Physical Sciences and Mathematics Commons^™

Toward Integrated Urban Observatories: Synthesizing Remote And Social Sensing In Urban Science, Danlin Yu

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Urbanization is reshaping landscapes and posing unprecedented sustainability challenges, necessitating more integrative approaches to urban observation. This review synthesizes recent advancements in traditional remote sensing and emerging social sensing technologies, emphasizing their convergence within urban science. A systematic thematic analysis of 667 peer-reviewed articles highlights the methodological progress, practical applications, and theoretical innovations arising from this integration. Traditional remote sensing effectively captures urban physical features but lacks insights into human behaviors. Conversely, social sensing, leveraging digital traces from social media and mobile data, introduces essential human-centered dimensions into urban monitoring. The fusion of these complementary paradigms through advanced data analytics …

2025 June - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

The main story of June 2025 was the first major heat wave of the year that sent temperatures into the mid-to-upper 90’s and heat index values over 100°F for most locations in the state from June 22nd to 28th. This included the first day of the year with a high over 90°F for many parts of the state. The National Weather Service offices covering Tennessee issued heat advisories for most counties in the state for at least 1 day during this period and several areas of West and Middle Tennessee had multiple days in a row with these …

Forging The Future, Kenneth Benoit

Asian Management Insights

How AI is rewriting the rules of knowledge, expertise, and practice.

Strategy And Stewardship In An Uncertain World, Havovi Joshi

Asian Management Insights

This issue, as we continue to celebrate Singapore Management University’s (SMU) 25th anniversary, we explore leadership in higher education, the rise of artificial intelligence (AI), ethical stewardship, and other challenges, highlighting how they intersect in our increasingly complex, fast-changing world.

Binary Document Filtering For Retrieval-Augmented Generation, Sreyan Saha

Master’s Dissertations

Retrieval-Augmented Generation (RAG) has become a popular technique to enhance Large Language Models (LLMs) with access to external information sources. However, the success of RAG systems critically depends on the relevance and quality of the retrieved documents. In particular, supplying irrelevant or noisy context can lead to degraded downstream generation quality. To address this, our project focuses on improving the document filtering stage in a RAG pipeline through binary relevance classification — deciding whether a retrieved document is suitable to include in the final context window based on its usefulness in directly answering the user query. We explore a wide …

"Maine Office Of Behavioral Health’S Section 17 Self-Direction Pilot Program: Executive Summary", Rachel M. Gallo Mph, Sarah Goan, Emma Schwartz

Publications

The Self-Directed Care (SDC) pilot program in Maine tested a service delivery model that allows individuals with mental health needs to manage a personal budget, supported by a trained broker to purchase goods and services that best support their recovery goals. Funded through the American Rescue Plan Act, the Maine Office of Behavioral Health implemented the nine-month pilot in three counties, partnering with Alpha One, Maine’s Center for Independent Living, to provide reloadable debit cards for participant purchases. The program aimed to promote autonomy, satisfaction, and stability among adults receiving Section 17 Medicaid services while informing decisions about the model’s …

Reducing Carbon Emissions Through Sustainable Food Consumption: Applying An A-S-I Framework On Beijing Residents, Xuan Yang, Jiaxin Zou, Jingyao Gao, Shu Yang

Student Publications

The food sector represents one of the largest contributors to global climate change, making it urgent for the public to transform their food consumption behavior. However, food consumption behaviors that can facilitate carbon reduction, and how to classify these behaviors from the perspective of behavioral science, have not been deeply explored. This study pioneers a novel categorization of carbon-mitigating food consumption behaviors based on an A-S-I framework (i.e., “Avoid” food loss and waste, “Shift” to low-carbon alternatives, and “Improve” dietary structure). Such a classification not only encompasses the full spectrum of emission-altering behaviors but also enables identification of common determinants …

Minifying Deep Denoising Networks With Knowledge Distillation, Antonio L. Rozzi

Master's Theses

Hearing loss is a prevalent condition, affecting hundreds of millions globally, with a higher incidence among older adults. While hearing aids are the standard treatment, the majority of those who could benefit from hearing aids choose not to wear them, attributing this decision in large part to their inability to perform well in conversations in large groups and in noisy situations. To date, no denoising systems on commercial hearing aids are able to improve speech intelligibility. Recent advances in artificial intelligence research have shown that large deep-learning models can in fact improve speech intelligibility by removing background noise from audio. …

Efficient Gan-Based Adversarial Example Generation Against Ml-Based Network Intrusion Detection Systems, Darren D. Hartono

