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Ethical Data Considerations For Engaging In Reparative Archival Practice, Jamie Rogers, Rhia Rae 2023 Florida International University

Ethical Data Considerations For Engaging In Reparative Archival Practice, Jamie Rogers, Rhia Rae

Works of the FIU Libraries

Archival textually-rich materials--such as warranty deeds, mortgages, legal documents, and letter correspondence--can provide valuable historical insights, and if transcribed and analyzed, can produce data points in the form of unstructured text, tabular data, and geospatial assets. This presentation will provide an overview of the process Florida International University librarians went through to turn the papers of Dana A. Dorsey, Miami's first Black Millionaire, into data. Their work is guided by the concept of "collections as data" as a form of reparative archival practice, enabling the elevation of marginalized individuals' histories. The goal of reparative archival practice is to create a …


Promoting Data Harmonization To Evaluate Vaccine Hesitancy In Lmics: Approach And Applications, Ryan Rego, Yuri Zhukov, Kyrani Reneau, Amy Pienta, Kristina L. Rice, Patrick Brady, Geoffrey Siwo, Peninah Wachira, Amina Abubakar, Ken Kollman 2023 University of Michigan, USA

Promoting Data Harmonization To Evaluate Vaccine Hesitancy In Lmics: Approach And Applications, Ryan Rego, Yuri Zhukov, Kyrani Reneau, Amy Pienta, Kristina L. Rice, Patrick Brady, Geoffrey Siwo, Peninah Wachira, Amina Abubakar, Ken Kollman

Institute for Human Development

Background: Factors influencing the health of populations are subjects of interdisciplinary study. However, datasets relevant to public health often lack interdisciplinary breath. It is difficult to combine data on health outcomes with datasets on potentially important contextual factors, like political violence or development, due to incompatible levels of geographic support; differing data formats and structures; differences in sampling procedures and wording; and the stability of temporal trends. We present a computational package to combine spatially misaligned datasets, and provide an illustrative analysis of multi-dimensional factors in health outcomes.

Methods: We rely on a new software toolkit, Sub-National Geospatial Data Archive …


Link Tank, 2023 DePaul University

Link Tank

DePaul Magazine

A new JD certificate program in information technology, cybersecurity and data privacy provides DePaul University students with proficiency in both law and tech.


A Dynamic Online Dashboard For Tracking The Performance Of Division 1 Basketball Athletic Performance, Erica Juliano, Chelsea Thakkar, Christopher B. Taber, Mehul S. Raval, Kaya Tolga, Samah Senbel 2023 Sacred Heart University

A Dynamic Online Dashboard For Tracking The Performance Of Division 1 Basketball Athletic Performance, Erica Juliano, Chelsea Thakkar, Christopher B. Taber, Mehul S. Raval, Kaya Tolga, Samah Senbel

School of Computer Science & Engineering Undergraduate Publications

Using Data Analytics is a vital part of sport performance enhancement. We collect data from the Division 1 'Women's basketball athletes and coaches at our university, for use in analysis and prediction. Several data sources are used daily and weekly: WHOOP straps, weekly surveys, polar straps, jump analysis, and training session information. In this paper, we present an online dashboard to visually present the data to the athletes and coaches. R shiny was used to develop the platform, with the data stored on the cloud for instant updates of the dashboard as the data becomes available. The performance of athletes …


Google Search Trends To Assess Public Interest In And Concern About Vuity For Treating Presbyopia, Taku Wakabayashi, Hana A. Mansour, Robert Abishek, Jayanth Sridhar, Michael N. Cohen, David Xu, Jordan Deaner, Yoshihiro Yonekawa, Jason Hsu, Ajay E. Kuriyan 2023 Thomas Jefferson University

Google Search Trends To Assess Public Interest In And Concern About Vuity For Treating Presbyopia, Taku Wakabayashi, Hana A. Mansour, Robert Abishek, Jayanth Sridhar, Michael N. Cohen, David Xu, Jordan Deaner, Yoshihiro Yonekawa, Jason Hsu, Ajay E. Kuriyan

Wills Eye Hospital Papers

PURPOSE: To assess public awareness, interest, and concerns regarding Vuity (1.25% pilocarpine hydrochloride ophthalmic solution), an eye drop for the treatment of presbyopia, based on Google Trends.

