Social and Behavioral Sciences Commons^™

Rhetorics Of Encounter: Toward A Biocentric Theory Of Discourse, Matthew D. Whitaker

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Encounters with more-than-human identities are transformative moments that stand to affect dispositional and bodily change in individuals. From close brushes with wild animals in National Parks to everyday interactions with local ecologies, encounters invite us to feel and think differently about the nature of our realities. In Rhetorics of Encounter: Toward a Biocentric Theory of Discourse, I draw from interdisciplinary perspectives to disrupt the idea of rhetoric as a representational medium, arguing that rhetoric occurs not just through textual exchanges of words and symbols, but through embodied moments of contact with other responsive beings. Invoking George Kennedy’s theory …

Explainable Multimodal Sentiment Analysis Of Social Media Visual Content For Child Safety, Yee Sen Tan, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Ensuring the safety and well-being of children is increasingly important, especially in a world where visual content is pervasive. This paper proposes a novel multimodal, multilingual, and multiclass sentiment analysis method for social media content, aimed at improving content moderation for child safety. Our approach integrates textual, visual, and audio data from videos, categorizing sentiment into four levels: positive, slightly negative, negative, and strongly negative, enabling granular detection of harmful content. To enhance explainability and trust, we also leverage interpretable mechanisms to analyze the contributions of each modality. Evaluation of our method demonstrates strong generalization across diverse video types, and …

Roadside Asset Extraction From Mobile Lidar Point Cloud, Yushin Ahn, Riadh Munjy, Stephen Choi

Mineta Transportation Institute

Mobile LiDAR systems are powerful tools that help us map roads and their surroundings in 3D with great speed and precision. The data provided by these systems support urban planning efforts, digital mapping, transportation infrastructure maintenance, and more. This report presents a comprehensive workflow for roadside asset extraction using Mobile Terrestrial Laser Scanning (MTLS) data, focusing on road lane detection, cross-section slope analysis, and point cloud classification. Roadside asset extraction is the identification and classification of roadside features like signs and poles. The dataset, acquired using a high-resolution mobile LiDAR system, contains over 5.7 billion points (pieces of data) across …

Sustainability: Buzz Word Or Future Of Fashion? Measuring The Feasibility Of Outright Sustainability Among Fast Fashion’S Biggest Agents, Ryan Miller

Apparel Merchandising and Product Development Undergraduate Honors Theses

Abstract

The fashion industry is currently experiencing unsustainable rates of pollution within its supply chains. The rapid increase in demand for short lead times perpetrated by large-scale retailers has led to hazardous practices negatively affecting both the environmental conditions and working conditions of producing countries. With this increased pressure, relationships between brands and suppliers have become untenable. Limited transparency and imbalanced power dynamics at the hand of the industry’s leading retailers require restructuring in order to build more sustainable and equitable supply-chain practices. Further, governmental regulation is currently limited in its capacity to enforce sustainable business practices on a global …

Exploring Commutativity In A Hindi Language Classroom, Kumar Gandharv Mishra

Journal of Humanistic Mathematics

Commutativity is an important concept in mathematics. However, not much emphasis is given to it in the elementary or secondary school curriculum, as there is a lack of interesting noncommutative examples at this level. Since most examples of binary operations provided deal with numbers, commutativity appears trivial. In this article we offer an interesting example of noncommutativity that is familiar to Indian school children from a different context. Students in India study a chapter based on the joining of vowels in Hindi grammar. This process is analogous to producing commutative as well as noncommutative operations. When we bring in mathematical …

Memes As An Effective Approach To Increase Public Engagement With Mathematical Concepts, Juan M. Romero, Carlos Trenado

Journal of Humanistic Mathematics

A meme is a graphical concept or cultural item that is disseminated via the Internet, often through social media platforms. Memes serve as a mechanism for replicating cultural traits by incorporating aspects of cultural mutation and evolution. The potential of memes in learning and education has been emphasized in several recent studies. The present article examines the impact of memes in increasing public engagement with mathematics and mathematical concepts. By focusing on memes that exhibit specific attributes—such as emotional facial expressions of recognizable human characters and dialogues emphasizing the usefulness or beauty of a mathematical concept—we observe a significant increase …

Bayes In The Brain: A Review Of Everything Is Predictable: How Bayesian Statistics Explain Our World, (2024) By Tom Chivers., Michael T. Catalano

Numeracy

Tom Chivers’ Everything is Predictable: How Bayesian Statistics Explain Our World, is an interesting and wide-ranging narrative on Bayesian thinking, its history, and its applicability to both our everyday lives and the pursuit of scientific truth. Although appropriate for the non-expert, afficionados and teachers of quantitative literacy should find the plethora of examples, links to psychology as it applies to how people reason about probabilities, and even Chivers’ philosophical musings informative and thought-provoking.

