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Assessing Total Mortality Following Seabird Wrecks Given Variable Data Quantity And Quality: The Cassin’S Auklet Die-Off, Timothy Jones, Julia K. Parrish, Parker Maccready, Lisa T. Ballance, David W. Bradley, Hillary K. Burgess, Jane E. Dolliver, James T. Harvey, Trevor Joyce, Kirsten Lindquist, Jacqueline Lindsey, Hannahrose M. Nevins, Jan Roletto, Laurie Wilson, Charlie Wright Jan 2025

Assessing Total Mortality Following Seabird Wrecks Given Variable Data Quantity And Quality: The Cassin’S Auklet Die-Off, Timothy Jones, Julia K. Parrish, Parker Maccready, Lisa T. Ballance, David W. Bradley, Hillary K. Burgess, Jane E. Dolliver, James T. Harvey, Trevor Joyce, Kirsten Lindquist, Jacqueline Lindsey, Hannahrose M. Nevins, Jan Roletto, Laurie Wilson, Charlie Wright

Faculty Research, Scholarly, and Creative Activity

Mass mortality events (MMEs) of seabirds are becoming more frequent as the global climate warms. Often documented via beached bird surveys, methods for estimating event-wide mortality are needed that can accommodate regional differences in carcass deposition and data quality/quantity. We develop a framework for estimating mortality from beached bird counts, extending existing approaches through the novel application of ocean circulation modeling to assess beaching likelihood. We applied our framework to the 2014/15 Cassin’s auklet (Ptychoramphus aleuticus) MME, which spread across three regions (central California, northern California-through-Washington, British Columbia) with varying data quality/quantity. Our best mortality estimate of ∼400 000 (estimates …

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Cross-Species Real-Time Detection Of Trends In Pupil Size Fluctuation, Sharif I. Kronemer, Victoria E. Gobo, Catherine R. Walsh, Joshua B. Teves, Diana C. Burk, Somayeh Shahsavarani, Javier Gonzalez-Castillo, Peter A. Bandettini Jan 2025

Cross-Species Real-Time Detection Of Trends In Pupil Size Fluctuation, Sharif I. Kronemer, Victoria E. Gobo, Catherine R. Walsh, Joshua B. Teves, Diana C. Burk, Somayeh Shahsavarani, Javier Gonzalez-Castillo, Peter A. Bandettini

Faculty Research, Scholarly, and Creative Activity

Pupillometry is a popular method because pupil size is easily measured and sensitive to central neural activity linked to behavior, cognition, emotion, and perception. Currently, there is no method for online monitoring phases of pupil size fluctuation. We introduce rtPupilPhase—an open-source software that automatically detects trends in pupil size in real time. This tool enables novel applications of real-time pupillometry for achieving numerous research and translational goals. We validated the performance of rtPupilPhase on human, rodent, and monkey pupil data, and we propose future implementations of real-time pupillometry.

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A Unifying Double-Reference Approach To Semantic Paradoxes: From The White-Horse-Not-Horse Paradox And The Ultimate-Unspeakable Paradox To The Liar Paradox In View Of The Principle Of Noncontradiction, Bo Mou Jan 2025

A Unifying Double-Reference Approach To Semantic Paradoxes: From The White-Horse-Not-Horse Paradox And The Ultimate-Unspeakable Paradox To The Liar Paradox In View Of The Principle Of Noncontradiction, Bo Mou

Faculty Research, Scholarly, and Creative Activity

The purpose of this study is to suggest and explain an engaging approach to three distinct types of (alleged or genuine) semantic paradoxes, the White-Horse-Not-Horse Paradox, the Ultimate-Unspeakable Paradox, and the Liar Paradox, in a unifying way that is sensitive to distinct features of them. Although the three types of semantic paradoxes address distinct types of objects, and although their seemingly paradoxical features are different (alleged or genuine), their distinct structures and contents can be understood and treated on the same common ground, which is jointly conceived in people's pretheoretic understandings of truth and of the double-reference feature of people's …

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Collective Liberation Through Critical Pedagogy, Robert A. Marx, Anne E. Dufault, Miriam R. Arbeit Jan 2025

