Digital Commons Network^™

Quantifying The Sensitivity Of Land Use Land Cover Metrics Through Simulation Techniques, Haley Burger

All Graduate Theses and Dissertations, Fall 2023 to Present

As human activities and climate change continue to reshape our landscape, understanding how land use changes over time is becoming increasingly important. Accurate ways to track and analyze these changes are essential for governments, businesses, and communities to make informed decisions. Monitoring agricultural land is particularly critical, as shifts in land use can impact food production and environmental pollutants. One of the primary tools used in the United States to monitor agricultural land is the Cropland Data Layer (CDL), an annual map created by the United States Department of Agriculture (USDA) from satellite images. While the CDL is highly accurate, …

Warfare And Woodlands: Tracing Environmental And Military History In The Hürtgen Forest, Cedar Williams

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis explores what happens when war enters a forest. From 1944 to 1945, American and German forces fought a long, brutal battle in the Hürtgen Forest near Germany’s western border. The dark, wet, and heavily wooded terrain made the fighting unusually difficult. Soldiers struggled not just with enemy fire, but with freezing rain, deep mud, low visibility, and constant stress. The forest shaped how the battle unfolded and intensified its hardships.

But the war’s impact on the forest continued long after the soldiers left. Unexploded bombs and artillery shells littered the ground. During a heatwave in 1947, many of …

Womanhood, Survival, And The American Revolution: The Correspondence Between John And Abigail Adams And Henry And Lucy Knox, Kristin Jaques

All Graduate Theses and Dissertations, Fall 2023 to Present

The letters of Lucy and Henry Knox and Abigail and John Adams sent between 1775 and 1782 show how women stepped out of their expected gendered roles with thoughts of survival, not because they wanted to challenge the patriarchal society prevalent in the American colonies during the American Revolution.

Adaptations To Family-Based Treatment For Medicaid-Insured Adolescents With Anorexia Nervosa, Renee Borges

Doctoral Dissertations

Background: Family-based treatment (FBT) is the leading intervention for adolescents with anorexia nervosa (AN), however it is under researched in socioeconomically disadvantaged and racially diverse youth.

Methods: Semi-structured interviews were completed with ten FBT clinicians who practice in publicly-funded settings. Interview questions were focused on implementation challenges, overall acceptability and appropriateness of FBT, and naturally-occurring treatment adaptations.

Results: Content analysis revealed common themes relating to the implementation of FBT in publicly-funded, community-based settings: acceptability and appropriateness, complexity and learnability, perceived core components of FBT, cultural adaptations, socioeconomic factors, logistical considerations, organizational and systemic barriers, training acceptability, participant’s self-efficacy, and telehealth …

The Psychological Constructs Of International Graduate Students Transitioning To A University In America: A Thematic Analysis, Umadevi Ramesh

Doctoral Dissertations

This dissertation employed a qualitative analysis methodology to explore the experiences of first-time international graduate students during their transition to university, focusing on initial adjustment, perceived support, perceived discrimination, and mental well-being. Previous studies about international student experience have mainly focused on undergraduate students. Furthermore, few have examined the initial transition period to university and factors involved in both positively and negatively impacting students’ adjustment process as well as overall psychological well-being. Nine participants qualified for inclusion in the present study and participated in semi-structured interviews, which the researcher analyzed using a thematic analysis framework. Participants expressed a strong need …

Trust In Healthcare Ai Can’T Just Be Designed – It Must Be Felt By Clinicians And Patients, Adriana Banozic-Tang, Heng Wang

Research Collection Yong Pung How School Of Law

Trust in healthcare AI currently over-relies on system design, not lived medical realities.Continuous feedback loops are necessary to embed trust in healthcare AI that is responsive to clinician and patient needs.Initiatives in South-East Asia show how trust in technology can be extended from policy to practice.

