Data Science Commons^™

Sticky Charters? The Surprisingly Tepid Embrace Of Officer-Protecting Waivers In Delaware, Jens Frankenreiter, Eric L. Talley

Scholarship@WashULaw

This article investigates the reaction to a much-heralded 2022 legal reform in Delaware that permitted a corporation’s charter to exculpate its officers from monetary exposure for breaching their fiduciary duty of care. To isolate reactions to this statutory reform, we make extensive use of generative AI tools to identify and interpret charter amendments that introduce officer-facing waivers. We find a surprisingly tepid rate of uptake among Delaware corporations through the end of the first post-reform year, notwithstanding widespread predictions that corporate entities would quickly storm the exculpation exits once permitted to do so.

Our study makes two contributions to the …

Beyond Binary: Revealing Variations In Islamophobic Content With Hierarchical Multi-Class Classification, Esraa Aldreabi, Khawlah M. Harahsheh, Mukul Dev Chhangani, Chung-Hao Chen, Jeremy Blackburn

Electrical & Computer Engineering Faculty Publications

In the digital age, the rise of Islamophobia-marked by an irrational fear or discrimination against Islam and Muslims-has emerged as a pressing issue, especially on social media platforms. In this paper we employs a multi-class classification system, moving beyond traditional binary models. We categorize Islamophobic content into three main classes and various subclasses, covering a range from subtle biases to explicit incitement. Comparative analysis of data from Reddit and Twitter illuminates the distinct prevalence and types of Islamophobic content specific to each platform. This paper deepens our understanding of digital Islamophobia and provides insights for crafting targeted online counter strategies. …

A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic

Electrical & Computer Engineering Faculty Publications

This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

Understaning Low Vision Graphical Perception Of Bar Charts, Yash Prakash, Akshay Kolgar Nayak, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Bar charts are widely used for their simplicity in data representation, prompting numerous studies to explore and model how users interact with and perceive bar chart information. However, these studies have predominantly focused on sighted users, with a few also targeting blind screen-reader users, whereas the graphical perception of low-vision screen magnifier users is still an uncharted research territory. We fill this knowledge gap in this paper by designing four experiments for a laboratory study with 25 low-vision participants to examine their graphical perception while interacting with bar charts. For our investigation, we built a custom screen magnifier-based logger that …

Quantification Of Landside Congestion In Ports: An Analysis Based On Gps Data, Kumushini Thennakoon, Namal Bandaranayake, Senevi Kiridena, Asela K. Kulatunga

Computer Science Faculty Publications

Hinterland transport is a critical segment in maritime cross-border logistics, which links the end-users of global supply chains to the maritime segment. Truck-based hinterland transport is known to cause congestion in and around ports. This study aimed to quantify the congestion caused by trucks at the Port of Colombo, which has not been a subject of a systematic study. To this end, the study makes use of GPS data. In addition to revealing heavy congestion within the port, the study also reveals significant variations in congestion during different times of the day with the duration of journeys peaking from 1200hrs …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

The Psychological Science Accelerator's Covid-19 Rapid-Response Dataset, Erin M. Buchanan, Andree Hartanto

Research Collection School of Social Sciences

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with …

Selecting Patient-Reported Outcome Measures For A Patient-Facing Technology, Priyank Raj, Youmin Cho, Yun Jiang, Yang Gong

Faculty, Staff and Student Publications

OBJECTIVE: This article provides insight into our process and considerations for selecting patient-reported outcome measures (PROMs) designed for self-reporting symptoms and quality-of-life among breast cancer (BCA) patients undergoing oral anticancer agent treatment via a patient-facing technology (PFT) platform.

METHODS: Following established guidelines, we conducted a thorough assessment of a specific set of PROMs, comparing their content to identify the most suitable options for studying BCA patients.

RESULTS: We recommend utilizing the combination of EORTC QLQ-C30 + EORTC QLQ-BR45 as the preferred instrument, especially when developing a dedicated "breast cancer-only" application.