Collective Liberation Through Critical Pedagogy, Robert A. Marx, Anne E. Dufault, Miriam R. Arbeit

Faculty Research, Scholarly, and Creative Activity

The collective liberation of queer and trans people—which is inherently tied to the liberation of those oppressed by white supremacy and racism, ableism, classism, ageism, and other asymmetrical power distributions—is possible when we develop critical consciousness through critical pedagogy. As young people develop an awareness of the contradictions and falsehoods they are taught (e.g., the myth of meritocracy), they begin to work to change their environments and offer resistance to the structures that inequitably shape their world. The vast majority of research on queer and trans adolescents, though, has been shaped by dominant, deficit-based views of queerness that presuppose that …

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Young Audience And Vod Platforms Of Linear Television. Perceptions About Playz, Mtmad And Flooxer, Belén Moreno Albarracín, Tania Blanco Sánchez Jan 2025

Young Audience And Vod Platforms Of Linear Television. Perceptions About Playz, Mtmad And Flooxer, Belén Moreno Albarracín, Tania Blanco Sánchez

Faculty Research, Scholarly, and Creative Activity

Introduction: The new audiovisual paradigm, marked by flexible consumption, a wide catalog and a participatory audience, increases the interest of linear television in connecting with young people. To that end, the channels manage specialized content platforms. This research aims to analyze Mtmad, Playz and Flooxer, and the perceptions about them. The specific objectives are to examine the catalogs; evaluate identification with management chains; analyze youth-content identification and study their consumption habits. Methodology: A content analysis based on web structures and catalogs is proposed; and a survey of 160 young people about their knowledge, identification and consumption patterns. Results: Mtmad leads …

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Temporal Patterns Of The Introduced Sponge Hymeniacidon Perlevis (Montagu, 1814) In The Elkhorn Slough, California, Usa, Jackson T. Hoeke, Kerstin Wasson, Amanda S. Kahn Jan 2025

Temporal Patterns Of The Introduced Sponge Hymeniacidon Perlevis (Montagu, 1814) In The Elkhorn Slough, California, Usa, Jackson T. Hoeke, Kerstin Wasson, Amanda S. Kahn

Faculty Research, Scholarly, and Creative Activity

Hymeniacidon perlevis is a cosmopolitan sponge with a seasonal life cycle. We investigated seasonal and interannual dynamics of H. perlevis in Elkhorn Slough estuary, where it is an introduced species, and explored correlations between sponge cover and environmental conditions. We used sponge cover to estimate the potential effects of H. perlevis on its environment, and how those could vary across its seasonal life cycle. We found that recruitment is currently restricted to the upper estuary and while it varies annually, the frequency and density of sponge recruits have generally increased from 2007 to 2023. A seasonal life cycle was confirmed …

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Learning About The Transit Passenger Experience From Microblogging Posts, Egbe Etu Etu, Asha Weinstein Agrawal, Jordan Larot, Chaitanya Tatipigari, Imokhai Theophilus Tenebe Jan 2025

Learning About The Transit Passenger Experience From Microblogging Posts, Egbe Etu Etu, Asha Weinstein Agrawal, Jordan Larot, Chaitanya Tatipigari, Imokhai Theophilus Tenebe

Faculty Research, Scholarly, and Creative Activity

Transit agencies often track delays and malfunctions but may overlook riders’ real-time social experiences. To fill this gap, we analyzed 559 tweets from 2020 to 2023 that captured personal accounts of public transport use. Using thematic analysis, we found that 74% of posts criticized other passengers’ behavior, far outweighing comments on transit ride quality, such as complaints about delays (25%). Notably, 86% of tweets expressed negative sentiment, though some highlighted exceptional service. These findings demonstrate that interpersonal dynamics are a key contributor to riders’ experiences and illustrate the nature of the interactions that riders like and dislike.