I See Sick People: Beliefs About Sensory Detection Of Infectious Disease Are Largely Consistent Across Cultures, Joshua M. Ackerman, Theodore Samore, Daniel M. T. Fessler, Norman P. Li, Et Al

Research Collection School of Social Sciences

Identifying cues to contagious disease is critical for effectively tracking and defending against interpersonal infection threats. People hold lay beliefs about the types of sensory information most relevant for identifying whether others are sick with transmissible illnesses. Are these beliefs universal, or do they vary along cultural and ecological dimensions? Participants in 58 countries (N = 19,217) judged how effective, and how likely they were to use, cues involving each of the five major sensory modalities in an imagined social interaction during a flu outbreak. Belief patterns were strongly consistent across countries (sight > audition > touch > smell > taste), suggesting a largely …

Socioeconomic Status Shapes Dyadic Interactions: Examining Behavioral And Physiologic Responses, Jacinth J. X. Tan, Tessa V. West, Wendy B. Mendes

Research Collection School of Social Sciences

With more opportunities for diverse interactions, little is known about how social interactions involving people of different socioeconomic status (SES) may unfold. We investigated social attunement patterns in dyadic interactions involving SES. Unacquainted individuals recruited from the community interacted with similar-or-different-SES partners in the lab (Ndyads = 130). Attunement was assessed throughout the interaction by examining physiological linkage—how much a person’s physiological change is predicted by another’s physiological change, over time. Overall, low-SES participants showed stronger physiological linkage—indicating greater attunement—to partners across SES. Participants also appeared more comfortable when interacting with low-SES partners. There were no SES differences in dominance …

A Lifespan Perspective On Positive Affect Fluctuations On Purpose In Life: Findings From A 9-Year Longitudinal Study, Jonathan L. Chia, Verity Y. Q. Lua, Andree Hartanto

Research Collection School of Social Sciences

Existing research has examined how static or average levels of positive affect (PA) influence purpose in life (PIL), but theoretical work suggests PA fluctuations may also play a role, potentially undermining PIL, especially in older adulthood. To this end, the present study examined the longitudinal association of PA fluctuations on PIL and the moderating role of age among 1,294 midlife and older adults in the United States, over a 9-year period (between 2004 and 2014). Results revealed a conditional effect of PA fluctuations on PIL – particularly among older individuals, and greater PA fluctuations were associated with a poorer sense …

A General Bibliometric And Conceptual Structure Approach To Global Trend On Poverty Research In Islam Using Biblioshiny, Mohd Zaid Mustafar, Mohd Khairul Nizam Mohd Aziz, Dziauddin Sharif, Md Azzaat Ahsanie Lokman, Ashraff Bin Ruslan, Saiyidi Mat Roni

Research outputs 2022 to 2026

This study maps the intellectual landscape of research on poverty in Islam using a structured bibliometric approach with Biblioshiny (Bibliometrix) in RStudio. A Scopus search (TITLE-ABS-KEY “poverty” AND “Islam”) conducted on 1 September 2023 identified 279 English-language journal articles published between 1976 and 2023. The corpus spans 227 sources, 646 authors, and 10,262 cited references, with an annual growth rate of about 5%. Performance and science-mapping analyses reveal two “motor themes”—Islamic finance and healthcare/public health—while spiritually anchored constructs (e.g., maqasid, zakat governance, waqf, spiritual poverty) remain peripheral in co-occurrence and thematic maps. Citation patterns indicate higher field-normalized impact when studies …

Enhancing Gaas Solar Cell Efficiency Through Nanostructured Features: A Comprehensive Review Of Recent Advances, Challenges And Future Outlook, Mohammad Nur-E-Alam, Boon Kar Yap, Tiong Sieh Kiong, Mohammad Khairul Basher, Tarek Abedin, Mohammad Aminul Islam, Mohd Adib Ibrahim, Mayeen Uddin Khandaker, Narottam Das