Tackling Data Quality Challenges In Remote Sensing: Solutions For Reliable Urban Heat Island Analysis, Wei Xia, Aqil Tariq, Hesham El-Askary, Rana Waqar Aslam, Elgar Barboza, Dmitry E. Kucher, Youssef M. Youssef, Habib Kraiem

Mathematics, Physics, and Computer Science Faculty Articles and Research

Urban heat islands (UHIs) pose critical challenges to public health, energy demand, and environmental sustainability, particularly in rapidly expanding urban regions. This study examines the complex relationship between building configurations and integrated green spaces, as well as their combined impact on thermal regulation. It focuses on addressing data quality issues commonly encountered in remote sensing applications. Using high-resolution multispectral and thermal imagery, we developed an integrated modeling approach that captures the collective influence of built form and green infrastructure on urban microclimates. A key finding is the significant linear inverse relationship between green space coverage and land surface temperature, underscoring …

Analysis Of The Impact And Adaptation Of Tidal Floods From Coastal Landscape Area Communities In Poasia District, Kendari City, Indonesia, La Ode Hadini, La Aba, Noor Husna Khairisa, Nikita Jasmine Almira

Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi

Poasia District is located in the coastal area of the southern part of Kendari City, which is highly susceptible to tidal flooding. However, the extent of the community's exposure to these events and their subsequent adaptation measures remain to be fully delineated. This study examines the impacts of tidal flooding and the adaptation patterns of the Poasia Coastal Community to the tidal flood disaster. This research employed a descriptive qualitative method, which was carried out through document review, interviews involving 34 respondents, and field observations. The results of this study indicate that tidal flooding exerts a negative impact on the …

07.28.2025 Ored Connect, Liz Williamson

ORED Newsletter

On-demand training courses released

• Mentoring
• My Project Was Funded, Now What?

Notice of Funding Opportunity SMART Act Accelerate Initiative

Memo Regarding Contact from Federal Agencies

High Spatial Resolution Crop Type And Land Use Land Cover Classification Without Labels: A Framework Using Multi-Temporal Planetscope Images And Variational Bayesian Gaussian Mixture Model, Minh Tri Le

Mathematics, Physics, and Computer Science Faculty Articles and Research

Previous studies often combined high spatial resolution data (e.g., PlanetScope) with wider spectral range data (e.g., Sentinel-2) and relied on supervised classification methods to produce land use and land cover (LULC) maps. This study proposed a new unsupervised framework to generate crop type and LULC maps at high spatial resolution (< 5 m) using available PlanetScope data solely without requiring ground truths. We used PlanetScope surface reflectance images and their derived spectral indices during growing seasons to create multi-temporal input features, which were fed into an unsupervised Variational Bayesian Gaussian Mixture Model (VBGMM). The VBGMM, unlike the traditional unsupervised classification methods, (1) first estimated optimal parameters that are most suitable based on the input features and then (2) assigned pixels to the cluster with maximum posteriori probability of a mixture of several Gaussian distributions. The crop type and LULC maps were then generated by labeling the derived clusters using the best possible assignment method, referring to the existing crop type or LULC products. We evaluated the produced PlanetScope-based crop type and LULC maps using true labels, corresponding reference maps, and other unsupervised classification methods. The results demonstrated the robustness and effectiveness of the proposed framework in mapping crop types and LULC at 3–5 m pixels across various ecosystems, climate zones, and human-managed landscapes. The spatial patterns of PlanetScope-based maps were (1) highly comparable with all the reference datasets at 10–30 m spatial resolution and (2) better than the traditional GMM and K-means clustering methods. The VBGMM produced classification maps with high confidence, yielding class probabilities above 0.9 for over 90 % of all study areas. The area percentage for all crop type and LULC classes agreed well with their reference maps, with R2 of 0.95 and RMSE of 1.04 %. The confusion matrices using true labels indicated that PlanetScope-based maps achieved a higher overall accuracy of 84 % than the supervised referenced maps of 81 %. Besides, the entropy comparison showed that our framework-based maps were better at capturing fine-scale features such as developed areas within cities that commonly mix with open space and vegetation, deforestation and cropland conversion in South America, smallholder croplands in Africa and Asia, and generating homogeneous crop fields in North America. This study further highlighted the potential for future research to implement our proposed framework to generate timely and extensive annotated datasets, which can be used for operationally training machine learning models to map crop types and LULC, track deforestation, detect wildfires, and delineate flooded areas at larger scales using medium/coarse Earth observations.