Master's Theses

In the realm of network security, Network Intrusion Detection Systems (NIDS) are essential for identifying and mitigating malicious activities targeting networked devices. Traditionally, these systems have relied on signature-based and anomaly-based detection techniques. However, the increasing complexity and adapt- ability of cyber threats have driven the adoption of Machine Learning (ML) ap- proaches in modern NIDS, significantly improving their ability to detect a wider range of attack vectors. Despite these advancements, ML-based NIDS remain vulnerable to adversarial examples—deliberately crafted inputs designed to mislead models and trigger incorrect classifications. Originally identified in the field of computer vision, adversarial examples now pose …

Clusters, Trends, And Choices: Feature Selection In Interactive Statistical Graphics, Dylan Le

Master's Theses

Exploratory data analysis (EDA) is a method for uncovering the structure and key characteristics of data, often through the use of statistical graphics. These visual tools can reveal patterns and trends, and their effectiveness can be enhanced through interactivity. By enabling users to filter data, zoom, and toggle visual features, interactive plots can accelerate and enrich the EDA process. This study extends a previous graphical study by incorporating an interactive framework. Using a statistical lineup protocol with two target patterns (a linear trend and a clustering trend) participants interacted with plots by toggling various aesthetic features, including cluster coloring, ellipses …

The Impact Of Accessibility Features On Player Experience In Video Games, Christine M. Widden

Master's Theses

While video game accessibility is a growing research topic, few studies investigate how players perceive the presence versus the absence of accessibility features, or how non-disabled players react to the option of accessibility features. This study explores these research gaps, investigating how access to accessibility features affects the experience of both disabled and non-disabled players. For the purposes of this study, a small platformer game was developed with as many accessibility features as feasible for the scope of the project. An A vs.\ B study was conducted in the game, with anonymous participants randomly assigned to version A, with all …

Steiner Coset Partitions Of Groups, Fusun Akman, Papa Sissokho

Faculty Publications – Mathematics

A coset partition of a group G is a set partition of G into finitely many left cosets of one or more subgroups. A driving force in this research area is the Herzog–Schönheim Conjecture, which states that any nontrivial coset partition of a group contains at least two cosets with the same index. Although many families of groups have been shown to satisfy the conjecture, it remains open.

A Steiner coset partition of G, with respect to distinct subgroups H₁,...,H_r, is a coset partition of G that contains exactly one coset of each …

"Maine Office Of Behavioral Health’S Section 17 Self-Direction Pilot Program: Evaluation Report", Rachel M. Gallo Mph, Sarah Goan, Emma Schwartz, Aaron Rose

Publications

Maine’s Office of Behavioral Health conducted a nine-month pilot of Self-Directed Care to support adults with serious mental illness in Cumberland, Hancock, and Washington Counties. The program allowed eligible participants receiving MaineCare Section 17 services to manage a personal budget, guided by trained Support Brokers from Alpha One, to purchase goods and services that would advance their recovery goals. The pilot aimed to increase participant choice, autonomy, and flexibility in managing their mental health needs. Support Brokers worked closely with participants and Case Managers to develop and approve individualized purchase plans, monitor expenditures, and ensure alignment with treatment objectives. A …

A Decision Support System For Conference Session Selection Using Natural Language Processing, Tillman E. Erb

Master's Theses

Conference attendees are faced with selecting from hundreds to thousands of presentations and sessions in pursuit of new findings and methods relevant to their area of interest, an overwhelming amount of information from which to clearly make a decision. To address this, we developed a decision support system leveraging natural language processing (NLP) techniques such as semantic matching. By creating and matching embeddings of conference presentation abstracts and titles, the application provides improved query matching compared to keyword searching. We introduce Session Scout, a novel conference decision support system built upon a semantic retrieval framework. Session Scout is designed to …

Density-Based And Model-Based Clustering With Tidyclust In R, Brendan S. Callender

Master's Theses

Clustering is a fundamental technique in unsupervised learning that can be used to find hidden patterns and structures within unlabeled data. The tidyclust package in R provides a unified interface for applying various clustering techniques to data. This paper outlines the addition of density-based clustering with DBSCAN, and model-based clustering using Gaussian mixture models (GMMs) to the tidyclust package. DBSCAN can be performed using the db_clust() function and makes use of the dbscan package implementation as its engine. GMMs can be fit using the gm_clust() function which makes use of the mclust package implementation. This paper highlights the changes made …

Statistical Investigations Of Strategies In The Game Ecosystem, Dylan Li

Master's Theses

This work provides a probability-based analysis of strategies in the board game Ecosystem. Ecosystem is a turn-based multiplayer tiling game, where players take turns picking a wildlife card from a limited pool of cards then placing that card on their personal 4x5 grid. The objective of the game is to place the wildlife cards to maximize your score, as each card’s scoring condition depends on the presence or absence of certain cards surrounding it. The goal of this project is to determine optimal strategies for tiling your grid using techniques such as simulation to find optimal grid arrangements and clustering …

