Digital Commons Network^™

Research Priorities For Nursing And Allied Health: A Priority-Setting Project Using A Partnership Approach, Marina Weckend, Lucy Gent, Erin Godecke, Linda Coventry, Gemma Doleman, Amanda Towell-Barnard, Lisa Whitehead

Research outputs 2022 to 2026

Background: Research priorities guide research activities, funding and resources within health services. To ensure that research efforts are meaningful and impactful, it is vital that organisational research agendas reflect the priorities of both healthcare consumers and staff, alongside broader national and international research frameworks. This paper outlines a research priority-setting project conducted across two hospitals in Western Australia, aimed at identifying shared research priorities through a collaborative and inclusive approach. Aim: To identify the top ten nursing and allied health research priorities for two hospitals in Western Australia. Methods: A modified James Lind Alliance Priority Setting Partnership approach was used, …

Making Their Community Proud: First-Generation Latinx Students' Participation In Clep, Michelle Van Beek, Abby Holland

Journal of College Access

This study explores the impact of earning Spanish CLEP credit on first-generation Latinx students' levels of self-efficacy, college-going mindset toward earning a post-secondary degree, and their perceptions of bilingualism. Study participants (n=47) were all enrolled or previously enrolled in a college access program in high school. All participants received the opportunity to take the Spanish CLEP exam. Participants (n=33) completed a pre/post survey, and a paired sample t-test showed self-efficacy, college-going mindset, and language perceptions remained neutral for participants. Five semi-structured group interviews (n=26) were conducted after the post-survey. Participants showed that earning Spanish CLEP credit impacted their way of …

Complete Issue, Christopher Tremblay, Patrick J. O'Connor Phd, Laura Owen, Moya Malcolm, Diana Camilo

Journal of College Access

No abstract provided.

Reframing Narratives, Reclaiming Futures: Antiracist School Counseling And Black And Brown Girls In Stem, Renae D. Mayes, Lia D. Falco, Shontell Zenon, Dequindre Hughes, Yijia Chen, Lydia Ross, Medha Dalal

Journal of College Access

Black and Brown girls often have educational experiences that stifle their career aspirations, especially in STEM fields. These experiences can be exacerbated by educators who misunderstand and refuse to recognize their STEM potential, thus limiting their opportunity to build STEM identities. School counselors can disrupt these experiences through antiracist practices that cultivate homeplace and joy for Black and Brown girls to heal and grow while working to address harmful policies and practices. In this paper, authors discuss how school counselors can specifically use antiracist school counseling practices to support Black and Brown girls in STEM as a part of multi-tiered …

The Limits Of Daca: Affordability- And Access-Related Barriers To Health Professions Education, Nicole Perez, Laura Hirshfield

Journal of College Access

The U.S. is currently facing a shortage of health professionals from underrepresented backgrounds. One potential pathway to decrease this shortage is through the Deferred Action for Childhood Arrivals (DACA) program, a policy that provides temporary relief from deportation for individuals who migrated to the U.S. before age 16. This study, using 15 life-history narrative interviews, investigates the experiences of Latinx young adults who were pursuing health professions education or working as health professionals. Nine of the participants were DACA recipients, while the remaining six were second-generation (i.e., children of immigrants). An iterative, inductive approach to data analysis was used to …

Effect Of Traditional And Cluster Set Structures On Bar Path Kinematics During High-Volume Power Clean Training, Tsuyoshi Nagatani, Shayne Vial, Kristina L. Kendall, Paul Comfort, Jiahao Yang, G. Gregory Haff

Research outputs 2022 to 2026

The aim of this study was to examine the effects of traditional (TRAD) and cluster (CLU) set structures on bar path kinematics during a series of high-volume power clean sets, and compare insights gained from discrete versus waveform analysis. Twenty participants completed TRAD or CLU protocols in a randomised, crossover design. Each protocol involved three sets of nine repetitions at 70% of one-repetition maximum. In CLU sets, a 30-second inter-repetition rest was applied. During TRAD sets, peak velocity declined, and significant (p ≤ 0.05) changes were observed in both vertical and horizontal barbell displacement across repetitions, indicating fatigue-related technical alterations. …

Physicochemical Characterization Of Small Extracellular Vesicles: Effects Of Immobilization, Isolation, And Disease State, Bianca M. Mercado Velez