Research outputs 2022 to 2026

This article aims to provide a synopsis of recent advances in the use of nanostructured features to augment the conversion efficiency of gallium arsenide (GaAs) solar cells. GaAs are a very well-known and highly advantageous material for solar cells because they possess an extraordinary bandgap (i.e., approximately 1.4 eV), wide spectral absorption coefficient, and favorable carrier mobility. Numerous studies have explored the use of nanostructures, such as antireflection (AR) nanofilms/nanocoatings, nanoparticles (NPs), and nanogratings (NG), to improve the conversion efficiency of GaAs-based solar cells. These structures are generally designed to enhance light transmission capacity and absorption while reducing light reflection …

Incorporating Ecosystem Service Assessments Into Development Planning − Impact From A Dredging Project In South Australia On Seagrass, Sam Gaylard, Rachel Colella, Matt Nelson, Paul Lavery, Michelle Waycott

Research outputs 2022 to 2026

Major infrastructure development is required for economic development and to improve human well-being, however conflict exists between developers and the community. Environmental impact assessment (EIA) is used in over 100 countries to evaluate potential impacts of major developments across environment, economy, and social benchmarks. However, EIA has been criticized for a lack of transparency and accountability, lack of consultation or participation and inadequate science. An ecosystem service assessment (ESA) recognizes the links between the environment and the socio-economic environment, resulting in a more holistic evaluation of potential impacts and effective community consultation. Despite this, its inclusion within EIA's is rare. …

Not All Political Ties Are The Same: Firms' Ties To The Government And Pollution, Wen Helena Li, Ilya R. P. Cuypers, Gokhan Ertug, Hari Bapuji, Wei Liu

Research Collection Lee Kong Chian School Of Business

Complementing research on the implications of political ties for firms’ strategic decisions and financial performance, recent studies are increasingly focusing on the environmental consequences of firms’ political connections. We contribute to this stream of work by integrating insights from the literature on political ties and the multifaceted nature of governments to explore how the level of government influences the pollution implications of firms’ political ties. Specifically, we theorize and demonstrate that, in China, firms' achieved political ties with high levels of the government reduce pollution, while such ties with low levels of the government increase it. Furthermore, we examine how …

Axicons For Improved Resolution And Depth Of Focus In Adaptive Optics Scanning Light Ophthalmoscopy, Ruth E. Woehlke, Robert F. Cooper

Biomedical Engineering Faculty Research and Publications

Adaptive optics scanning light ophthalmoscopes are instrumental for studying the eye, yet they use truncated Gaussian illumination and are limited by diffraction, restricting resolution and depth of focus (DOF). Non-diffractive Bessel beams have emerged as an alternative. Here, we use two axicons configured as: (1) an extended DOF beam for resolving multiple retinal layers; and (2) an annular beam for increasing lateral resolution. We compare both approaches to truncated Gaussian illumination using a variety of metrics. Using Configuration 1, we successfully observed multiple retinal layers simultaneously. Using Configuration 2, we observed enhanced lateral resolution but decreased signal-to-noise ratio.

An Injectable, Dual-Curing Hydrogel For Controlled Bioactive Release In Regenerative Endodontics, Meisam Omidi, Daniela S. Masson-Meyers, Jeffrey M. Toth

Biomedical Engineering Faculty Research and Publications

Regenerative endodontics seeks to restore the vascularized pulp–dentin complex following conventional root canal therapy, yet reliable neovascularization within the constrained root canal remains a key challenge. This study investigates the development of an injectable, dual-curing hydrogel based on methacrylated decellularized amniotic membrane (dAM-MA) and compares its performance to a conventional gelatin methacryloyl (GelMA). The dAM-MA platform was designed for biphasic release, incorporating both free vascular endothelial growth factor (VEGF) for an initial burst and matrix-metalloproteinase-cleavable VEGF conjugates for sustained delivery. The dAM-MA hydrogel achieved shape-fidelity via thermal gelation at 37 °C and possessed tunable stiffness (0.5–7.8 kPa) after visible-light irradiation. …

Decision-Making Methods Under Uncertainty In Discrete Multi-Objective Optimization, Chathuri Malee Aththanayake