DISCUSSION: When developing and maintaining a dashboard for a PFT …

Making Data Meaningful: Stakeholder Perceptions On Data Visualization And Data Management Practices Within A Multi-Tiered System Of Supports (Mtss), Domenick Saia

Dissertations

Data-driven decision-making and collaboration are core pillars of a multi-tiered system of supports (MTSS); however, timely and accessible data use, as well as data literacy and visualization literacy skills, are challenges school leaders and educators face related to implementing such frameworks. I hypothesized efficient data management systems and data visualization tools enable school teams to predict student learning outcomes, readily communicate, and better understand student data. The purpose of this study design was to highlight a need for more efficient data structures that allow school stakeholders to balance their roles within an MTSS framework more effectively. The context of this …

Critical Transitions In Mental Health: Van Gogh Case Study, Anna Singley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Modeling Of The Impact Of Lobbying On Climate Policy, Andrew Jacoby, Claire Hannah, James Hutchinson, Jasmine Narehood, Aditi Ghosh, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Economic Equity And People With Disabilities: Development And Characterization Of A Novel Index, Bhavneet Walia, Katherine Mcdonald, Joy Hammel, Lex Frieden, Michael Morris, Barry Whaley, Vinh Nguyen

Faculty, Staff and Student Publications

Here we develop two new social indices: The ADA PARC Absolute Economic Opportunity Index and the ADA PARC Relative Economic Opportunity Index. These indices allow us novel examinations of economic equity between people with and without disabilities within a U.S. State and between people with disabilities in different states using aggregations of multiple component economic indicators. These represent the first efforts to offer U.S. indices of this focus, an important development given the distinct economic needs of people with disabilities and the value in accounting for distinct national policies. The indices rely on U.S. Census and other data on economic …

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 …

Evaluating The Impact Of An Mhealth Platform For Managing Acute Postoperative Dental Pain: Randomized Controlled Trial, Bunmi Tokede, Alfa Yansane, Ana Ibarra-Noriega, Joanna Mullins, Kristen Simmons, Nicholas Skourtes, Urvi Mehta, Sayali Tungare, David Holmes, Joel White, Muhammad Walji, Elsbeth Kalenderian

Faculty, Staff and Student Publications

BACKGROUND: Postoperative dental pain is pervasive and can affect a patient's quality of life. Adopting a patient-centric approach to pain management involves having contemporaneous information about the patient's experience of pain and using it to personalize care.

OBJECTIVE: In this study, we evaluated the use of a mobile health (mHealth) platform to collect pain-related patient-reported outcomes over 7 days after the patients underwent pain-inducing dental procedures; we then relayed the information to the dentist and determined its impact on the patient's pain experience.

METHODS: The study used a cluster-randomized experimental study design with an intervention arm where patients were prompted …

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

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.

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 …

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

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 …

Environmental Loss, Displacement, And Anxiety In Portugal: Analyzing News Articles To Differentiate Manifestations Of Environmental Distress, Robin Greene

Independent Study Project (ISP) Collection

Expressions of environmental distress can take different forms, with different symptoms, causes, and treatments. Existing literature generally identifies three primary categories of environmental distress responses: environmental grief, solastalgia, and eco-anxiety. This paper explores these distinctions and identifies words typically associated with each category in Portuguese news articles using Latent Dirichlet Allocation (LDA). LDA is a Natural Language Processing (NLP) technique that groups words into topics and identifies connections between those words based on how often those words appear together in sequences. This paper uses a modified LDA algorithm called GuidedLDA to identify additional keywords within topics defined by a list …

Surveillance Systems In Western Kenya: Methods, Perceptions, And Effectiveness, Marissa Duffy

Independent Study Project (ISP) Collection

Surveillance is an important tool in monitoring and evaluating infectious disease patterns and trends. Surveillance is vital because it aids public health officials and medical professionals in creating better prevention methods and efficiently managing outbreaks. Kenya is home to many noncommunicable diseases making it an important location to conduct disease surveillance. Within Kenya, each county has its own surveillance unit which tracks and controls outbreaks. In addition, government run surveillance systems were established to determine disease burden, incidence, and patterns in specific at-risk communities around Kenya. One of these major surveillance systems is Population-Based Infectious Disease Surveillance (PBIDS) which has …

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.