Dissertations, Master's Theses and Master's Reports

Cancer treatments and survival outcomes have improved significantly in the last couple of decades, with survival rates increasing in the U.S. Despite improvements in treatment outcomes, early detection and treatment are crucial for improving cancer prognosis and survival rates. The standard cancer diagnostic procedure of tissue biopsy is highly invasive, leading to the further spread of cancer in some cases. Alternatively, the extraction of biofluids from cancer patients, also called a liquid biopsy, is increasingly popular because it is less invasive and more representative of the tumor microenvironment, which contains cancer cells, tumor genetic material, and extracellular vesicles, including small …

Antenna-Based Sensors For Dielectric Characterization Of Materials, Hilary Scott Nkimbeng Cho

Dissertations, Master's Theses and Master's Reports

This research introduces antenna-based sensors for dielectric characterization aimed at overcoming the limitations of conventional microwave sensors. Although traditional microwave sensors are widely used for their noncontact operation, high sensitivity, and ability to penetrate various materials, they often face challenges such as large size and high-power consumption. To address these issues, antenna-based sensors are explored for their compactness, ease of fabrication, and flexible design adaptability across diverse sensing applications. An in-depth analysis of multiple antenna sensor configurations is conducted, followed by the design and development of high-performance sensing structures. A saw-tooth slot antenna sensor is developed for highly sensitive liquid …

Robust State Estimation And Scene Understanding For Autonomous Ground Vehicles In Challenging Environments, Nader J. Abu-Alrub

Dissertations, Master's Theses and Master's Reports

Autonomous ground vehicles require reliable state estimation and scene understanding to operate safely in challenging environments. Poor illumination, adverse weather, degraded visibility, snow-covered roads, and sensor noise can reduce the reliability of conventional localization and perception pipelines. Addressing these challenges requires sensing and algorithmic strategies that exploit the complementary strengths of different modalities. Radar is particularly attractive because of its resilience to lighting and weather variations, while inertial, camera, and lidar measurements provide additional motion, appearance, and geometric information. This dissertation investigates compact radar-based and sensor-fusion approaches for improving autonomous ground-vehicle state estimation and scene understanding under degraded sensing conditions. …

Applied Forest Restoration And Conservation In Michigan: Advancing American Beech Restoration And Documenting A Historical Insect Collection, Thomas E. Panella

Dissertations, Master's Theses and Master's Reports

Forest restoration and conservation require both practical management approaches and the preservation of biological resources that support future research. This dissertation presents applied research conducted in Michigan that advances American beech (Fagus grandifolia) restoration in response to beech bark disease (BBD) while documenting an important historical entomological resource. Chapters 1–3 focus on overcoming practical barriers to American beech restoration. Restoration protocols were developed and refined for identifying BBD-resistant trees, graft propagation, rootstock collection, container production, and the field establishment of grafted BBD-resistant trees. A greenhouse experiment evaluated the influence of growing media and fertilization on container stock quality, …

First-Principles Investigation Of Quasi-One-Dimensional Van Der Waals Magnets For Advancing Low-Dimensional Spintronics, Alyssa Horne

Dissertations, Master's Theses and Master's Reports

Van der Waals (vdW) magnets have been of great interest for advancing low- dimensional spintronics. A notable example is the quasi-one-dimensional (Q1D) vdW CrSbSe₃, as it is composed of individual one-dimensional units that are held together by the vdW forces. Finding other Q1D vdW magnets that exhibit non-metallic behavior together with long range ferromagnetic ordering is critical in developing next generation spintronics. Here in, using first-principles density functional theory (DFT), we investigate the compositional effects on electronic and magnetic behavior of Cr_1–xMn_xSbSe₃ (x = 0, 0.5, 1). When 50% of Cr is replaced …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Beyond Satisfaction: Developing A Data Storytelling Evaluation Protocol For Stem Equity Program Assessment, Karen Colbert

Dissertations, Master's Theses and Master's Reports

Higher education institutions routinely evaluate equity initiatives using measures of participation, engagement, and satisfaction. While these approaches provide useful information about program delivery, they offer limited insight into whether interventions change how participants understand institutional inequities. As a result, important dimensions of organizational learning and awareness often remain difficult to detect, particularly within STEM higher education environments where evaluation systems frequently emphasize measurable outputs over deeper indicators of change.

