Digital Commons Network^™

Social Engineering Scenario Generation For Awareness-Based Attack Resilience, Jade Webb

Master's Projects

Social engineering is found in a strong majority of cyberattacks today, as it is a powerful manipulation tactic that does not require the technical skills of hacking. Calculated social engineers utilize simple communication to deceive and exploit their victims, all by capitalizing on the vulnerabilities of human nature: trust and fear. When successful, this inconspicuous technique can lead to millions of dollars in losses. Social engineering is not a one-dimensional technique; criminals often leverage a combination of strategies to craft a robust yet subtle attack. In addition, offenders are continually evolving their methods in efforts to surpass preventive measures. A …

Cca Analysis Using Computer Vision Techniques, Rahul Thakur

Master's Projects

Coral reefs are an essential part of the marine ecosystem. They perform a wide variety of tasks, some directly and others indirectly. They can produce oxygen, absorb carbon dioxide, along with supporting ocean habitat. Crustose Coralline Algae (“CCA”) plays an important role in helping provide structural support to Coral Reef ecosystems. However, global warming is causing ocean water to become more acidic resulting in coral bleaching. This is leading to changes in coral environments and causing coral deaths at alarming rates. Object detection using computer vision techniques, specifically deep learning, can help to monitor coral reef health and identify CCA …

Smart: Semantic Mapping And Analysis For Regional Terrain Using Multi-Scale U-Net And Topsis, Rashmi Sonth

Master's Projects

Accurate land use classification is the backbone for urban planning. But with poor quality satellite images, varied landscapes and structures which are changing faster than ever, it becomes a challenge to define clear boundaries and hence to urban planning. This research explores the application of deep-learning model for land use classification and asses the suitability of the land. The proposed model combines a multi-scale U-Net architecture with Transformer blocks applied on a multi-spectral satellite images that improves the semantic segmentation greatly across the urban and rural regions. Additionally, a patch-wise segmentation is applied to overcome the common problem of feature …

Retrieval-Augmented Generation For Survival Analysis In Cancers: Methods And Evaluation On The Surveillance, Epidemiology, And End Results Database, Jyothi Vaidyanathan

Master's Projects

Healthcare is one of the most important fields that benefits from advancements in Artificial Intelligence (AI). From classic models like linear regression to cuttingedge transformers, AI is applied across various healthcare subdomains, such as drug discovery, predictive analytics, and personalized medicine, to name a few. These techniques enable medical practitioners to make more informed decisions, significantly improving both the speed and accuracy of diagnoses and treatments. Machine learning has played a transformative role in oncology, especially in areas like early detection, diagnosis, treatment planning, and patient monitoring, by analyzing medical images, clinical information, genomic data, sensor information. Our research aims …

Rul Estimation Of N-Cmapss Turbofan Engines Using Deep Learning With Customized Penalty And Expanded Sensors, Prathmesh Pethkar

Master's Projects

Accurate prediction of Remaining Useful Life (RUL) for aircraft engines is important to enhance maintenance efficiency and flight safety. For this project, a solution to RUL prediction on NASA's N-CMAPSS data set, mimicking realistic engine degradation under simulated full-flight scenarios, is being proposed. For addressing the high-dimensional noisy sensor data challenge, a new feature engineering pipeline was utilized. Models trained on healthy data predict normal sensor behavior, and the discrepancy between these predictions—referred to as residual features—is a measure of degradation. To handle the size and computational demands of the dataset, training was conducted on Google Cloud Platform using GPU-supported …

Smithian Merchant Towns And Good Government In The Wealth Of Nations, John B. Estill

Faculty Research, Scholarly, and Creative Activity

Commentators on Adam Smith’s Inquiry into the Nature and Causes of the Wealth of Nations often characterize Smith as a proponent of government in multiple areas, including security in person, property, contract, and some public goods. However, Smith understood government more expansively than people today. In volume I, book III, chapters I–IV, Smith describes the evolution of merchant towns in England that led to “good governance” that dismantled the feudal system. This limited government not only included the security provided by the formal laws and institutions. It also aligned the informal elements of individual civic ethics and self-reliance with the …

The Role Of Advocacy And Occupational Justice In Increasing The Accessibility Of Parks For Parents With Disabilities, Nathan Burke-Tan