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Evaluating Seasonal Vs. Spatial Extrapolation For Cetacean Distribution Models In The California Current, Elizabeth A. Becker, Karin A. Forney, Bruce J. Thayre, Katherine Whitaker, Ryan Hoopes, Joshua M. Jones, John A. Hildebrand, Jeff Moore Jan 2025

Evaluating Seasonal Vs. Spatial Extrapolation For Cetacean Distribution Models In The California Current, Elizabeth A. Becker, Karin A. Forney, Bruce J. Thayre, Katherine Whitaker, Ryan Hoopes, Joshua M. Jones, John A. Hildebrand, Jeff Moore

Faculty Research, Scholarly, and Creative Activity

Species distribution models (SDMs) have been developed for multiple cetacean species within the California Current Ecosystem (CCE) from shipboard survey data collected by the Southwest Fisheries Science Center (SWFSC) in summer and fall, thus limiting the ability to inform management decisions in cool seasons when abundance and distribution patterns are substantially different. Winter and spring SDMs have been developed for a few species using California Cooperative Oceanic Fisheries Investigations (CalCOFI) shipboard survey data, but model predictions are limited to the waters off southern and central California. In this study, winter and spring density estimates for the entire CCE study area …

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From Shocks To Solidarity And Superstition: Exploring The Foundations Of Faith, Aidin Hajikhameneh, Laurence R. Iannaccone Jan 2025

From Shocks To Solidarity And Superstition: Exploring The Foundations Of Faith, Aidin Hajikhameneh, Laurence R. Iannaccone

Faculty Research, Scholarly, and Creative Activity

Additive shocks can substantially increase cooperation in otherwise standard public goods game experiments. We study shocks that randomly adjust players’ earnings by a fixed positive or negative amount reported at the end of each round. These adjustments change neither the return to players’ contributions nor the information about other group members. We compare results across four treatments that employ the same group-level adjustment algorithm but frame it differently, with pre-play descriptions that range from omitting all useful information to accurately revealing its 50/50 random nature. In each treatment, overall contributions run about 50% higher than those obtained in the standard …

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How We Could Have Libertarian Free Will Even If God Were A Total Know-It-All About The Future, Mark Balaguer, Rebecca Chan Jan 2025

How We Could Have Libertarian Free Will Even If God Were A Total Know-It-All About The Future, Mark Balaguer, Rebecca Chan

Faculty Research, Scholarly, and Creative Activity

We argue that libertarianism (roughly, the thesis that we have indeterministic, libertarian free will) is compatible with God's infallible foreknowledge. We use eternalism (roughly, the thesis that reality is a 4-dimensional block and that past, present, and future objects exist) as an explanatory stepping stone between libertarianism and God's foreknowledge: eternalism entails that (and comes close to explaining how) an omniscient God would know what we decide in the future even if we have libertarian free will. This account also explains what is wrong with standard fatalist arguments for the incompatibility of free will and God's foreknowledge.

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On Modeling Agent Behavior Change Through Multi-Typed Information Diffusion In Online Social Networks, Masaaki Miyashita, Norihiko Shinomiya, Daisuke Kasamatsu, Genya Ishigaki Jan 2025

On Modeling Agent Behavior Change Through Multi-Typed Information Diffusion In Online Social Networks, Masaaki Miyashita, Norihiko Shinomiya, Daisuke Kasamatsu, Genya Ishigaki

Faculty Research, Scholarly, and Creative Activity

The rapid spread of information on online social networks (OSNs) has had both beneficial and detrimental societal impacts. Notably, the propagation of misinformation during events such as the COVID-19 pandemic has driven collective behavioral responses, sometimes exacerbating crises such as panic buying and bank runs. The toilet paper shortage in Japan in 2020 caused by people's selfish behavior owing to the diffusion of information to correct misinformation, which is considered a general phenomenon based on three sociological characteristics: a collective action problem, a self-fulfilling prophecy, and pluralistic ignorance. Understanding what kind and how information can inhibit selfish behavior to mitigate …

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Physiological Effects Of Research Handling On The Northern Elephant Seal (Mirounga Angustirostris), Lauren A. Cooley, Allyson G. Hindle, Cassondra L. Williams, Paul J. Ponganis, Shawn M. Hannah, Holger Klinck, Markus Horning, Daniel P. Costa, Rachel R. Holser, Daniel E. Crocker, Birgitte I. Mcdonald Jan 2025