METHODS: We used Google Trends that provides a relative search volume for queried terms, to evaluate searches for Vuity from June 30, 2021, to June 30, 2022, in the United States. The data for this study were downloaded on June 30, 2022. Main outcome measures were changes in relative search volumes for the terms "Vuity," "Eye drops for reading," "Eye drops for near vision," "Presbyopia," "Pilocarpine," and related popular search terms, such as …


Modeling And Estimation Of A Continuous Flexible Structure Using The Theory Of Functional Connections, Riccardo Bevilacqua 2023 Embry-Riddle Aeronautical University

Modeling And Estimation Of A Continuous Flexible Structure Using The Theory Of Functional Connections, Riccardo Bevilacqua

Math Department Colloquium Series

This talk presents a novel method for modeling and estimating the dynamics of a continuous structure based on a limited number of noisy measurements. The goal is reached using a Kalman filter in synergy with the recently developed mathematical framework known as the Theory of Functional Connections (TFC). The TFC allows to derive a functional expression capable of representing the entire space of the functions that satisfy a given set of linear and, in some cases, nonlinear constraints. The proposed approach exploits the possibilities offered by the TFC to derive an approximated dynamical model for the flexible system using the …


Digital Economy Enables Chinese Path To Modernization, Ying LIU, Chaochun HUANG, Yongmiao HONG, Shouyang WANG 2023 School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China MOE Philosophy and Social Science Laboratory of Digital Economic Monitoring, Forecasting, Early Warning, and Policy Simulation(Cultivation), University of Chinese Academy of Sciences, Beijing 100190, China

Digital Economy Enables Chinese Path To Modernization, Ying Liu, Chaochun Huang, Yongmiao Hong, Shouyang Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Firstly, from the perspective of the internal consistency between the characteristics of Chinese path to modernization and the Internet spirit, this study reveals the importance of developing the digital economy for achieving Chinese path to modernization, and expounds the internal logic of digital economy enabling Chinese path to modernization. Then, it analyzes the challenges and problems faced by the construction of Chinese path to modernization from the aspects of the construction of basic scientific and technological capacity of digital economy, the coordination mechanism of data elements, the structural imbalance of digital development, governance system and security system. Finally, based on …


Fall Town Hall On Research Data Management, Megan Hurst, Christine Madsen, Kristi Thompson 2023 Athenaeum21

Fall Town Hall On Research Data Management, Megan Hurst, Christine Madsen, Kristi Thompson

Western Libraries Presentations

This Town Hall was held to share recommendations for Research Data Management at Western that result from a gap analysis to understand the RDM needs at Western, conducted by Athenaeum21, a strategy and technology consultancy engaged by Western for this work. The recommendations will inform the implementation of Western’s Research Data Management Strategy, which shapes Research Data Management at Western for all researchers, grant funded or not, student or faculty, regardless of discipline.


Local Model Agnostic Xai Methodologies Applied To Breast Cancer Malignancy Predictions, Heather Hartley 2023 Western University

Local Model Agnostic Xai Methodologies Applied To Breast Cancer Malignancy Predictions, Heather Hartley

Electronic Thesis and Dissertation Repository

This thesis examines current state-of-the-art Explainable Artificial Intelligence (XAI) methodologies applicable to breast cancer diagnostics, as well as local model-agnostic XAI methodologies more broadly. It is well known that AI is underutilized in healthcare due to the fact that black box AI methods are largely uninterpretable. The potential for AI to positively affect health care outcomes is massive, and AI adoption by medical practitioners and the community at large will translate to more desirable patient outcomes. The development of XAI is crucial to furthering the integration of AI within healthcare, as it will allow medical practitioners and regulatory bodies to …


