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Assessing Arterial Compliance: Utilizing A Surrogate Arm Bench Top Model For Oscillometric Blood Pressure Monitoring, Krystal Cardenas

Master's Theses

A study was conducted to evaluate the compliance of artificial artery systems utilizing an adaptation of the Yong-Geddes Surrogate Arm model, composed of a blood pressure cuff, artificial artery, pressure transducers, and flow to replicate physiological conditions to validate oscillometric non-invasive blood pressure measurement methods. The experiment phases included tube, blood pressure cuff, and the surrogate arm compliance tests both in static and dynamic conditions. Tube compliance tests showed that larger diameters resulted in increased compliance, with Sample 1 (smaller inner diameter, ID) resulting in an average compliance of 0.0912 mL/mmHg, and Sample 2 (bigger ID) resulting in 0.1597 mL/mmHg. …

Adopting Permissioned Blockchain Models To Enhance Consumer Protection And Comply With Consumer Protection Laws, Erika Buenrostro

Featured Student Work

Blockchain technology enables decentralized, peer-to-peer transactions and data management, offering transparency while raising data privacy and consumer protection concerns. As the current administration promotes blockchain adoption, including cryptocurrency, more users and businesses will likely integrate the technology. This thesis provides a framework to help businesses adopt blockchain while ensuring compliance with the California Consumer Privacy Act (CCPA). To prevent data mishandling and legal penalties, consumers and businesses must stay informed about the risks and evolving state privacy laws.

A CCPA-compliant approach retains blockchain’s benefits through a permissioned model, storing only non-personal (neutral) data on-chain while keeping personal information off-chain in …

A Meta-Analysis Of Technology Usage In Word Problem Solving Interventions For Elementary Students: An Application Of The Samr Model, Joelle Prate, Jennifer E. Kong, Lamiya Hoque, Trisha Sugita, Tanya Belom

Education Faculty Articles and Research

This meta-analysis assessed the effect of the usage of technology in math interventions on the math achievement of students in kindergarten to the fifth grade. The SAMR (Substitution, Augmentation, Modification, Redefinition) (Puentedura, 2006) model was applied to evaluate the degree of technology integration within the math intervention. Twelve group studies met the criteria for inclusion in this meta-analysis. Overall, technology interventions yielded a significant positive effect on the math achievement of elementary-aged students with learning disabilities (LD) (ES = 1.34). While no significant differences in effect sizes were found by function of the SAMR model, the studies that utilize technology …

The Present And Future Of Ai: Ethical Issues And Research Opportunities, Ankita Srivastava, Marco Marabelli, Danielle Blanch-Hartigan, Jeffrey Moriarty, Evan Carey

Philosophy Faculty Publications

Healthcare is currently a fast-changing industry with AI and generative AI (GenAI) playing a prominent role in the transformation of clinical as well as managerial practices. Clinical practices involve AI to diagnose diseases and develop new drugs and compounds, while managerial practices concern AI-supporting processes such as billing patients and insurance companies, handling electronic medical records, and supporting remote connections with patients, increasingly using virtual and augmented reality. Yet, all these opportunities offered by AI come with challenges involving potential ethical issues, such as discrimination, bias, lack of accessibility, and privacy issues. In March 2024, we organized a panel with …

Research Update - March 2025, Office Of Research

Research Update

No abstract provided.

If You Were A Sesame Street Character, Which One Would You Be? Natural Language Processing And Personality With Big Bird And Friends, Joseph Uran Meyer

Doctoral Dissertations

This paper examined and compared several natural language processing and machine learning techniques in predicting self-reported Big Five personality traits from text responses. The models were validated on the open-source 2019 SIOP Machine Learning Competition dataset (N = 1,689). The techniques evaluated included bag-of-words, Empath dictionary, LSTM networks, fine-tuning Transformer models, and stacked generalization. Results indicated that the present study’s models had lower error in four of the five constructs analyzed. Limitations of the study include use of an MTurk sample and small sample size. Future research should explore similar techniques on larger applicant samples. Practical implications and contributions to …