Physiological Effects Of Research Handling On The Northern Elephant Seal (Mirounga Angustirostris), Lauren A. Cooley, Allyson G. Hindle, Cassondra L. Williams, Paul J. Ponganis, Shawn M. Hannah, Holger Klinck, Markus Horning, Daniel P. Costa, Rachel R. Holser, Daniel E. Crocker, Birgitte I. Mcdonald

Faculty Research, Scholarly, and Creative Activity

Wildlife researchers must balance the need to safely capture and handle their study animals to sample tissues, collect morphological measurements, and attach dataloggers while ensuring their results are not confounded by stress artifacts caused by handling. To determine the physiological effects of research activities including chemical immobilization, transport, instrumentation with biologgers, and overnight holding on a model marine mammal species, we collected hormone, blood chemistry, hematology, and heart rate data from 19 juvenile northern elephant seals (Mirounga angustirostris) throughout a translocation experiment. Across our six sampling timepoints, cortisol and aldosterone data revealed a moderate hormonal stress response to handling accompanied …

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The Multiple Classes Of Ultra-Diffuse Galaxies: Can We Tell Them Apart?, Maria Luisa Buzzo, Duncan A. Forbes, Thomas H. Jarrett, Francine R. Marleau, Pierre Alain Duc, Jean P. Brodie, Aaron J. Romanowsky, Anna Ferré-Mateu, Michael Hilker, Jonah S. Gannon, Joel Pfeffer, Lydia Haacke Jan 2025

The Multiple Classes Of Ultra-Diffuse Galaxies: Can We Tell Them Apart?, Maria Luisa Buzzo, Duncan A. Forbes, Thomas H. Jarrett, Francine R. Marleau, Pierre Alain Duc, Jean P. Brodie, Aaron J. Romanowsky, Anna Ferré-Mateu, Michael Hilker, Jonah S. Gannon, Joel Pfeffer, Lydia Haacke

Faculty Research, Scholarly, and Creative Activity

This study compiles stellar populations and internal properties of ultra-diffuse galaxies (UDGs) to highlight correlations with their local environment, globular cluster (GC) richness, and star formation histories. Complementing our sample of 88 UDGs, we include 36 low surface brightness dwarf galaxies with UDG-like properties, referred to as NUDGes (nearly UDGs). All galaxies were studied using the same spectral energy distribution fitting methodology to explore what sets UDGs apart from other galaxies. We show that NUDGes are similar to UDGs in all properties except for being, by definition, smaller and having higher surface brightness. We find that UDGs and NUDGes show …

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The Chatgpt Fact-Check: Exploiting The Limitations Of Generative Ai To Develop Evidence-Based Reasoning Skills In College Science Courses, Ursula Holzmann, Sulekha Anand, Alexander Y. Payumo Jan 2025

The Chatgpt Fact-Check: Exploiting The Limitations Of Generative Ai To Develop Evidence-Based Reasoning Skills In College Science Courses, Ursula Holzmann, Sulekha Anand, Alexander Y. Payumo

Faculty Research, Scholarly, and Creative Activity

Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenges for using such tools in college classrooms. To address this, an adaptable assignment called the ChatGPT Fact-Check was developed to teach students in college science courses the benefits of using LLMs for topic exploration while emphasizing the importance of validating their claims based on evidence. The assignment requires students to use ChatGPT to generate essays, evaluate AI-generated sources, and assess the validity of AI-generated scientific claims …

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A Short Pragmatic Tool For Evaluating Community Engagement: Partnering For Health Improvement And Research Equity, John G. Oetzel, Blake Boursaw, Lenora Littledeer, Sarah Kastelic, Page Castro-Reyes, Juan M. Peña, Patricia Rodriguez Espinosa, Shannon Sanchez-Youngman, Lorenda Belone, Nina Wallerstein Jan 2025

A Short Pragmatic Tool For Evaluating Community Engagement: Partnering For Health Improvement And Research Equity, John G. Oetzel, Blake Boursaw, Lenora Littledeer, Sarah Kastelic, Page Castro-Reyes, Juan M. Peña, Patricia Rodriguez Espinosa, Shannon Sanchez-Youngman, Lorenda Belone, Nina Wallerstein