Large-Scale Google Street View Images For Urban Change Detection, Fangzheng Lyu, Xinlin Ma, Yan Song, Eric Zhu, Shaowen Wang 2023 University of Illinois at Urbana-Champaign

Large-Scale Google Street View Images For Urban Change Detection, Fangzheng Lyu, Xinlin Ma, Yan Song, Eric Zhu, Shaowen Wang

I-GUIDE Forum

Urbanization has entered a new phase characterized by urban changes occurring at a micro-scale and “under the roof”, as opposed to external modifications. These changes, known as urban retrofitting, involve the incorporation of novel technologies or features into pre-existing systems to promote sustainability. Given the limitations of remote sensing images in identifying such urban changes, novel tools need to be developed for detecting urban retrofitting. In this study, we first build a pipeline to collect large-scale time-series urban street view images from Google Street View in Mecklenburg County, North Carolina. And we examine the feasibility of utilizing the acquired dataset …


Deep Q-Learning Framework For Quantitative Climate Change Adaptation Policy For Florida Road Network Due To Extreme Precipitation, Orhun Aydin 2023 Saint Louis University

Deep Q-Learning Framework For Quantitative Climate Change Adaptation Policy For Florida Road Network Due To Extreme Precipitation, Orhun Aydin

I-GUIDE Forum

Climate change-induced extreme weather and increasing population are increasing the pressure on the global aging road networks. Adaptation requires designing interventions and alterations to the road networks that consider future dynamics of flooding and increased traffic due to the growing population. This paper introduces a reinforcement learning approach to designing interventions for Florida's road network under future traffic and climate projections. Three climate models and a tide and surge model are used to create flooding and coastal inundation projections, respectively. The optimal sequence of decisions for adapting Florida's road network to minimize flooding-related disruptions is solved by using a graph-based …


Graph Transformer Network For Flood Forecasting With Heterogeneous Covariates, Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang, Giri Narasimhan 2023 Florida International University

Graph Transformer Network For Flood Forecasting With Heterogeneous Covariates, Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang, Giri Narasimhan

I-GUIDE Forum

Floods can be very destructive causing heavy damage to life, property, and livelihoods. Global climate change and the consequent sea-level rise have increased the occurrence of extreme weather events, resulting in elevated and frequent flood risk. Therefore, accurate and timely flood forecasting in coastal river systems is critical to facilitate good flood management. However, the computational tools currently used are either slow or inaccurate. In this paper, we propose a Flood prediction tool using Graph Transformer Network (FloodGTN) for river systems. More specifically, FloodGTN learns the spatio-temporal dependencies of water levels at different monitoring stations using Graph Neural Networks (GNNs) …


Solving Geospatial Problems Under Extreme Time Constraints: A Call For Inclusive Geocomputational Education, Coline C. Dony 2023 American Association of Geographers

Solving Geospatial Problems Under Extreme Time Constraints: A Call For Inclusive Geocomputational Education, Coline C. Dony

I-GUIDE Forum

To prepare our next generation to face geospatial problems that have extreme time constraints (e.g., disasters, climate change) we need to create educational pathways that help students develop their geocomputational thinking skills. First, educators are central in helping us create those pathways, therefore, we need to clearly convey to them why and in which contexts this thinking is necessary. For that purpose, a new definition for geocomputational thinking is suggested that makes it clear that this thinking is needed for geospatial problems that have extreme time constraints. Secondly, we can not further burden educators with more demands, rather we should …


Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian 2023 University of Minnesota - Twin Cities

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …


Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy 2023 California Polytechnic State University, San Luis Obispo

Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy

College of Engineering Summer Undergraduate Research Program

High-entropy alloys (HEA) are a very new development in the field of metallurgical materials. They are made up of multiple principle atoms unlike traditional alloys, which contributes to their high configurational entropy. The microstructure and properties of HEAs are are not well predicted with the models developed for more common engineering alloys, and there is not enough data available on HEAs to fully represent the complex behavior of these alloys. To that end, we explore how the use of machine learning models can be used to model the complex, high dimensional behavior in the HEA composition space. Based on our …


Dei: Exploring Academic Reflections Using Natural Language Processing To Create A Roadmap Of Student Success And Foster Inclusive Engineering Education, Rajvir H. Vyas, Nidhi Raviprasad 2023 California Polytechnic State University, San Luis Obispo

Dei: Exploring Academic Reflections Using Natural Language Processing To Create A Roadmap Of Student Success And Foster Inclusive Engineering Education, Rajvir H. Vyas, Nidhi Raviprasad

College of Engineering Summer Undergraduate Research Program

Every year, the College of Engineering (CENG) students and faculty reach out to admitted students through “Text-a-Thon” programs to answer their questions about being a student at Cal Poly. In order to improve CENG outreach efforts, we analyzed these text conversations to predict the likelihood of an admitted student accepting an offer of admission from Cal Poly. Through our research, we discovered key factors that play a role in a student committing to Cal Poly through data-based insights. Additionally, we successfully used a human-on-the-loop system to help create Machine Learning (ML) models that predict satisfaction of response by way of …


Cross-Scale Urban Land Cover Mapping: Empowering Classification Through Transfer Learning And Deep Learning Integration, Zhe Wang, Chao Fan, Xian Min, Shoukun Sun, Xiaogang Ma, Xiang Que 2023 University of Idaho

Cross-Scale Urban Land Cover Mapping: Empowering Classification Through Transfer Learning And Deep Learning Integration, Zhe Wang, Chao Fan, Xian Min, Shoukun Sun, Xiaogang Ma, Xiang Que

I-GUIDE Forum

Urban land cover mapping is essential for effective urban planning and resource management. Thanks to its ability to extract intricate features from urban datasets, deep learning has emerged as a powerful technique for urban classification. The U-net architecture has achieved state-of-the-art land cover classification performance, highlighting its potential for mapping urban trees at different spatial scales. However, deep learning approaches often require large, labeled datasets, which are challenging to acquire for specific urban contexts. Transfer learning addresses this limitation by leveraging pre-trained deep learning models on extensive datasets and adapting them to smaller urban datasets with limited labeled samples. Transfer …


Ethics And Social Justice For Ai In Data Science, Arya Ramchander, Kylene Nicole Landenberger 2023 California Polytechnic State University, San Luis Obispo

Ethics And Social Justice For Ai In Data Science, Arya Ramchander, Kylene Nicole Landenberger

College of Engineering Summer Undergraduate Research Program

The advances of AI raise several critical questions about human values and ethics, highlighting the need for researchers and developers to consider the ethical implications and the risks of neglecting them. In the past few years, student researchers have developed an AI model that allows users to test their surveys for possible breaches of subject confidentiality. This allows the users to gauge the ethicality of their proposal. This summer, we have expanded on this research and launched an interactive model for students and researches to assess their current work for ethical and social justice implications. Using Langchain and Figma, we …


Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook 2023 Embry-Riddle Aeronautical University

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …


Digital Scholarship And Data Science Intersect In Libraries: A Needs Assessment Report, Halie Kerns 2023 Binghamton University

Digital Scholarship And Data Science Intersect In Libraries: A Needs Assessment Report, Halie Kerns

Library Created Resources

The following report summarized the results of a needs assessment completed in the fall of 2023 at Binghamton University by the Libraries’ Digital Scholarship team. The aim was to understand how data science-focused programming, as part of the digital scholarship’s offerings, would be utilized on campus. The report evaluates existing literature, summarizes findings from twenty-eight interviews done across campus, and lays out an action plan for the Digital Scholarship team’s future planning.


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