A Feedback-Guided Analysis Of Environmental, Health And Socio-Economic Factors Affecting Drivers’ Willingness To Shift To E-Jeepneys, Charlotte Kendra Gotangco Gonzales, Katrina Abenojar, Carlos Rosauro Manalo, Melliza Templonuevo Cruz, Maria Obiminda L. Cambaliza, James Bernard Simpas, Imee Delos Reyes, John Wong, Bernell Go, Krizelle Cleo Fowler, Rene Marlon Panti, Emma E. Porio, Jean Jardeleza Mijares

Environmental Science Faculty Publications

The Jeepney Modernization Program involves the replacement of traditional jeepneys with more efficient alternatives, including modern enclosed electric vehicles, alongside operational improvements to the public transportation system. This study aims to assess the environmental, health and socio-economic factors impacting drivers’ willingness to shift to e-jeepneys. Feedback-Guided Analysis was used as a framework for designing an interdisciplinary approach towards understanding the decision-making paradigms of drivers plying a specific route in Quezon City, Metro Manila. Measurements of drivers’ exposure to PM2.5 and associated health parameters were complemented by key informant interviews delving into income, expenses, valuation of benefits and decision-making paradigms. A …

Aged 539 Graduate Internship Report - Avenal High School, Ryan D. Deaver

Agricultural Education: Graduate Internship Reports

This report includes documentation that Avenal High School meets the quality criteria required for High School Agriculture Education Programs. The documents are used for reviewing a school as well as applying for grant funding through the Agriculture Incentive Grant. There are supporting documents provided to show proof of things that are being done as well as areas that may need improvement.

Artificial Intelligence In Higher Education Accreditation: Advancing Quality, Accessibility, And Special Education Inclusion, Jacques D. Singleton

Teacher Education Faculty Publications

Artificial Intelligence (AI) is transforming higher education accreditation by enhancing quality assurance, accessibility, and inclusion. Traditional accreditation relies on manual evaluation, but AI- driven tools improve efficiency through realtime data analysis, predictive insights, and automation. This chapter explores AI’s role in adaptive learning, automated accessibility tools, and predictive analytics for student success, with a focus on supporting students with disabilities and ensuring compliance with accessibility standards. Ethical concerns, including bias, privacy, and transparency, are addressed to ensure AI complements human judgment. Through case studies and policy recommendations, this chapter provides a roadmap for institutions and accrediting bodies to integrate AI …

The Virtual Wunderkammer: Integrating Neuroinclusive Design And Ai-Augmented Technologies For Immersive Museum Experiences, Piper Hutson, James Hutson

Faculty Scholarship

The Virtual Wunderkammer represents an innovative paradigm in museum exhibition design, integrating neuroinclusive principles with artificial intelligence (AI)-augmented technologies to foster immersive and cognitively accessible visitor experiences. Historically, the Wunderkammer, or "cabinet of curiosities," served as a precursor to modern museums, offering eclectic collections that stimulated intellectual curiosity and sensory engagement. The contemporary reimagining of this concept utilizes emerging technologies such as augmented reality (AR), virtual reality (VR), haptic feedback, and olfactory-enhanced digital environments to create personalized, adaptive museum experiences. This study explores the critical intersection of neuroaesthetics, cognitive science, and AI-driven interactivity in digital exhibitions, emphasizing their potential to …

Solid-State Crystallization Of Zeolites And Their Use In Plastic Upcycling Applications, Yixin Liao

Doctoral Dissertations

Plastics have been an irreplaceable component of modern technology as well as everyday life. They have brought much convenience to us with their characteristics of great malleability, durability, and stability. The versatile and low-cost nature of plastics also enables their wide engagement in many modern industries including automobile, medical, communication as well as aerospace. Polyethylene (“PE”), made from polymerization of ethylene, is one of the most widely used plastics in the world. Being cheap, flexible, and long-lasting, they are extensively used in the packaging industry, especially for plastic bags and other sorts of containers. However, the durability of plastics, on …

Smoothed Particle Hydrodynamics For Free-Surface Flows And Time Series Forecasting Approach For Computational Fluid Dynamics, Huali Ye

