be the first to use ranked-choice voting in a presidential election in 2020. This system differs from traditional voting in that voters rank candidates rather than choose just one. Supporters of ranked-choice voting tout it as a better model for accurately representing the values of the voting population; however, a study conducted in San Francisco details a potential shortfall referred to as “ballot fatigue” that the theoretically-ideal system may face as it struggles to deal …

The Most-Cited Articles In Data In Brief Journal: A Bibliometric Analysis Using Scopus Data, Lusiana Wulansari, Ansari Saleh Ahmar, Agus Rochmat, Nurmawati, Akbar Iskandar

Library Philosophy and Practice (e-journal)

Bibliometric analysis is one of the research approaches that utilizes quantitative and mathematical data to address problems posed in the context of visualization to see patterns in the field of science. In fact, bibliometric analysis may also include a wider overview of the names of the most influential writers in the area of science. This data analysis would discuss the most-cited articles in Data in Brief Journal including the countries, authors. The data was collected on 31st May 2020 of Scopus database. The literature review was conducted using the keyword: ISSN (2352-3409). The bibliometric analysis is visualized utilizing the VosViewer …

Blockchain Technology And Freight Forwarder Exploration Of Implications Focused On Practitioners In Shanghai, Johannes Van Bohemen

World Maritime University Dissertations

No abstract provided.

How Port Logistics Competitiveness Evolves Among Major Ports In China And Europe (1998-2018), Jiawei Wang

World Maritime University Dissertations

No abstract provided.