This dissertation examines how awareness-related outcomes can be identified, measured, and communicated within equity intervention contexts. Using a three-study design, the research first presents a systematic review of equity intervention evaluation …

Enhancing Coastal Vulnerability Assessments And Policy Impacts On Socioeconomic And Environmental Equity In Michigan's Great Lakes Communities, Esther N. Acheampong

Dissertations, Master's Theses and Master's Reports

Accelerating shoreline erosion, fluctuating lake levels, and climate-induced hazards are transforming the Great Lakes’ freshwater coasts, exposing the limitations of static and inequitable management frameworks. This dissertation investigates how Michigan’s coastal governance systems produce and manage vulnerability along the Lake Michigan shoreline by integrating geospatial modeling, institutional policy analysis, and environmental justice theory. It argues that both physical processes and institutional designs co-determine patterns of exposure, protection, and equity. The research begins by developing a refined Coastal Vulnerability Index (CVI) tailored for lacustrine environments, applying it to Muskegon County to assess how shoreline change, armoring, and seasonality influence localized risk. …

How To Build A Black Girl Traphouse:A Meditation And Manual For Black Feminist Survival In And Beyond The Academy, Loren Cahill, Brandyn-Dior Mckinley, Arianne Napier-White, Janae Peters, Jalisa Williams

School for Social Work: Faculty Publications

By design, the university is a colonizing, racializing, and classed space, built through unequal structures that perpetuate systemic violence (Peña, 2022). When many marginalized folks enter any university setting, they are marred by projections, judgments, assumptions, and assaults by those who question their worth, ability, and competence (y Muhs, Niemann, González, & Harris, 2012). Discriminatory actions and attitudes endured by Black women in academia often make us severely angry as well as mentally andphysically ill. Many of us are so traumatized that we choose to leave and/or are pushed out of our jobs. Those of us who choose to stay …

Reconciliation, Draper Matthews

Theses and Dissertations

This thesis exhibition, Reconciliation, examines how memory, loss, and lived experience shape personal identity over time. Through sculptural works composed of cast, blown, and hot-sculpted glass combined with mixed media, the exhibition explores the pressures that life events place upon individuals and the ways those pressures persist, transform, and become integrated into the self. The work considers identity not as a fixed state but as a continual process of negotiation between past experiences, present circumstances, and future possibilities.

Central to the project is the material analogy between glass and human experience. Glass, a material formed under extreme heat and pressure …

The Thing About Stuff: Exploring Consumerism Through Contemporary Print, Collage And Self-Reflection, Alexandra Lee Cox

Theses and Dissertations

The Thing about Stuff is an exhibition of editioned prints and book forms that pertain to personal and societal contradictions under capitalism. I use a combination of collage, design, print, traditional research and writing to form a better understanding of my place in capitalism by redefining my participation in it. Historical and contemporary research in combination with self-reflection and artmaking assists in my exploration of consumerism through the lens of human-object relationships. This body of work translates my own material desire for an audience through intentional composition, limited color pallets and intentional display. The accompanying supportive statement focuses on the …

Ai Systems For Physicians: A Review From Socio-Technical And Human-Computer Interaction Perspectives, Wu Jiaqi Young, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The adoption of artificial intelligence (AI) in healthcare is accelerating, yet successful implementations of physician-facing AI systems remain limited and uneven. This paper presents a literature review of 40 peer-reviewed studies published between November 2022 and November 2024, spanning clinical, technical, and human-computer interaction (HCI) domains. Anchored in a socio-technical perspective, the review examines our existing understanding of how technical design, user expertise, and organizational factors shape the effectiveness of AI systems in real-world clinical settings. Our analysis identifies two meta-themes: (1) context as a dynamic, multi-level influence that actively reshapes AI system behavior, and (2) trust as an emergent …

Thinkmatter: Panoramic-Aware Instructional Semantics For Monocular Vision-And-Language Navigation, Guangzhao Dai, Shuo Wang, Hao Zhao, Bin Zhu, Qianru Sun, Xiangbo Shu

Research Collection School Of Computing and Information Systems

Vision-and-Language Navigation in continuous environments (VLN-CE) requires an embodied robot to navigate the target destination following the natural language instruction. Most existing methods use panoramic RGB-D cameras for 360° observation of environments. However, these methods struggle in real-world applications because of the higher cost of panoramic RGB-D cameras. This paper studies a low-cost and practical VLN-CE setting, e.g., using monocular cameras of limited field of view, which means “Look Less” for visual observations and environment semantics. In this paper, we propose a ThinkMatter framework for monocular VLN-CE, where we motivate monocular robots to “Think More” by 1) generating novel views …