Evolving Availability And Standardization Of Patient Attributes For Matching, Yu Deng, Lacey P Gleason, Adam Culbertson, Xiaotian Chen, Elmer V Bernstam, Theresa Cullen, Ramkiran Gouripeddi, Christopher Harle, David F Hesse, Jacob Kean, John Lee, Tanja Magoc, Daniella Meeker, Toan Ong, Jyotishman Pathak, Marc Rosenman, Laura K Rusie, Akash J Shah, Lizheng Shi, Aaron Thomas, William E Trick, Shaun Grannis, Abel Kho

Faculty, Staff and Student Publications

Variation in availability, format, and standardization of patient attributes across health care organizations impacts patient-matching performance. We report on the changing nature of patient-matching features available from 2010-2020 across diverse care settings. We asked 38 health care provider organizations about their current patient attribute data-collection practices. All sites collected name, date of birth (DOB), address, and phone number. Name, DOB, current address, social security number (SSN), sex, and phone number were most commonly used for cross-provider patient matching. Electronic health record queries for a subset of 20 participating sites revealed that DOB, first name, last name, city, and postal codes …

Balanced Blended Space: Proposing A Universal Theoretical Framework For Combinative Reality, David Smith, Frederick Bianchi

Publications and Research

In today's fragmented societies, a unified framework for communication and collaboration across different realities is crucial. We introduce Balanced Blended Space (BBS) as a framework for describing combinative reality, encompassing virtual, physical, and conceptual realms, all intrinsically connected. Interactions within these environments shape our perceptual space. This paper outlines key axiomatic assumptions, criteria for a universal framework, and fundamental terminology. We identify deep symmetries enabling the BBS framework, including Cognitive and Computational Symmetry, Physical and Virtual Symmetry, Mediation Pathway Symmetry, Space-Time Symmetry, and Sensory Symmetry. We propose tests to determine its viability, emphasizing virtual intelligence as a collaborative partner. We …

Research Data Management In The Canadian Context: A Guide For Practitioners And Learners, Kristi Thompson, Elizabeth T. Hill, Emily Carlisle-Johnston, Danielle Dennie, Émilie Fortin

Western Libraries Publications

Research Data Management is a term for all the things that researchers do to structure, organize and maintain data before, during and after doing research. RDM is also an emerging discipline that is concerned with researching and developing ways to manage research data more effectively. But what is research data? Where is the push towards formal Research Data Management coming from? What are the requirements of good data management? Research Data Management in the Canadian Context: A Guide for Practitioners and Learners looks at these questions and more, all with a focus on Canadian guidelines, regulations and infrastructure.

On Digital Productivity Base Of Policies For Cross-Border Data Flows Between Rcep Parties And Its Influences—Taking Digital Integration Index As A Reference, Gui Huang, Ru Tao

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study reviews the newest legislation and policies of Regional Comprehensive Economic Partnership (RCEP) participating countries on cross-border data flow, and then categorized them according to the ban on data transfer, local storage of data, permission-based regulation, and standards-based regulation. By referring to the indexes in the ASEAN Digital Integration Index, the subject and object factors of digital productivity in RCEP parities are sorted out, as well as the status quo of digital economy. Through the introduction of data value chain theory, the decisive impact of digital productivity factors on the policy formulation of cross-border data flow is expounded; by …

Paradigm Review Of Data Localization In India And Its Implications For China, Ying Fan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Data localization is a focal point of global data governance and its impact on global data governance is no longer confined to a single country. Over the years, India has followed a unique policy framework in terms of cross-border data flows and data localization, and its insistence on data sovereignty reflects its position in the international arena. This study uses the Indian data localization paradigm as a research base to discuss the common phenomenon of disconnect between policy motivations and practical effects of data localization, and as an entry point to introduce the latest Indian research findings in this area. …

Research On Multi-Source Heterogeneous Big Data Fusion Based On Wsr, Aihua Li, Weijia Xu, Yong Shi

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the era of multi-source heterogeneous big data, big data presents new features such as cross, diversity and variability. The applications of big data in a wider range of fields have new requirements for data fusion. Under this background, the connotation of data fusion is enriched and expanded. The generalized data fusion includes the fusion of data resources, the fusion of model methods, and the fusion of decision-makers' knowledge and experience. This study analyzes the characteristics of multi-source heterogeneous data fusion at three different fusion levels: data level, information level and decision level, and discusses challenges for data fusion in …

Using Geographic Information To Explore Player-Specific Movement And Its Effects On Play Success In The Nfl, Hayley Horn, Eric Laigaie, Alexander Lopez, Shravan Reddy

SMU Data Science Review

American Football is a billion-dollar industry in the United States. The analytical aspect of the sport is an ever-growing domain, with open-source competitions like the NFL Big Data Bowl accelerating this growth. With the amount of player movement during each play, tracking data can prove valuable in many areas of football analytics. While concussion detection, catch recognition, and completion percentage prediction are all existing use cases for this data, player-specific movement attributes, such as speed and agility, may be helpful in predicting play success. This research calculates player-specific speed and agility attributes from tracking data and supplements them with descriptive …