Doctoral Dissertations

With the increase in computing power, numerical simulation has become an essential approach to solving problems in engineering and science. Numerical simulations provide a platform for theoretical validation and facilitate novel discovery. Even though extensive mesh-based numerical methods are utilized, significant limitations exist, particularly in Computational Fluid Dynamics (CFD). Because of the grid distortion, issues related to large deformations, moving interfaces, and free surfaces may lead to considerable computational errors, constraining their efficacy in numerous applications. As a mesh-free method, Smoothed Particle Hydrodynamics (SPH) was introduced in 1977 and has been widely applied in many fields such as astrophysics and …

Best Strategies For Bilingual Education: How Can We Explain Their Success?, Claudia Cabrera, Olga Kosheleva, Christian Servin, Vladik Kreinovich

Departmental Technical Reports (CS)

When designing AI-based tools for education, it is important to take into account the experience of human teachers. In this, it is necessary to distinguish between the education features that are justified by the general features of the corresponding education task -- these features should be taken into account in AI-based learning as well -- and features which are specific for traditional non-AI teaching. In this paper, on the important example of bilingual education, we show that several empirically successful teaching strategies can be explained in the general context -- and thus, should be implemented in AI-based teaching as well.

Novel Approach To Traveling-Wave-Based Fault Location In Nonhomogeneous Transmission Lines, John Parker Burrell

Master's Theses

Accurate fault location is a critical aspect of power system protection, ensuring grid reliability and minimizing downtime. Traditional traveling-wave-based fault location methods face limitations when applied to nonhomogeneous transmission lines due to the reliance on precise segment velocities and propagation time data. This thesis addresses these challenges by proposing a novel algorithm that leverages historical fault data to estimate segment velocities and refine these estimates as more faults occur. The algorithm was rigorously tested using the digital model of an 11-segment, 65.694 km real overhead transmission line and validated using both simulations and hardware tests using commercially available time-domain protective …

Integrating Three-Dimensional Mentoring With Workforce Development Training: A Collaborative Autoethnographic Examination Of Skill Transfer, Danny L. Darden, Ramiro Pesina

Human Resource Development Student Publications and Presentations

The increasing demand for skilled professionals in technical fields necessitates innovative educational approaches that integrate skill development with effective mentoring frameworks. This paper presents an autoethnographic analysis of skill transfer within workforce development environments, emphasizing a three-dimensional mentoring model encompassing cognitive, emotional, and behavioral mentoring dimensions. The study examines applications in command-line learning, gamified instruction, and safety training within virtual environments. The research highlights best practices in mentoring sustainability, the role of technology in reinforcing skill acquisition, and the ways in which learning-community engagement enhances workforce readiness. Additionally, this study integrates research on student engagement, community experiences, and retention strategies, …

Flexible Work, Rigid Discrimination, Natalia Ramírez Lee

Center for Racial and Economic Justice

No abstract provided.

Gap Filling Crowdsourced Air Temperature Data In Cities Using Data-Driven Approaches, Miao He, Zhiwen Luo, Xiaoxiong Xie, Peng Wang, Haichao Wang, Gabriela Zapata-Lancaster

School of Art, Design and Architecture

Crowdsourced temperature data from citizen weather stations (CWS) in urban area offer valuable insights into intra-urban temperature distribution but are often challenged by a significant number of missing values. Existing gap-filling methods, typically effective for random gaps and low missing rates, are inadequate for the continuous gaps and high missing rates common in CWS recordings. This study introduces a novel data-driven approach to fill these gaps by modelling relationships between CWS data and official weather station (OWS) records during periods of data availability. We evaluate various feature sets and data-driven algorithms, including Multiple Linear Regression (MLR), Random Forest (RF), and …

University Of San Diego Magazine Spring 2025, University Of San Diego

University of San Diego Magazine (1992- )

Shared Space; Confronting COVID; Growing a Legacy of STEM at USD; The Camino Will Provide; Around Alcalá Park; At the Edge of It All; Faith in Action; Global Perspectives; Torero Athletics; Toreros Making Waves; In Memoriam; Leading with Love

Smart Highway Construction Site Monitoring Using Artificial Intelligence, Mehran Mazari, Yahaira Nava-Gonzalez, Ly Jacky N. Nhiayi, Mohamad H. Saleh