Memoryart: Enhancing Llms Via Multi-Memory Models With Adaptive Resonance Theory For Healthcare Agents, Renke Dai, Hebin Hu, Jiahui Zhang, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Though promising in healthcare consultation applications, large language models (LLMs) face critical limitations in retaining and utilizing long-term memory across multiturn interactions. In particular, existing memory enhancing paradigms are constrained by limited context windows and embedding-based retrieval, often failing to maintain task relevance and still suffering from memory prototype collapse in multi-turn healthcare consultation. To address these challenges, we propose a cognitively-inspired memory framework named MemoryART, which is grounded in Adaptive Resonance Theory (ART)—a cognitive and learning theory of how humans and animals adapt to dynamic environments. MemoryART employs three memory modules—working memory, episodic memory, and semantic memory to support …

Gui Test Migration Via Abstraction And Concretization, Yakun Zhang, Chen Liu, Xiaofei Xie, Yun Lin, Jin Song Dong, Dan Hao, Lu Zhang

Research Collection School Of Computing and Information Systems

GUI test migration aims to produce test cases with events and assertions to test specific functionalities of a target app. Existing migration approaches typically focus on the widget-mapping paradigm that maps widgets from source apps to target apps. However, since different apps may implement the same functionality in different ways, direct mapping may result in incomplete or buggy test cases, thus significantly impacting the effectiveness of testing the target functionality and the practical applicability of migration approaches.In this article, we propose a new migration paradigm (i.e., the abstraction-concretization paradigm) that first abstracts the test logic for the target functionality and …

Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Analysis Theories On Artificial Intelligence, Chatgpt, Data Science, And Metaverse: The Case Of Digital Medicine, Yin Yang, Xingyun Liu, Jorge Luis Cuyubamba Dominguez, Yuan Fang, Wen Xie, Bairong Shen, Keng Siau

Research Collection School Of Computing and Information Systems

Healthcare organizations are increasingly adopting digital technologies, with Artificial Intelligence (AI), Data Science, and the metaverse driving significant advancements in smart healthcare. Al facilitates personalized medicine and efficient drug development, while Data Science enables predictive analytics and big data management, enhancing patient outcomes and healthcare quality. The metaverse introduces immersive training and telemedicine platforms, revolutionizing patient engagement and healthcare research. This study conducts' a scoping review of 6,171 articles, analyzing the transformational impact of AI, ChatGPT, Data Science, and the metaverse on healthcare. It highlights the benefits and risks of these technologies, identifies research gaps in their application within the …

Towards Secure Program Partitioning For Smart Contracts With Llm’S In-Context Learning, Ye Liu, Yuqing Niu, Chengyan Ma, Ruidong Han, Wei Ma, Yi Li, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging because they stem from inherent data confidentiality issues rather than straightforward implementation bugs. To tackle this by preventing sensitive information leakage, we present PARTITIONGPT, the first LLM-driven approach that combines static analysis with the in-context learning capabilities of large language models (LLMs) to partition smart contracts into critical (privileged) and normal codebases, guided by a few annotated sensitive data variables. We evaluated PARTITIONGPT on 18 annotated smart contracts containing 99 sensitive functions. The results demonstrate that PARTITIONGPT successfully generates …

Clique Annealing: Semi-Supervised Community Detection Under Crystallization Kinetics, Ling Cheng, Jiashu Pu, Ruicheng Liang, Qian Shao, Hezhe Qiao, Feida Zhu

Research Collection School Of Computing and Information Systems

Semi-supervised community detection seeks to find a specified community type when only few communities are labeled. Existing "select-then-refine" pipelines often start from mis-aligned cores and rely on Reinforcement-Learning or Generative Adversarial Network, increasing computational cost and limiting scalability. We address these issues with a unified energy framework under crystallization kinetics that jointly models energy, structure, and growth. Based on this perspective, we propose CLique ANNealing (CLANN), which first employs Nucleus Proposer to select candidate clique as community core under four physics-inspired criteria. A learning-free Transitive Annealer then iteratively merges neighboring cliques and repositions the nucleus, enabling spontaneous, scalable community growth. …

Airaclex: Automated Detection Of Price Oracle Manipulations Via Llm-Driven Knowledge Mining And Prompt Generation, Bo Gao, Yuan Wang, Qingsong Wei, Yong Liu, Rick Siow Mong Goh, David Lo