Faculty Research, Scholarly, and Creative Activity

Background: As community-engaged research (CEnR), community-based participatory research (CBPR) and patient-engaged research (PEnR) have become increasingly recognized as valued research approaches in the last several decades, there is need for pragmatic and validated tools to assess effective partnering practices that contribute to health and health equity outcomes. This article reports on the co-creation of an actionable pragmatic survey, shortened from validated metrics of partnership practices and outcomes. Methods: We pursued a triple aim of preserving content validity, psychometric properties, and importance to stakeholders of items, scales, and constructs from a previously validated measure of CBRP/CEnR processes and outcomes. There were …

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Automated Research Review Support Using Machine Learning, Large Language Models, And Natural Language Processing, Vishnu S. Pendyala, Karnavee Kamdar, Kapil Mulchandani Jan 2025

Automated Research Review Support Using Machine Learning, Large Language Models, And Natural Language Processing, Vishnu S. Pendyala, Karnavee Kamdar, Kapil Mulchandani

Faculty Research, Scholarly, and Creative Activity

Research expands the boundaries of a subject, economy, and civilization. Peerreview is at the heart of research and is understandably an expensive process. This work,with human-in-the-loop, aims to support the research community in multiple ways. Itpredicts quality, and acceptance, and recommends reviewers. It helps the authors andeditors to evaluate research work using machine learning models developed based on adataset comprising 18,000+ research papers, some of which are from highly acclaimed,top conferences in Artificial Intelligence such as NeurIPS and ICLR, their reviews, aspectscores, and accept/reject decisions. Using machine learning algorithms such as SupportVector Machines, Deep Learning Recurrent Neural Network architectures such …

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Understanding Mobility-Related Challenges For Aapi Older Adults: A Preliminary Study In Southern California, Yongping Zhang, Priscila Salgado Inzunza, Carol Kachadoorian, Wen Cheng, Calvin Wong Jan 2025

Understanding Mobility-Related Challenges For Aapi Older Adults: A Preliminary Study In Southern California, Yongping Zhang, Priscila Salgado Inzunza, Carol Kachadoorian, Wen Cheng, Calvin Wong

Mineta Transportation Institute

The Federal Highway Administration (FHWA) and state Departments of Transportation (DOTs) Nationwide, the Asian American Pacific Islander (AAPI) community is projected to constitute 11 percent of people 65 years and older in the United States by 2050 (He et al., 2005). The challenges limiting the transportation and mobility of AAPI older adults include, but are not limited to, language barriers, cultural barriers, anti-Asian hate, accessibility to public transit, traffic safety and public security concerns, and changes to mobility due to the COVID-19 pandemic. This project conducted an extensive literature review and a preliminary multi-language survey in Southern California to better …

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Toward Strategy Identification And Subtask Decomposition In Task Exploration, Tom Odem Jan 2025

Toward Strategy Identification And Subtask Decomposition In Task Exploration, Tom Odem

Master's Projects

This research builds on work in anticipatory human-machine interaction, a subfield of human-machine interaction where machines can facilitate advantageous interactions by anticipating a user’s future state. The aim of this research is to further a machine’s understanding of user knowledge, skill, and behavior in pursuit of implicit coordination. A task explorer pipeline was developed that uses clustering techniques, paired with factor analysis and string edit distance, to automatically identify key global and local strategies that are used to complete tasks. Global strategies identify generalized sets of actions used to complete tasks, while local strategies identify sequences that used those sets …

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Automated Sponge Segmentation With Mask R-Cnn On Arms Plate Images For Reef Monitoring, Mrunali Abhijit Thokadiwala Jan 2025

Automated Sponge Segmentation With Mask R-Cnn On Arms Plate Images For Reef Monitoring, Mrunali Abhijit Thokadiwala

Master's Projects

Climate change-driven ocean warming and acidification are disrupting the ecological balance of coral reefs. Notably, these oceanic conditions are undermining coral health and accelerating their decline which is favoring some sponge species in outcompeting them for dominance. Although functional, these altered reefs destabilize the reef architecture, hinder nutrient cycling, and support fewer marine species. Thus, monitoring the growth and abundance of various sponges and understanding their roles at different stages of ecological succession in coral reefs is vital. Autonomous reef monitoring structures (ARMS) are often used for this purpose, but manual taxonomic analysis using their images is time-consuming, inconsistent and …