Doctoral Projects

The purpose of this doctoral capstone project was to address ongoing accessibility barriers experienced by adults with disabilities, particularly those in caregiving roles, in public parks and playgrounds in the greater San Diego region. Although many parks meet the minimum requirements of the Americans with Disabilities Act (1990), research shows that caregivers with disabilities continue to encounter obstacles that limit safe, meaningful participation in community spaces (Dalpra, 2022; Fernelius, 2017; Firkin et al., 2024; Movahed et al., 2023; Ogletree et al., 2020; Prellwitz & Skar, 2007). These persistent gaps indicate a need for stronger advocacy and clearer public awareness of …

Grounded In Experience: A Collaborative Approach To Resource Development For Adults With Ehlers-Danlos Syndrome, Morgan Kam

Doctoral Projects

Background: Ehlers-Danlos syndrome (EDS) is a complex connective tissue disorder that significantly affects daily occupations, participation, and quality of life, yet early support for individuals pursuing or newly receiving a diagnosis remains limited. Occupational therapy (OT) is uniquely positioned to address these challenges through interventions that promote self-management and functional engagement.

Purpose: This project aimed to develop an experience- and evidence-informed educational resource for individuals undergoing or newly receiving an EDS diagnosis, while increasing awareness of OT’s role in managing this chronic, multisystemic condition.

Methods: A mixed-methods approach integrated qualitative insights from interviews, online support groups, and practitioner feedback. A …

Family-Level Impacts Of Equine-Assisted Occupational Therapy For Children With Disabilities: An Exploratory Mixed-Methods Pilot Study, Emily Canigiula

Doctoral Projects

Equine-assisted occupational therapy (EAOT) has been shown to enhance functional, social, and quality-of-life outcomes for children with disabilities (McDaniel Peters & Wood, 2017; Prieto et al., 2022). While child-focused outcomes are well documented, significantly less is known about how EAOT participation may influence caregivers and the broader family unit, as existing research largely prioritizes individual outcomes over family experiences (Peters et al., 2017; Tan & Simmonds, 2018; Trzmiel et al., 2019; Xiao et al., 2023). Emerging qualitative studies suggest potential family-level impacts including family engagement, reduced parental stress, and enhanced feelings of pride, empowerment, and connection (Kalmback et al., 2020; …

Bridging Gaps With Occupational Therapy: The Unique Role Of Occupational Therapy In Women’S Day Shelters, Alex Sato

Doctoral Projects

Homelessness is a multifaceted, complex issue that we face as a society. Mainstream services provided to homeless or vulnerable populations tend to focus on housing and basic services. While these are essential and meaningful, literature suggests there is a lack in trauma and self-care support (Marzana et al., 2023; Milaney et al., 2020). Looking through an Occupational Therapy (OT) lens, there are a multitude of ways the profession can provide holistic care. Current OT service provision within this population most commonly focuses on obtaining and maintaining housing and addressing the survival occupations these individuals may be engaging in (Cunningham & …

Applying Occupational Empowerment Principles In A Life Skills Program For Unhoused Transitional-Aged Youth: Feasibility And Early Outcomes, Eriza Navarro

Doctoral Projects

The purpose of this occupational therapy doctoral capstone project was to address a gap in community-based services for unhoused transitional-aged youth (TAY) by promoting life skill acquisition and supporting participation in meaningful activities in order to enhance self-efficacy. This project aimed to design, implement, and evaluate a structured occupation-based life skills program that builds upon existing services at a local drop-in center. The program incorporated life skill education and activity-based, experiential interventions tailored to meet the needs and learning styles of the population. Methods included conducting a needs assessment, developing the program curriculum, and piloting the 6-week program consisting of …

Promoting Participation And Self-Efficacy Among Youth With Disabilities In Community-Based Vocational Education, Allison Hollender

Doctoral Projects

Occupational therapy, with its focus on participation, contextual adaptation, and strength-based practice, is uniquely suited to support the growth and inclusion of youth in transition (Angell et al., 2018; Cahill et al., 2020; Carroll et al., 2025). Research indicates that transitional-aged youth (TAY) with disabilities, ages 14-24, are less likely to graduate from high school, pursue postsecondary education, or live independently (BLS, 2024; Cheng & Shaewitz, 2022; Cook et al., 2015). These disparities are compounded by occupational deprivation, or limited opportunities for meaningful participation, which can negatively impact long-term self-efficacy and belonging (Arbesman & Logsdon, 2011; Cahill et al., 2020). …

From Silos To Synergies: How To Enhance Interdisciplinary Collaboration Among Graduate Students, Jennifer Jimenez