Bandwagon Behavior In Major League Baseball, Daniel E. Erro

Master's Theses

This study investigates “bandwagon” behavior among Major League Baseball (MLB) fans by analyzing Google search interest data from 2004 to 2019. Drawing on publicly available information from Google Trends, the analysis explores how fluctuations in search activity align with team performance during both the regular season and postseason. Hierarchical linear models are used to estimate expected levels of fan interest based on team performance and market characteristics. Deviations from these expectations during the regular season are interpreted as evidence of bandwagon or anti-bandwagon behavior. A drop-off in interest following playoff elimination is also examined to capture shifts in fan attention …

Babies, Babes, And Bayes: Modeling Mother-Infant Feedings With Bayesian Multilevel Hidden Markov Models, Zachary G. Felix

Master's Theses

Understanding the interaction between mother and baby during feeding is critical for the long-term development health of the baby. Overfeeding can lead to later obesity, while underfeeding can lead to malnutrition. In a recent study, the behaviors exhibited by mother-infant dyads across multiple ages of infants have been observed and coded according to the Baby Behaviors when Satiated (BABES) coding scheme. However, creating models using the data obtained from this coding is no simple task since the data coding is continuous, multivariate, and longitudinal in nature. The specific model utilized for these data is a hidden Markov model, since there …

Topiarism: The Kernel Embedding Of Distributions Applied To Modern Portfolio Theory, Stephen G. Cook

Master's Theses

The method of kernel embedding of distributions on a set $\Omega$ into a reproducing kernel Hilbert space is a method of studying the space of measures on a set $\Omega$ using Hilbert space geometry. Because positively weighted portfolios can be interpreted as nonnegative probability measures on the space of assets, we are able to apply this technique to portfolio theory. In this thesis, we discuss the theory of "topiarism", the study of positively weighted probability measures on compact sets under the kernel embedding of distributions. Given a specific payoff function $\psi$ on the set of assets $\Omega$, we optimize a …

Optical Character Recognition For Early Handwriting Legibility Assessment, Franceli L. Cibrian, Kayla Anderson, Yingying 'Yuki' Chen, Lauren Min, Lizbeth Escobedo

Engineering Faculty Articles and Research

Monitoring children’s handwriting, such as avoiding writing assignments, displaying uneven letter formation, or showing slow writing speed, can help identify developmental and academic issues early. Poor handwriting affects up to 34% of children, leading to academic and self-esteem challenges. Handwriting assessments, typically conducted by teachers, are often delayed due to workload and could be subjective and inconsistent. This paper explores the potential of Optical Character Recognition (OCR) technology to augment and ease handwriting assessments. Based on an evaluation of 10 OCR algorithms using 33 handwriting samples assessed by two experts, the research indicates that Pen to Print and Google are …

Enabling Automatic Solar Pv Array Identification Using Big Satellite Imagery, Qi Li, Keyang Yu, Carson Snow, Dong Chen

Computer Science Faculty Research and Publications

Recently, there has been a growing interest in automatically collecting distributed solar photovoltaic (PV) installation information in smart grid systems, including the quantity and locations of solar PV deployments, as well as their profiling information across a given geospatial region. Most recent approaches are still suffering low detection accuracy due to insufficient sample and principal feature learning when building their models and also separation of rooftop object segmentation and identification during their detection processes. In addition, they cannot report accurate multi-deployment results. To address these problems, we design a new system-SolarDetector+, which can automatically and accurately detect and profile distributed …

Capfish Project Report : Summer Academy For The Pacific Islands, Kathleen Auld, Francis Neat, Raphaël Baumler

Reports

The CAPFISH Project was created in response to an identified need for capacity-building to address illegal, unreported and unregulated (IUU) fishing and related matters - a complex problem affecting aquatic ecosystems, coastal communities, fishers and fish workers, and economic and national security. Over the last four years, the CAPFISH Project has provided training and educational materials on IUU fishing to developing country administrations around the world, most recently with a two-week regional Summer Academy for the Pacific Islands. This Academy ran for two weeks and included delegates from fisheries, labour, safety, maritime, foreign affairs, and enforcement administrations in the Pacific …

Satellite And Eddy Covariance Analysis Reveals Short-Lived Evapotranspiration Changes After Fire In Mediterranean Woodland, Hoang Long Nguyen, Simone Gelsinari, J. Nik Callow, Richard Silberstein, Sally E. Thompson

Research outputs 2022 to 2026

Ecosystem evapotranspiration (ET) varies through space and time in response to environmental gradients and disturbances like fire. Field-based techniques (e.g. eddy covariance) can directly measure how ET responds to fire; however, these measurements are localised and only represent small areas. Remotely sensed ET products can potentially evaluate fire impacts on ecosystem ET, but their performance for this task remains largely unassessed. This paper uses three widely available remote sensing products: the CSIRO MODIS ReScaled ET (CMRSET), MODIS ET (MOD16), and Penman–Monteith–Leuning (PML), to assess ET changes caused by a fuel reduction burn in a Mediterranean woodland in comparison to the …

City & Town Perspectives On Water Management In Utah: Descriptive Report Of Survey Findings, Bailey M. Holdaway, Courtney G. Flint

Environment and Society Student Research

In an effort to better understand the water management practices of municipalities in Utah, surveys were conducted with city and town representatives. These surveys aimed to capture insights across a variety of key topics related to water resource management. A brief overview of survey methods is provided followed by findings organized by question topic.