Rishon Le-ẒIyyon, Winepress Park: Geomorphology And Sedimentology, Joel Roskin, Yotam Asscher

Qadum: Journal of Excavation Reports from Israel

An extensive brown sandy double-unit sediment, draping large parts of the archaeological remains at the Winepress Park in Rishon Le-Ẓiyyon, is suggested to be associated with the previously reported, undated ʻEn Ha-Qore clay. Based on relative age port-OSL profiling, the depositional mechanism of this unit and the overlying sand is suggested to be related to late Holocene, dune-dammed winter ponds. These aeolian-fluvial dune-damming processes may have been partly triggered by intensive Byzantine human activity that may have led to sand mobilization.

Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson

Doctoral Dissertations and Projects

The purpose of this descriptive qualitative applied study is to define and explain through analysis the reasonable person standard as it relates to prosecution and sentencing computer crime cases involving digital identities while addressing the problem of digital anonymity. This has been done by analyzing computer crime cases with the advent of current and planned technologies, and surveying potential jurors to understand the current state of knowledge of digital attribution. This descriptive qualitative research method analyzed the problem through the use of criminological theories of control and social learning theory to better understand the reasonable person standard in computer crime …

Towards Sustainable Community-Designed Ai Systems In The Public Sector, Victoria Chui, Kelly Mcconvey, Erina Seh-Young Moon, Maya Ghai, Shion Guha

Health Services and Informatics Research

Advancements in data-driven modeling and artificial intelligence applications in public sector settings can lead to increased ten sions between stakeholder needs and tangible model capabilities from developers. Engaging multiple stakeholder groups in model development through the gleaning of sociotechnical, theoretical in sights using qualitative methods can contribute to more impactful, beneficial model solutions. Qualitative methods can complement quantitative model development, emphasizing stakeholder priori ties, informing model design choices, and promoting sustainable connections and model longevity. We are excited to discuss human centered qualitative methods, sustainable modeling practices, and community engagement in this workshop, engaging with scholars on system-level modeling strategies.

Collaborative Class Zine: Weekly Reflection Assignment With Powerpoint Template, Brett Whysel

Open Educational Resources

Abstract

This collaborative class zine assignment uses a shared PowerPoint format to deepen student learning while building community. Students contribute visual reflections (graphics, diagrams, quotes, or doodles) weekly or periodically throughout the semester. Faculty provide reflection prompts about key takeaways and unclear concepts (sample prompts included). The resource includes both sample LMS instructions and a ready-to-use PowerPoint zine template that works across all disciplines. By combining metacognitive reflection with creative expression, students consolidate learning by finding new connections and applications. The collaborative format creates community connections and joy while students learn from peers' diverse perspectives.

A Cancer Education Needs Assessment: Informing Middle-Aged Female Patients About The Relationships Between Obesity And Women’S Health Concerns In The Reproductive System, Breast, And Endometrial Health, Batul Mirza

MUSC Theses and Dissertations

Obesity significantly impacts women’s health, particularly among middle-aged women, by increasing the risk of hormone-sensitive cancers such as breast, endometrial, and reproductive system cancers. This study examines the educational needs of this demographic group regarding obesity-related cancer risks and explores effective intervention strategies. Obesity-induced mechanisms – hormonal imbalances, chronic inflammation, and insulin resistance – drive cancer susceptibility, emphasizing the need for targeted health education. The study employs a qualitative design, which includes interviews with subject matter experts (SMEs) and surveys of middle-aged women. The goal is to assess awareness, perceived barriers, and preferred learning methods. Findings suggest that with many …

"...Anything My Friend Shares, I Would Want To Support Them By Clicking On It": Co-Designing Story-Based Interventions Against Clickbait For Teenagers, Ankit Shrestha, Audrey Flood, Bryson Hackler, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Teenagers' lack of digital sophistication and cyber hygiene makes them vulnerable to social engineering attacks, especially as they start using social media. Clickbait, one of such attacks, is primarily performed through social media to trick users into clicking on malicious links. With teenagers' increasing use of social media, clickbait poses a substantial threat to their online safety. The existing online safety measures for teens mainly focus on parental mediation, which can be perceived as restrictive and privacy-invasive. To this end, researchers recommended empowering teens to deal with online risks. In order to design such interventions for clickbait, we conducted co-design …