Doctoral Projects

Interprofessional education (IPE) is essential for preparing collaborative healthcare practitioners, yet opportunities at San José State University (SJSU) have been limited, inconsistent, and largely dependent on individual faculty initiative. This capstone project aimed to strengthen IPE at SJSU by assessing institutional capacity and developing feasible, sustainable strategies to enhance exposure and participation across health-related programs. Guided by the Person–Environment–Occupation–Performance (PEOP) model and adult learning theory, the project combined a needs assessment, literature review, and partnership with the Healthy Development Community Clinic (HDCC) to create an instructor implementation guide and student introductory modules for HDCC service-learning onboarding. An IRB-approved mixed-methods faculty …

A Guide To Falls In A Skilled Nursing Facility, Sarah Ghione

Doctoral Projects

Approximately one in four older adults experiences a fall each year in the United States (Centers for Disease Control and Prevention [CDC], 2024b; Kakara et al., 2023). Among those residing in nursing homes for either short-term rehabilitation or long-term care, the risk of falls is doubled (Acker & Janssen, 2017; Shao et al., 2023). The purpose of this doctoral capstone project was to develop an educational resource aimed at enhancing staff education and fall prevention efforts within a single nursing home, supporting the facility’s goal of reducing fall rates. Methods included a needs assessment, observational experiences, resource development, and the …

Advancing The Environmental Dna And Rna Toolkit For Aquatic Ecosystem Monitoring And Management, Xavier Pochon, Holly A. Bowers, Anastasija Zaiko, Susanna A. Wood

Faculty Research, Scholarly, and Creative Activity

The application of environmental DNA (eDNA) and RNA (eRNA) technologies to aquatic ecosystem monitoring and management has increased rapidly in the last decade. These methods are providing many new and exciting opportunities for enhanced biodiversity assessment, ecological health evaluation, and species detection. This special issue of PeerJ Life and Environment brings together 20 innovative studies that collectively advance the eDNA toolkit. Four key themes are covered: (i) Methodological advancements, (ii) Ecological health assessments and biomonitoring, (iii) Species detection, and (iv) Application and management. The studies cover a suite of topics including; optimizing sample collection, developing species-specific assays, evaluating bioindicator species, …

Grand Challenges For Human Factors And Ergonomics, Waldemar Karwowski, Gavriel Salvendy, Mica Endsley, William Rouse, Paul Salmon, Kay Stanney, Andrew Thatcher, Tony Andre, Jessie Yang, Hasan Ayaz, Ahmet Cakir, Vince Duffy, Colin Drury, Qin Gao, Yinni Guo, Peter Hancock, William S. Marras, Patrick Rau

Faculty Research, Scholarly, and Creative Activity

Contemporary society faces a growing set of complex global issues representing significant human health, well-being, and sustainability threats. Human Factors and Ergonomics (HFE) has a critical role to play in responding to these issues; however, there remain a set of grand challenges that require resolution. This paper presents and discusses six grand challenges for HFE and related key research thrust areas for each of the challenges. The grand challenges are (1) Evolution in Societal Thinking; (2) Future of Human Work in Industry 5.0; (3) Climate Change and Sustainability; (4) Future of Education and Training; (5) Future of Personalized Health, and …

A Privacy-Preserving Federated Learning Approach For Airline Upgrade Optimization, Sien Chen, Yinghua Huang

Faculty Research, Scholarly, and Creative Activity

Purpose: A key issue of making upgrade decisions is to match the most relevant upgrade offers to the right customers at the right time. To optimize upgrade strategies and profitability, companies seek to break “data silos” between themselves and other business partners for a more holistic view of customers' consumption experiences. However, multi-source data fusion may lead to potential privacy leakage. To overcome these two challenges in data silos and privacy protection, this study introduced a privacy-preserving federated learning (FL) approach and explained the process of using FL in modeling airline passengers’ willingness to pay for upgrade offers. Design/methodology/approach: Federated …

Using A Sober Curious Framework To Explore Barriers And Facilitators To Helping Sexual Minority Women Reduce Alcohol-Related Harms: Protocol For A Descriptive Study, Tonda L. Hughes, Lauren Bochicchio, Laurie A. Drabble, Belinda Lunnay, David Whiteley, Jillian R. Scheer, Beth Meadows, Paul Ward, Carol Emslie