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Ai-Based Dynamic Spectrum Allocation Model For Wireless Network Management, Sai Sashank Peddibhotla Jan 2025

Ai-Based Dynamic Spectrum Allocation Model For Wireless Network Management, Sai Sashank Peddibhotla

Master's Projects

The growth of wireless communication has introduced challenges in the dynamic and resource contrived space which is the efficient utilization of bandwidth and spectrum. This research presents a model for dynamic spectrum allocation with the help of Convolutional Neural Network (CNN) for feature extraction and the Deep Q-Network (DQN) model’s reinforcement learning architecture. The CNN captures both spatial and temporal features of the network states and gives them to the DQN for optimal allocation decision making. This CNN-DQN architecture effectively implements spectrum resource allocation in wireless networks and adapts to resource allocation changes within performance bounds. The system’s performance is …

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Improving Contextual Retrieval For Long Documents In Q & A Systems, Sakshi Garg Jan 2025

Improving Contextual Retrieval For Long Documents In Q & A Systems, Sakshi Garg

Master's Projects

With the vast amount of information available on the internet distributed across several lengthy documents, finding relevant information has become more important and challenging. The goal of this project is to develop advanced techniques to retrieve information from long texts in order to deliver accurate and relevant results while ensuring speed and efficiency. As part of this work, we employ techniques to address unique difficulties posed by large and complex documents. This paper presents a custom Retrieval-Augmented Generation (RAG) framework designed to improve contextual retrieval in long and multi-document settings. In this paper, we employ several techniques like summarization, semantic …

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Evorgcn: Harnessing Esm-2 Evolutionary Embeddings With Relational Gcns For High-Fidelity Protein-Protein Interaction Prediction, Mohit Kunder Jan 2025

Evorgcn: Harnessing Esm-2 Evolutionary Embeddings With Relational Gcns For High-Fidelity Protein-Protein Interaction Prediction, Mohit Kunder

Master's Projects

Accurately predicting protein-protein interactions (PPIs) is essential for understanding cellular function and advancing biomedical discovery. We model PPIs as graphs, where nodes represent proteins and edges denote interactions. Using interaction data from the STRING database, we use two samples of it, namely the benchmark datasets—SH27K and SH148K—filtered by confidence score and annotated by interaction mode (multiple relations). In this project, we present EvoRGCN, a graph-based machine learning framework for PPI prediction that integrates both sequence-level (ESM-2 embeddings) and network-level information. We incorporate various Graph Neural Network architectures, including Graph Convolutional Networks, Graph Attention Networks, and Relational Graph Convolutional Networks. Our …

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Synthetic Malware Generation Using Generative Ai, Phanidhar Sai Sravan Chandana Jan 2025

Synthetic Malware Generation Using Generative Ai, Phanidhar Sai Sravan Chandana

Master's Projects

Malware grows in numbers and complexity, evading conventional signature-and anomaly-based defenses and worsening extreme data sparsity and class imbalance problems for machine learning based detection. Generative models, specifically GANs conditioned on contextual embeddings like BERT have proved effective augmenting training corpora to improve classifier accuracy, but these approaches have largely produced family-specific samples In this paper, we propose a generalized augmentation scheme for generating robust malware embeddings for various families. We begin by extracting opcode sequences from 13 malware families and encoding them into three embedding methods: CountVectorizer, TF-IDF, and BERT’s ‘[CLS]‘ vectors. We therefore train standard GANs and Wasserstein …

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Comparative Analysis Of Embedding Techniques With Clustering Algorithms For Malware Opcodes, Ayush Koul Jan 2025

Comparative Analysis Of Embedding Techniques With Clustering Algorithms For Malware Opcodes, Ayush Koul