Towards Leveraging Social Media Data For Fostering Collaborations Among Non-Profits, Monazil Chowdhury

LSU Doctoral Dissertations

Nonprofit organizations serve a crucial role in tackling a wide range of significant social, environmental, and economic issues. But it is often hard to get a clear picture of their work because their information is spread out and it is difficult to see how they are collaborating. To address this issue we developed a web-based tool to collect scattered data—from a variety of sources, such as the IRS, social media, and the Census, into one easy-to-use resource. The tool begins by taking IRS records and geocoding each nonprofit’s physical address With its coordinates. It then retrieves census tract information from …

Hyperspectral Band Selection Via Heterogeneous Graph Convolutional Self-Representation Network, Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hyperspectral image (HSI) band selection (BS) plays a crucial role in HSI dimensionality reduction, aiming to identify a representative subset of bands with minimal redundancy. However, conventional BS approaches primarily operate in the Euclidean domain, often overlooking the structural characteristics of pixels and spectral bands, such as spatial continuity and spectral dependencies. In addition, they handle each HSI as an integrated unit to harness implicit spatial information, disregarding spatial distribution variations across different homogeneous regions. To fully leverage structural information, this study introduces a novel BS method, termed the dual heterogeneous graph convolutional network with enhanced self-representation (ESR-HGCN), for HSI …

The People's Rivers: Early Environmental Regulation And The Oregon State Sanitary Authority, Avery Morgan Fischer

Dissertations and Theses

The environmental movement in Oregon can trace its origins to the turn of the twentieth century, where citizen activism and initiative led to the creation of an early environmental regulatory agency, the Oregon State Sanitary Authority. This creation established that the State of Oregon had a duty to preserve, not just the navigability or usability of rivers and waterways, but the quality and purity of its water. The Oregon State Sanitary Authority played an active role in maintaining and protecting the environment as a mandate of the people, and throughout its thirty-year existence battling industrial polluters, reluctant municipalities, and disinterested …

Review Of Averting The Digital Dark Age: The Future Of Digital Literary Heritage, Rebecca L. Hastings

Journal of Contemporary Archival Studies

In Averting the Digital Dark Age: How Archivists, Librarians, and Technologists Built the Web a Memory, Ian Milligan explores the efforts of technologists and information professionals to develop means of preserving information shared on the World Wide Web. The web lacks a built-in archiving function, raising fears of a “digital dark age,” an unprecedented gap in the historical record as information sharing via the web increases. Milligan tracks the development of web preservation debates and activities from the anxiety and turmoil of the early to mid-1990s to the coming of age of web preservation in the wake of the …

Integrating Artificial Intelligence And Machine Learning Technologies Into Common Operating Picture And Course Of Action Development, C. Anthony Pfaff, Christopher John Hickey

Books, Monographs & Collaborative Studies

C. Anthony Pfaff and Christopher John Hickey, Principal Investigators

©2025 C. Anthony Pfaff. All rights reserved.

Integrating Artificial Intelligence and Machine Learning Technologies into Common Operating Picture and Course of Action Development explores the potential of artificial intelligence (AI) and machine learning to revolutionize military planning processes by enhancing situational awareness and expediting course of action development within the Joint planning process. The study delves into technical, organizational, and resource considerations that are critical for AI integration. In addition, the study highlights the importance of clean, structured data in training AI systems, addresses challenges in data collection across varying formats …

Analyzing Environmental Health: Air Pollution And Human Health Using Geospatial Data Science, Yanhong Huang

Geography ETDs

Air pollution from industrial emissions and wildfire smoke poses growing threats to public health. This dissertation employs geospatial data science to examine these challenges through three interrelated studies. The first study investigates the relationship between maternal residential exposure to industrial pollutants and low birth weight, identifying five chemicals as significant risk factors. The second study assesses the impact of industrial air pollution on lung and bronchus cancer survival, finding that exposure to 1,1,1-trichloroethane and cobalt is associated with reduced survival. The third study explores disparities in wildfire smoke PM_2.5 exposure and its association with asthma exacerbations. Results show disparities …

"Chatgpt Told Me To Say It": Ai Chatbots And Class Participation Apprehension In University Students, Daisuke Akiba