Faculty Research, Scholarly, and Creative Activity

Background: Globally, women consume less alcohol than men, but alcohol consumption among women has declined less in recent years than among men. Drinking rates and alcohol-related harms vary substantially across population groups of women, and sexual minority women (eg, lesbian, bisexual, and queer) are at notably high risk. An emerging body of literature suggests that in addition to minority stress (eg, stigma, discrimination), drinking norms and drinking cultures likely influence sexual minority women’s drinking. Almost no research has explored these factors as possible targets of interventions. Sober curiosity is a rapidly growing wellness movement that may be particularly salient for …

Validation Of A Self-Fitting Over-The-Counter Hearing Aid Intervention Compared With A Clinician-Fitted Hearing Aid Intervention: A Within-Subjects Crossover Design Using The Same Device, Lucas S. Baltzell, Kosta Kokkinakis, Amy Li, Anusha Yellamsetty, Katherine Teece, Peggy B. Nelson

Faculty Research, Scholarly, and Creative Activity

In October of 2022, the US Food and Drug Administration finalized regulations establishing the category of self-fitting over-the-counter (OTC) hearing aids, intended to reduce barriers to hearing aid adoption for individuals with self-perceived mild to moderate hearing loss. Since then a number of self-fitting OTC hearing aids have entered the market, and a small number of published studies have demonstrated the effectiveness of a self-fitted OTC intervention against a traditional clinician-fitted intervention. Given the variety of self-fitting approaches available, and the small number of studies demonstrating effectiveness, the goal of the present study was to evaluate the effectiveness of a …

Impact Of Sensory Organization Tasks On Prefrontal Cortex Activity In Older Women: A Comparative Fnirs Study Of Osteoarthritis And Healthy Aging, Alka Bishnoi, Yang Hu, Manuel E. Hernandez

Faculty Research, Scholarly, and Creative Activity

Introduction: Osteoarthritis (OA), a prevalent musculoskeletal condition, is associated with an increased risk of falls. Maintaining posture relies on visual, vestibular, and proprioceptive inputs, but these systems can be compromised due to aging or disease, heightening fall risk. Such impairments may result from neuromuscular decline and reduced cognitive or visuospatial processing abilities. This study aimed to investigate prefrontal cortical (PFC) activation patterns during clinical sensory organization tasks (SOT) using functional near-infrared spectroscopy (fNIRS) in older women with OA and healthy controls (HOA). We hypothesized that PFC activation would increase as SOT conditions became more challenging, but that increases would be …

Stream Response To A Dam Removal: Mill Creek, Davenport, Ca, Jessica J. Williamson

Master's Theses

Dams have many effects on stream morphology and ecology, including a loss of sediment supply downstream, reduced access to the entire stream for aquatic fauna, and a flooded area upstream of the dam. Dams are a hurdle for migrating organisms such as anadromous fish, which is a group of concern. An over 100-year-old dam on Mill Creek, a stream draining a coastal watershed in central California, was removed in the fall of 2021. The site is in the Santa Cruz Mountains, where endangered salmonids such as steelhead, Oncorhynchus mykiss, have historically lived. To study the change in the stream from …

Why We Need To Fill In Our Mixed-Use Communities’ Business Vacancies And How We Can Do That, Victor Huynh

Master's Projects

This planning report provides an in-depth exploration as to why so many mixed use communities, including transit-oriented developments, in metropolitan regions across the country are facing challenges with filling in their retail business vacancies at the ground floor. It also provides a current snapshot of best practices to remedy this widespread barrier to cities functioning more effectively and sustainably. This report provides a combination of findings from a literature review which identifies the most common reasons and remedies for business vacancies, and a research design which identifies which urban planning or urban design characteristics correlate most frequently with case sites …

Equity In Public Budgeting: Community Engagement In Morgan Hill, Ariana Perez

Master's Projects

Through this research, I will examine what citizen participation strategies have been implemented and their role and effectiveness in addressing wealth inequities. My research will explore these topics and examine what programs and policies the City of Morgan Hill can implement to increase residents' sense of belonging and ultimately push for greater social equity. My primary research question is, what are the programs and policies that the City of Morgan Hill can implement to engage immigrant communities, specifically Spanish-speaking residents, and low-income residents in shaping decisions around public investments and funding? This project will serve as a needs assessment to …

Multimodal Feature Fusion And Machine Learning For Adhd Detection Using Neuroimaging Data, Isabel Pham