Mineta Transportation Institute

Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. …

School Principal Professional Development: A Case Study Of A Texas Rural School District, Deborah Nicole Wills Covault

Electronic Theses and Dissertations

The purpose of this study was to describe professional development experiences in one rural school district in Texas as perceived by the campus administrators. Existing research has implied a disconnect between preparation programs and campus administration practices. Rural school administrators experience a lack of access to professional development opportunities throughout the school year due to the distance of their community to urban cities hosting training opportunities, funding, and school leadership infrastructure. Due to the increase in federal, state, and local demands, the role of the educational leader has become more complex as the demand for administrators to recruit and retain …

Offline Safe Reinforcement Learning Using Trajectory Classification, Ze Gong, Akshat Kumar, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Offline safe reinforcement learning (RL) has emerged as a promising approach for learning safe behaviors without engaging in risky online interactions with the environment. Most existing methods in offline safe RL rely on cost constraints at each time step (derived from global cost constraints) and this can result in either overly conservative policies or violation of safety constraints. In this paper, we propose to learn a policy that generates desirable trajectories and avoids undesirable trajectories. To be specific, we first partition the pre-collected dataset of state-action trajectories into desirable and undesirable subsets. Intuitively, the desirable set contains high reward and …

Occlusion-Insensitive Talking Head Video Generation Via Facelet Compensation, Yuhui Deng, Yuqin Lu, Yangyang Xu, Yongwei Nie, Shengfeng He

Research Collection School Of Computing and Information Systems

Talking head video generation involves animating a still face image using facial motion cues derived from a driving video to replicate target poses and expressions. Traditional methods often rely on the assumption that the relative positions of facial keypoints remain unchanged. However, this assumption fails when keypoints are occluded or when the head is in a profile pose, leading to inconsistencies in identity and blurring in certain facial regions. In this paper, we introduce Occlusion-Insensitive Talking Head Video Generation, a novel approach that eliminates the reliance on spatial correlation of keypoints and instead leverages semantic correlation. Our method transforms facial …

Adapting Knowledge Prompt Tuning For Enhanced Automated Program Repair, Xuemeng Cai, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Automated Program Repair (APR) aims to enhance software reliability by automatically generating bug-fixing patches. Recent work has improved the state-of-the-art of APR by fine-tuning pre-trained large language models (LLMs), such as CodeT5, for APR. However, the effectiveness of fine-tuning be-comes weakened in data scarcity scenarios, and data scarcity can be a common issue in practice, limiting fine-tuning performance. To alleviate this limitation, this paper adapts prompt tuning for enhanced APR and conducts a comprehensive study to evaluate its effectiveness in data scarcity scenarios, using three LLMs of different sizes and six diverse datasets across four programming languages. Prompt tuning rewrites …

Mimic: Ai And Ar-Enhanced Multi-Modal, Immersive, Relative Instruction Comprehension, Dhanuja Wanniarachchi, Archan Misra

Research Collection School Of Computing and Information Systems

We present a multimodal instruction comprehension framework, called MImIC, that utilizes visual sensing (including LIDAR and 2D RGB sensing) & AI spatial reasoning capabilities to support more seamless and immersive interaction between humans and AI-driven situated assistive agents. MImIC's key new capability is to support disambiguation of a wider set of relative spatial references that users naturally employ while issuing spatially-situated instructions. To support enhanced visual grounding via a combination of both fully-qualified and relative attribute references, MImIC uses (a) a fine-tuned transformer-based language translation DNN to accurately convert natural verbal commands into a structured set of machine understandable constraints …

Explainable Neural Networks With Guarantee: A Sparse Estimation Approach, Antoine Ledent, Peng Liu

Research Collection School Of Computing and Information Systems

Balancing predictive power and interpretability has long been a challenging research area, particularly in powerful yet complex models like neural networks, where nonlinearity obstructs direct interpretation. This paper introduces a novel approach to constructing an explainable neural network that harmonizes predictiveness and explainability. Our model is designed as a linear combination of a sparse set of jointly learned features, each derived from a different trainable function applied to a single 1-dimensional input feature. Leveraging the ability to learn arbitrarily complex relationships, our neural network architecture enables automatic selection of a sparse set of important features, with the final prediction being …