Publications and Research

The growing prevalence of AI chatbots in everyday life has prompted educators to explore their potential applications in promoting student success, including support for classroom engagement and communication. This exploratory study emerged from semester-long observations of class participation apprehensions in an introductory educational psychology course, examining how chatbots might scaffold students toward active and independent classroom contribution. Four students experiencing situational participation anxiety voluntarily participated in a pilot intervention using AI chatbots as virtual peer partners. Following comprehensive training in AI use and prompt design given to the entire class, participants employed systematic consultation frameworks for managing classroom discourse trepidations. …

A Participatory Approach To Deploy Responsible Artificial Intelligence For Diabetes Prediction And Prevention, Laura C. Rosella, James Shaw, Shion Guha, Ibukun-Oluwa Omolade Abejirinde, Jennifer L. Gibson, Lorraine Lipscombe, Kathy Kornas, Remziye Zaim, Victoria Chui, Ijeoma Uchenna Itanyi

Health Services and Informatics Research

Artificial intelligence (AI) technologies have the potential to improve healthcare and public health. Although there has been success in AI for research uses, little progress has been made in implementing health-related AI technologies in health systems. Responsible AI for health systems requires engagement and co-design with health system partners, policymakers, and the community. Deploying responsible AI requires engaging stakeholders, particularly those affected by the technology. This commentary presents the importance of participatory approaches for responsible AI implementation. In this commentary, we discuss the planned use of participatory approaches to responsibly deploying validated machine learning models, with a specific case example …

Fireworks And Wood Combustion Impacts On Air Quality, Iris Keller

DePaul Discoveries

Fire is used as a land management tool to improve ecosystem health and to reduce wildfire risk by lowering tree and litter density. However, prescribed fire as a management practice has faced difficulties with public perception, because of increased awareness of air pollution. Understanding the way that prescribed burns impact air quality and how beneficial they are for ecosystems can help the public to recognize their necessity. This study measured particulate matter (PM) emissions from prescribed burns but also considered other PM sources: fireworks and bonfires. The measurements were conducted in Minnesota, Wisconsin, and the Chicagoland area in the summer …

Factors Motivating Clothing Choice: Environmental Impact Of T-Shirts, Lauren Hunt

DePaul Discoveries

Second only to oil, the fashion industry is one of the most pollutive industries globally. Due to the rise of fast fashion, this environmental issue is continually growing. The level of production has dramatically increased while quality of apparel has decreased, causing shorter garment lifespans. This research utilizes life cycle assessment to identify the environmental impacts of various textiles used in the production of t-shirts, including cotton, polyester, viscose, and elastane. The research scope focuses from material extraction through garment disposal. The life cycle assessment research is paired with a community survey to determine consumer behavioral patterns surrounding clothing consumption …

Environmental Justice And Soil Lead Contamination: Spatial Analysis Across Seven Community Areas, Arsene Lionel Apabaga

DePaul Discoveries

Pb is a pervasive metal with toxicity linked to numerous human health issues. Urban soil is a well-documented environmental sink for Pb, persisting as a legacy pollutant decades after the phaseout of leaded gasoline. This study measured, mapped, and analyzed the spatial distribution of total soil Pb concentrations across seven Chicago Community Areas (CCAs). The objectives were to: (1) assess the relationship between mean soil Pb concentration and mean Community Environmental Justice Index (CEJI) score per CCA, (2) determine the relationship between soil Pb levels and the percentage of industrial land use, and (3) quantify and compare the percentage of …

Values And Barriers: A Multidimensional View Of College Students’ Motivations To Volunteer, Gavin Warner, Quang Anh Nguyen, Ansuk Jeong

DePaul Discoveries

University students tend to have ample access to many resources for volunteering and so are in a unique position among Americans. With all the benefits of volunteering outlined in past research, the students training to become leaders in their fields may have the most to gain from volunteerism. It is surprising, then, to note that young people are less likely to volunteer than other age groups. Why is it that college students tend to volunteer at such low rates? The current study seeks to answer this question through a mixed-methods survey. A qualitative section clarified which specific barriers students felt …

“Put Me In Coach!”: The Impact Of College Sport Team’S Mentorship In Chronically Ill And Disabled Children And Adolescents Adherence To Medical Regimen, Jameela Askira

DePaul Discoveries

The purpose of this study was to see if participation in TeamIMPACT, a program which matches ill children with college sports teams, aided chronically ill children and adolescents in adhering to their treatment regimen. This research is a part of a larger study where 25 child participants were interviewed via Zoom to answer questions regarding their time in the program, peer and family relationships, coping and resilience and other factors. The current study solely analyzed answers to questions regarding adherence to medical treatments. There were three measures: Child vs Parent Response, Treatment Regimen Components and Care Responsibility. Through a descriptive …