Masters Theses and Doctoral Dissertations

This dissertation investigates decision-making methods in Uncertain Discrete Multi-objective Optimization Problems (UDMOPs), where uncertainty arises in both objective function and constraint coefficients. The study pursues three main goals: (1) constructing sensitivity regions in the objective space to handle objective-wise uncertainty, (2) constructing sensitivity regions in the decision space to handle feasibility uncertainties, and (3) developing methods to sort, group, and prune uncertain solutions based on their similarity. Each goal proposes a method to explore uncertain solutions and quantify their level of uncertainty. Based on this, solutions are classified as low and high-risk solutions, according to the Decision-Maker (DM)'s preferences and …

A Sociological Examination Of Masculinity In Korean Boys' Love Dramas, Jeremiah E. Magoncia

Korean Studies Department Faculty Publications

Korean Boys' Love (K-BL) dramas represent a growing subcategory within South Korean media, exploring romantic relationships between male characters and challenging historically rigid gender norms shaped by Confucian values, modernity, and hegemonic masculinity. Grounded in Social Constructionism and Queer Theory, this chapter employs content analysis on five K-BL dramas—Wish You, To My Star, Semantic Error, Jun and Jun, and Love for Love's Sake—to analyze how masculinity is constructed, portrayed, and subverted. The study reveals that K-BL dramas depict a spectrum of "Seme" and "Uke" roles that soften rigid gender binaries through emotional openness, gentleness, …

Impact Of Hereditary Angioedema Attacks On Health-Related Quality Of Life And Work Productivity, Maeve O'Connor, Paula J Busse, Timothy J Craig, Cristine Radojicic, H James Wedner, Sherry Danese, Julie Ulloa, Vibha Desai, Tomas Andriotti, Paul K Audhya, Sandra Christiansen

2020-Current year OA Pubs

BACKGROUND: Hereditary angioedema (HAE) negatively impacts health-related quality of life (HRQoL). Few studies have characterized impairments to HRQoL, work productivity, and well-being during and following HAE attacks.

METHODS: Patients with ≥1 HAE attack in the previous 3 months were recruited by the United States (US) HAE Association (HAEA) to complete an online survey. Respondents were categorized into those who did (Treated Cohort) and did not (Untreated Cohort) manage their last attack with on-demand treatment (OD). Adapted versions of the EuroQol-Five Dimensions-Five Levels (EQ-5D-5L), EuroQol Visual Analogue Scale (EQ VAS), and Work Productivity and Activity Impairment-General Health assessments were used.

RESULTS: …

Formation Control Between Leader And Migratory Follower Tissues Allows Coordinated Growth, Toru Kawanishi, Takamichi Sushida, Tony Y-C Tsai, Hiroyuki Takeda, Sean G Megason

2020-Current year OA Pubs

Coordinated growth of multiple tissues is fundamental to shaping our body, but the underlying mechanisms remain underexplored. In zebrafish embryos, midline tissues composed of the notochord, floorplate, and hypochord elongate synchronously with their lengths aligned. We show that floorplate and hypochord cells collectively migrate posteriorly along the nascent notochord extracellular matrix as it extends posteriorly, maintaining the tripartite configuration. Fibroblast growth factor-mediated migration in a spatially graded manner causes cell stretching, which triggers Yap-dependent proliferation and controls floorplate and hypochord growth. Supported by mathematical modeling, we further suggest that their growth is fine-tuned by mechanical tethering to the notochord via …

Barriers And Facilitators To Accessing Healthcare For People With Parkinson's Disease In Latin America: A Qualitative Study, Christine Jeyachandran, Catherine Spooner, Ana Margarita Rodriguez Salgado, Matthew Prina, Joel Rhee, Jorge Jesus Llibre-Guerra, Dani Kim, Juan J Llibre-Rodriguez, Mark F Harris

2020-Current year OA Pubs

AIMS: The aim of the study was to identify the barriers and facilitators to healthcare access for people with Parkinson's disease (PWP) in Spanish-speaking Latin American countries (LAC) in Central and South America, to understand their drivers and consider the implications for health systems in LAC.