Master's Projects

Malware detection and classification remain critical challenges in cybersecurity, especially as malicious software becomes increasingly sophisticated and prevalent. While much of the work involving embeddings has traditionally relied on supervised learning approaches, there is significant potential in leveraging unsupervised learning techniques to discern hidden structures in malware data. By employing embedding techniques to convert malware samples into high-dimensional vector representations, we can capture the subtle and complex patterns inherent in malicious code without relying on pre-labeled data. This unsupervised approach helps categorize malware into predefined malware families, greatly aiding in developing cybersecurity solutions. In contrast to traditional supervised models that …

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Gen Ai For Malicious Network Data, Aneesh Maturu Jan 2025

Gen Ai For Malicious Network Data, Aneesh Maturu

Master's Projects

Though botnet attacks are on the rise, they also have become sophisticated and difficult to detect. Such a rising threat demands more and more sophisticated cybersecurity that leverages machine learning technology. Nevertheless, one of the biggest bottlenecks remains the unavailability of large and well-balanced datasets, particularly for malicious traffic, which hampers the efficacy of detection models. In an attempt to address this issue, our research utilizes Generative Adversarial Networks (GANs) to produce synthetic samples of botnet traffic from the CTU-13 dataset. While the majority of generative models have been targeting image data, we use GANs for a new application: generating …

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Collaborative Governance In Practice: Evaluating Intergovernmental Relations Through The Santa Clara County Healthy Cities Initiative, Astrid J. Robles Jan 2025

Collaborative Governance In Practice: Evaluating Intergovernmental Relations Through The Santa Clara County Healthy Cities Initiative, Astrid J. Robles

Master's Projects

In the United States, intergovernmental relations (IGR) is rooted in the principles of American federalism, which focuses on the constitutional power dynamics between national, state, and local governments. While federalism outlines the structural framework, IGR specifically focuses on how federal, state, and local governments interact administratively, financially, and politically within the federal system. Beginning in the 1960’s, governments across the U.S. began to rely on non-governmental and private sector organizations for program implementation (Boyd & Fauntroy, 2000). This shift gave rise to the concept of collaborative governance, which expanded the scope of IGR by incorporating traditionally excluded groups from the …

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Application Of Root Cause Analysis For Fall Prevention: A Quality Improvement Initiative For Older Adults In A Skilled Nursing And Long-Term Care Facility, Terrence Ranjo Jan 2025

Application Of Root Cause Analysis For Fall Prevention: A Quality Improvement Initiative For Older Adults In A Skilled Nursing And Long-Term Care Facility, Terrence Ranjo

Doctoral Projects

Falls in older adults are common and often have severe outcomes. They are the leading cause of fatal and non-fatal injuries among people aged 65 and older and continue to increase. Half of residents in nursing facilities fall annually, and one in every ten falls will lead to a severe injury. Federal regulations like the Centers for Medicare and Medicaid Services require long-term care (LTC) facilities to incorporate quality assurance performance improvement initiatives to address identified quality concerns in LTC facilities. Root cause analysis (RCA) can help clinicians identify several root causes of falls and guide clinicians in developing personalized …

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Advocating For The Field Of Occupational Therapy Among High School Students, Linda Crabtree Jan 2025

Advocating For The Field Of Occupational Therapy Among High School Students, Linda Crabtree

Doctoral Projects

The field of occupational therapy (OT) is a healthcare field that is impactful on the lives of many individuals however there is currently a lack of awareness of the field of OT due to a lack of knowledge of and interest in OT among healthcare providers and the public (Richards and Valleé, 2020). The Aim of Research. The purpose of this project is to advocate for the field of OT and assess if an introductory presentation and hands-on lab about OT’s scope can improve the interest in OT among high school students in both rural and urban environments. Methods. The …

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Scans, Carlos D. Leon Jan 2025

Scans, Carlos D. Leon

Master's Theses

scans is a collection of poems that explore my memories within the small farm town of Soledad, California. This collection examines the intersections of religious experiences, relationships, and core regional identifiers. I believe literature transcends time and works as a capsule for our experiences. This collection looks to examine and elevate the qualities of these experiences, inviting the reader to rediscover their own memories and the minor details lost within them. Separated into four sections, each poem works as a fragmented memory, with the intent of creating a near, complete image of their designated section. I seek to provide an …

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Stream Response To A Dam Removal: Mill Creek, Davenport, Ca, Jessica J. Williamson Jan 2025

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 …

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