Personalizing Multimedia Content Recommendations For Intelligent Vehicles Through Text–Image Embedding Approaches, Jin A. Choi, Taekeun Hong, Kiho Lim

College of Communication and Media Scholarship and Creative Works

The ability to automate and personalize the recommendation of multimedia contents to consumers has been gaining significant attention recently. The burgeoning demand for digitization and automation of formerly analog communication processes has caught the attention of researchers and professionals alike. In light of the recent interest and anticipated transition to fully autonomous vehicles, this study proposes a text–image embedding method recommender system for the optimization of personalized multimedia content for in-vehicle infotainment. This study leverages existing pre-trained text embedding models and pre-trained image feature extraction methods. Previous research to date has focused mainly on textual-only or image-only analyses. By employing …

Exploring The Leadership Identity Development Of Emerging Leaders Who Have Answered The Call To Academic Administration Within U.S. Higher Education, J. "Clay" Hurdle, Nicole Lamee Perez Stedman, Matthew Sowcik, Sebastian Galindo, R. Elaine Turner

Journal of Educational Leadership in Action

Leadership identity (also known as leader identity) has been established as a sub-identity of general self-concept. A greater degree of leadership identity could have implications for leadership self-efficacy. Research on leadership identity development in the last 20 years has mostly been quantitative with limited qualitative efforts. Exploring the leadership identity development of academic leaders remains mostly absent from the literature. Using the Leadership Identity Development Model, a descriptive qualitative study was conducted with cohort members of two national academic leadership development programs, the Food Systems Leadership Institute and LEAD21. Interviews explored participants’ leadership identity development during their careers leading up …

Differences In Reading College Readiness By The Language Status Of Texas High School Students: A Statewide, Multiyear Analysis, Lidia Garza Calderón, John R. Slate, Tershundrea Branch, Clare A. Resilla

Journal of Educational Leadership in Action

The extend to which differences were present for Emergent Bilingual students and non-Emergent Bilingual students in their performance on the Texas state-mandated English I End-of-Course exam for the 2018-2019, 2020-2021, and 2021-2022 school years was examined. Specifically addressed was the extent to which Emergent Bilingual students and non-Emergent Bilingual students differed in their performance on three Grade Level performance standards: Approaches Grade Level standard, Meets Grade Level standard, and Masters Grade Level standard in the pre-pandemic year and the first and second-post-pandemic years. Non-Emergent Bilingual students had statistically significantly better English I End-of-Course exam performance than Emergent Bilingual students in …

Creating A School Climate Of Belonging And Engagement Through Visionary Leadership And Student Art, Jeff Irvine, Kyra Kristensen-Irvine

Journal of Educational Leadership in Action

This research adopted a case study methodology to investigate how student artwork helped establish a school climate that was intentionally inviting to students and the wider school community. Through the visionary leadership of two principals, a Kindergarten to Grade 5 school and a middle school enhanced their common areas through student visual arts projects. Previous research on school physical environments focused on safety, cleanliness, and noise levels. This paper addresses a research gap, identifying the role that physical environments played in promoting a positive school climate which in turn promoted students’ sense of belonging and engagement.

Algebra I End-Of-Course Exam Differences By The At-Risk Status Of Texas Hispanic Students: A Multiyear Statewide Investigation, Daniel Craft, John R. Slate

Journal of Educational Leadership in Action

Examined in this investigation was a comparison of the Algebra I End-of-Course exam performance between Hispanic students who were at-risk and Hispanic students who were not at-risk in the 2016-2017, 2017-2018, and 2018-2019 school years. Inferential statistical procedures yielded statistically significant differences in all three school years between these two groups of Hispanic students. In all three school years, higher percentages of Hispanic students who were at-risk did not meet the three grade level standards (i.e., Approaches Grade Level, Meets Grade Level, and Masters Grade Level) than Hispanic students who were not at-risk. Moreover, Hispanic students who were at-risk correctly …