METHODS: Four online semi-structured focus groups were conducted with 25 PWP who provide education and/or support to PWP. The study was designed and implemented by a person with lived experience of PD. Data were mapped to an existing model of access to healthcare that incorporates provider and consumer abilities.

FINDINGS: There were multiple provider …

Reimagining Education With Ai, Margherita Pagani, Steven M. Miller, Jerry Wind

Research Collection School Of Computing and Information Systems

This chapter examines AI’s transformative potential in education, focusing on Generative AI (GenAI) and Large Language Models (LLMs) while at the same time emphasizing the importance of grounding and guiding AI efforts with learning science and education research findings. It synthesizes analyses and expert recommendations, highlighting opportunities like personalized learning and enhanced teacher productivity, alongside challenges such as over-reliance on AI. Practical steps for instructors include adopting a question-first approach, utilizing AI for personalized feedback, designing AI-enhanced learning experiences, fostering critical thinking, and ensuring ethical AI use. The chapter concludes with strategic recommendations for leveraging AI to sustainably improve educational …

Dreamanime: Learning Style-Identity Textual Disentanglement For Anime And Beyond, Chenshu Xu, Yangyang Xu, Huaidong Zhang, Xuemiao Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Text-to-image generation models have significantly broadened the horizons of creative expression through the power of natural language. However, navigating these models to generate unique concepts, alter their appearance, or reimagine them in unfamiliar roles presents an intricate challenge. For instance, how can we exploit language-guided models to transpose an anime character into a different art style, or envision a beloved character in a radically different setting or role? This paper unveils a novel approach named DreamAnime, designed to provide this level of creative freedom. Using a minimal set of 2-3 images of a user-specified concept such as an anime character …

L3net: Localized And Layered Reparameterization For Incremental Learning, Xuandi Luo, Huaidong Zhang, Yi Xie, Hongrui Zhang, Xuemiao Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Model-based class incremental learning (CIL) methods aim to address the challenge of catastrophic forgetting by retaining certain parameters and expanding the model architecture. However, retaining too many parameters can lead to an overly complex model, increasing inference overhead. Additionally, compressing these parameters to reduce the model size can result in performance degradation. To tackle these challenges, we propose a novel three-stage CIL framework called Localized and Layered Reparameterization for Incremental Learning (L3Net). The rationale behind our approach is to balance model complexity and performance by selectively expanding and optimizing critical components. Specifically, the framework introduces a Localized Dual-path Expansion structure, …

Solving Two-Stage Stochastic Integer Programs Via Representation Learning, Yaoxin Wu, Zhiguang Cao, Wen Song, Yingqian Zhang

Research Collection School Of Computing and Information Systems

Solving stochastic integer programs (SIPs) is extremely intractable due to the high computational complexity. To solve two-stage SIPs efficiently, we propose a conditional variational autoencoder (CVAE) for scenario representation learning. A graph convolutional network (GCN) based VAE embeds scenarios into a low-dimensional latent space, conditioned on the deterministic context of each instance. With the latent representations of stochastic scenarios, we perform two auxiliary tasks: objective prediction and scenario contrast, which predict scenario objective values and the similarities between them, respectively. These tasks further integrate objective information into the representations through gradient backpropagation. Experiments show that the learned scenario representations can …

Preface, Special Issue For The 16th International Conference On Graph Transformation (Icgt 2023), Maribel Fernández, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

This special issue contains six extended versions of papers presented at the 16th International Conference on Graph Transformation (ICGT 2023), held in Leicester, UK, on 19–20 July 2023. The conference was part of STAF 2023 (Software Technologies: Applications and Foundations) and was held under the auspices of the European Association for Theoretical Computer Science (EATCS), the European Association of Software Science and Technology (EASST), and the IFIP Working Group 1.3, Foundations of Systems Specification.