A Digital Dive: Redesigning The Cabrillo High School Aquarium Website, Jacob V. Cacho

Graphic Communication

Tucked away on the Central Coast in Lompoc, you’ll find the Cabrillo High School (CHS) Aquarium. Started in 1986, the CHS Aquarium is the only high school aquarium of its kind in the nation run entirely by high school students. This 10,000+ square foot aquarium serves an underserved community at a Title I school, where students manage all aspects of animal care, nutrition, breeding, educational curriculum development, and visitor tours.

This program is truly one-of-a-kind and deserves the spotlight for just how unique it is. As a CHS graduate, I felt the current website lacked in many areas and could …

Efficient Blending Of Large Language Models, Sandeep Chatterjee

Master’s Dissertations

Due to the limited capabilities of single Large Language Models (LLMs), multiple LLMs can be employed in tandem for better reliability of answers. Blending refers to combining the strengths of various LLMs to make use of their complementary capabilities for generating high-quality responses. It is a non-trivial problem, and the task becomes even more difficult when aiming for minimal latency and supervising the blending components. The standard framework, LLM- Blender, approaches this in three stages: response generation, candidate selection via ranking, and response fusion through summarization. However, this pipeline faces two critical limita- tions—high latency due to repeated ranking steps, …

Geometry Based Uav Trajectory Planning For Mixed User Traffic In Mm Wave Communication, Sk Abid Hasan

Master’s Dissertations

Unmanned aerial vehicle (UAV) assisted communication is a revolutionary technology that has been recently presented as a potential candidate for beyond fifth-generation millimeter wave (mmWave) communications. Although mmWaves can o↵er a notably high data rate, their high penetration and propagation losses mean that line of sight (LoS) is necessary for e↵ective communication. Due to the presence of obstacles and user mobility, UAV trajectory planning plays a crucial role in improving system performance. In this work, we propose a novel computational geometry-based trajectory planning scheme by considering the user mobility, the priority of the delay sensitive ultra-reliable low-latency communications (URLLC) and …

Word Level Attack For Text Ranking, Tanmay Karmakar

Master’s Dissertations

Neural Ranking Models (NRMs) have become state-of-the-art in information retrieval, demonstrating remarkable effectiveness across various search and ranking tasks. However, their increasing deployment in real-world systems raises critical concerns about their robustness and susceptibility to adversarial attacks. This project investigates the fragility of modern NRMs by proposing and evaluating a document perturbation method based on targeted, single-word perturbation. Our approach strategically identifies an influential word depending on the query to be substituted or added in the document. We have done experiments on benchmark datasets to assess the impact of these minimal perturbations on ranking performance. Our findings reveal that even …

Designing A Model To Empower Rural Communities For Self-Sufficiency In Zanjan Province, Iran, Azra Ganjkhanloo, Alireza Poursaeed, Roya Eshraghi Samani, Marjan Vahedi

The Philippine Agricultural Scientist

In this research, empowerment is conceptualized as the process through which rural villagers organize themselves to enhance their self-sufficiency, assert their right to independent decision-making, gain control over resources, and address and overcome poverty. This study aimed to develop an empowerment model for rural communities in Zanjan Province, Iran, focusing on achieving self-sufficiency and assessing the model using structural equation modeling. The study compared the main components of the model using the post-event technique and validated the variables of self-sufficiency in rural communities through a descriptive-correlational design and structural equation modeling. The sample comprised 384 villagers selected via stratified random …

Integrating Universal Generative Ai Platforms In Educational Labs To Foster Critical Thinking And Digital Literacy, Vasiliy S. Znamenskiy, Joel Hernandez, Rafael Niyazov

Publications and Research

This study investigates the educational potential of generative artificial intelligence (GenAI) platforms based on large language models (LLMs), such as ChatGPT, Claude, and Gemini, as tools for studentcentred learning. Recognizing the current limitations of GenAI, particularly its propensity for generating inaccurate or misleading information—the paper proposes a novel instructional strategy: an interdisciplinary laboratory designed to foster critical evaluation of GenAI-generated outputs. In this pedagogical model, students engage with GenAI systems by posing questions or solving problems drawn from topics they have already studied and understand. Equipped with correct answers, students are positioned to assess the accuracy and relevance of AI-generated …