Research Collection School Of Computing and Information Systems

Decentralized finance (DeFi) applications depend on accurate price oracles to ensure secure and fair transactions. However, poorly integrated oracles remain susceptible to manipulation, enabling attackers to exploit smart contract logic for unfair asset valuation and financial gain. While many such vulnerabilities are only detected after deployment, smart contracts are typically immutable once deployed, making post-hoc fixes costly or infeasible. This highlights the critical need for detecting oracle manipulation risks before deployment. In this paper, we propose AiRacleX, a novel LLM-driven framework that enables pre-deployment detection of price oracle manipulation vulnerabilities by leveraging the complementary strengths of multiple large language models …

Purified Zero-Shot Sketch-Based Image Retrieval, Yang Zhou, Jingru Yang, Jin Wang, Kaixiang Huang, Guodong Lu, Shengfeng He

Research Collection School Of Computing and Information Systems

Sketches, as a new solution in multimedia systems that can replace natural language, are characterized by sparse visual cues such as simple strokes that differ significantly from natural images containing complex elements such as background, foreground, and texture. This misalignment poses substantial challenges for zero-shot sketch-based image retrieval (ZS-SBIR). Prior approaches match sketches to full images and tend to overlook redundant elements in natural images, leading to model distraction and semantic ambiguity. To address this issue, we introduce a distraction-agnostic framework, purified cross-domain matching (PuXIM), which operates on a straightforward principle: masking and matching. We devise a visual-cross-linguistic (VxL) sampler …

Portfoliopilot: An Agentic Platform For Financial Portfolio Management Algorithm Development And Evaluation, Jared Chan Xu Yang, Haokai Ma, Yunshan Ma

Research Collection School Of Computing and Information Systems

Developing new portfolio-management algorithms typically demands substantial programming effort, limiting rapid experimentation and excluding finance professionals without coding skills. Current robo-advisory tools offer pre-built but rigid strategies, restricting customization and experimentation. We introduce PortfolioPilot, an open-source, agentic platform that enables users to generate bespoke portfolio through natural-language descriptions. Leveraging the Anthropic Claude API, PortfolioPilot dynamically synthesizes executable TypeScript algorithms that run in the frontend with security validation. The system integrates real-time backtesting with historical market data, classical optimization algorithms (Markowitz, LSTM, ARIMA), and interactive performance visualizations.

Nondeterministic Polynomial-Time Problem Challenge: An Ever-Scaling Reasoning Benchmark For Llms, Chang Yang, Ruiyu Wang, Junzhe Jiang, Qi Jiang, Qinggang Zhang, Yanchen Deng, Shuxin Li, Shuyue Hu, Bo Li, Florian T. Pokorny, Xiao Huang, Xinrun Wang

Research Collection School Of Computing and Information Systems

Reasoning is the fundamental capability of large language models (LLMs). Due to the rapid progress of LLMs, there are two main issues of current benchmarks: i) these benchmarks can be crushed in a short time (less than 1 year), and ii) these benchmarks may be easily hacked. To handle these issues, we propose the ever-scalingness for building the benchmarks which are scaling over complexity against crushing, instance against hacking and exploitation, oversight for easy verification, and coverage for real-world relevance. This paper presents Nondeterministic Polynomial-time Problem Challenge (NPPC), an ever-scaling reasoning benchmark for LLMs. Specifically, the NPPC has three main …

Hpv Vaccination Learning Project: Final Report, Zaldy Collado, Homer Yabut, Jerome Cleofas, Rowalt Alibudbud, Marites Tiongco, Pilar Ramos-Jimenez, Cecile Lantican, Maria Margareth Geluz, Bernard Daniel Esseo, Jheraldo Salmasan, Sean Rex Iii

SDRC Projects

The HPV Vaccination Learning Project examined the factors that influence HPV vaccination among adolescent girls in selected Philippine communities. The research team adapted the BeSD survey and interview tools through two rounds of field testing that incorporated cognitive interviews. From August to October 2025, the team conducted 400 caregiver surveys and 120 in-depth interviews across 10 sites in Ilocos Norte, Abra, Santiago City in Isabela, and Navotas City. Interview participants included 30 parents, 30 adolescent girls, 30 teachers, and 30 barangay health workers.

Caregivers generally reported high awareness of the HPV vaccine and strong trust in health workers. Concerns about …