Evaluating And Mitigating Linguistic Discrimination In Large Language Models: Perspectives On Safety Equity And Knowledge Equity, Guoliang Dong, Haoyu Wang, Jun Sun, Xinyu Wang

Research Collection School Of Computing and Information Systems

By training on text in various languages, large language models (LLMs) typically possess multilingual support and demonstrate remarkable capabilities in solving tasks described in different languages. However, LLMs can exhibit linguistic discrimination due to the uneven distribution of training data across languages. That is, LLMs are hard to keep the consistency of responses when faced with the same task but depicted in different languages. In this study, we first explore the consistency in the LLMs’ outputs responding to queries in various languages from two aspects: safety and quality. We conduct this analysis with two datasets (AdvBench and NQ) based on …

Cami: A Counselor Agent Supporting Motivational Interviewing Through State Inference And Topic Exploration, Yizhe Yang, Palakorn Achananuparp, Heyan Huang, Jing Jiang, Phey Ling Kit, Nicholas Gabriel Lim, Cameron Shi Ern Tan, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Conversational counselor agents have become essential tools for addressing the rising demand for scalable and accessible mental health support. This paper introduces CAMI, a novel automated counselor agent grounded in Motivational Interviewing (MI) – a client-centered counseling approach designed to address ambivalence and facilitate behavior change. CAMI employs a novel STAR framework, consisting of client’s state inference, motivation topic exploration, and response generation modules, leveraging large language models (LLMs). These components work together to evoke change talk, aligning with MI principles and improving counseling outcomes for diverse clients. We evaluate CAMI’s performance through both automated and expert evaluations, utilizing simulated …

Towards Context-Aware Traffic Classification Via Time-Wavelet Fusion Network, Ziming Zhao, Zhuoxue Song, Xiaofei Xie, Zhaoxuan Li, Jiongchi Yu, Fan Terry Zhang, Tingting Li

Research Collection School Of Computing and Information Systems

Encrypted traffic classification occupies a significant role in cybersecurity and network management. The existing encrypted traffic classification technology mostly relies on intra-flow semantics for extracting features. However, considering that some attack behaviors inherently have similar patterns to legitimate behaviors, and powerful adversaries could simulate benign users to conceal their attack intentions, intra-flow features may be similar between different categories. In this paper, we propose TrafficScope, a time-wavelet fusion network based on Transformer to enhance the performance of encrypted traffic classification. Specifically, in addition to using intra-flow semantics, TrafficScope also extracts contextual information to construct more comprehensive representations. Moreover, to cope …

Assessing The Robustness Of Test Selection Methods For Deep Neural Networks, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Lei Ma, Yves Le Traon

Research Collection School Of Computing and Information Systems

Regularly testing deep learning-powered systems on newly collected data is critical to ensure their reliability, robustness, and efficacy in real-world applications. This process is demanding due to the significant time and human effort required for labeling new data. While test selection methods alleviate manual labor by labeling and evaluating only a subset of data while meeting testing criteria, we observe that such methods with reported promising results are simply evaluated, e.g., testing on original test data. The question arises: are they always reliable? In this article, we explore when and to what extent test selection methods fail. First, we identify …

Gradients As An Action: Towards Communication-Efficient Federated Recommender Systems Via Adaptive Action Sharing, Zhufeng Lu, Chentao Jia, Ming Hu, Xiaofei Xie, Mingsong Chen

Research Collection School Of Computing and Information Systems

As a promising privacy-aware collaborative model training paradigm, Federated Learning (FL) is becoming popular in the design of distributed recommender systems. However, Federated Recommender Systems (FedRecs) greatly suffer from two major problems: i) extremely high communication overhead due to massive item embeddings involved in recommendation systems, and ii) intolerably low training efficiency caused by the entanglement of both heterogeneous network environments and client devices. Although existing methods attempt to employ various compression techniques to reduce communication overhead, due to the parameter errors introduced by model compression, they inevitably suffer from model performance degradation. To simultaneously address the above problems, this …