Master's Projects

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopment disorder that can significantly affect a person’s attention, impulse control, and executive function. Currently, the traditional diagnosis method often relies on clinical assessments and observations. However, these methods can be subjective and lead to inconsistencies in diagnosis between individuals. To address this challenge, neuroimaging and machine learning (ML) are promising tools for providing a more objective diagnosis of ADHD. The goal of this project is to apply a multimodal approach in which structural and functional features of specific regions of the brain are used to develop a more accurate and objective …

Real-Time Adaptive Framework For Topic Modeling In Social Engineering Attacks, Manav Bhasin

Master's Projects

Detecting social engineering attempts is crucial for security, as these threats are becoming more frequent and increasingly exploit human vulnerabilities. This research focuses on topic modeling using conversational data from Kevin Mitnick’s ”The Art of Deception” with dialogues that illustrate various social engineering strategies. The dataset comprises manually extracted and synthetically augmented conversations to ensure natural dialogue flow. Two methodologies are presented for utterance-level and global topic extraction: prompt engineering leveraging OpenAI’s GPT-4o-mini, characterized by few-shot learning and chain-of-thought prompting, and Quantized Low Rank Adaptation (QLoRA) utilizing Mistral’s 7B instruct model for efficient fine-tuning. Through experimentation and evaluation, this study …

Simple Vs. Complex Human Activity Classification Via Hybrid Machine Learning Models, Anusha Kukreja

Master's Projects

In-depth understanding of the complexity of daily human activities is crucial for building responsive health monitoring and assistive technologies. However, limited research has focused on distinguishing activities based on their involvement level, as most existing work classifies only the type of activity performed. In this thesis, we address this gap by proposing a method to classify human activities as either simple or complex using sensor data from the Opportunity dataset. We define complex activities as those involving object interactions or multiple coordinated movements (e.g., drinking from a cup, cleaning a table), and simple activities as static or low-effort postures (e.g., …

Augmenting Missing Sensor Data For Robust Human Activity Recognition, Suryakangeyan Kandasamy Gowdaman

Master's Projects

Applications of ubiquitous computing, including health monitoring, sports analytics, and ambient-assisted living, rely on Human Activity Recognition (HAR) using wearable sensors. However, model robustness is challenged by missing sensor values, class imbalance, inter-subject variability, and temporal noise. This work proposes a complete HAR pipeline that addresses these challenges through sampling, time-series augmentation, dynamic feature handling, and GAN-PCA-based imputation. Built on the DeepSense architecture, the model integrates convolutional feature extraction with bi-GRUs for temporal modeling. The system is evaluated using 5-fold cross-validation, subject-aware holdout, and LOSEO strategies on the Opportunity dataset. Results demonstrate consistent accuracy across folds and strong generalization to …

Effects Of Data Augmentation On Sponge Identification Using Computer Vision Models, George Ku

Master's Projects

Coral reefs can be primarily found in tropical and sub-tropical regions of our oceans, providing a thriving habitat for millions of species. Marine sponges, which can be frequently found in coral reefs, play a critical role that contributes to the maintenance of these ecosystems, including the recycling of nutrients through water filtration. However, rising ocean temperatures and acidification due to climate change have resulted in the bleaching and death of coral reefs worldwide. In order to preserve these reefs and the sponges that depend on them, scientists have been performing studies on their biodiversity. This includes collecting numerous images of …

Ribomoe: An Application Of Mixture Of Experts On Artificial Riboswitch Classification, Hainian Audrey Long

Master's Projects

Urban water sewage is a potential health concern due to its possibility to spread contagious RNA viruses such as Coxsackievirus B3. However, detection of viral particles remains challenging because of low viral concentrations in wastewater and high mutation rates of the RNA virus. To address this, this study proposes a novel viral detection method using synthetic riboswitches that bind to the target virus and trigger a reporter gene, amplifying the detection signals. To support the design of effective riboswitches, we present a machine learning model for classifying riboswitch performance, integrating RNA sequence data with secondary structural features. This model used …

Disease Diagnosis Using Rag Llm With Smart Prompt Engineering, Qadeerullah Syed

Master's Projects

Although recent trends indicate that LLMs outperform traditional methods in solving complex problems with enhanced reasoning, there has been barely any progress in replicating the quality of diagnoses like those of actual human doctors. The identification of an accurate diagnosis with thorough reasoning is still a significant challenge, even with advanced AI models. The process of performing accurate diagnosis remains challenging due to a lack of transparency in state-of-the-art models existing today, a lack of explanation in the diagnosis process, an emphasis on results rather than reasoning, and a lack of foundational knowledge in models, along with limited exploration of …