Digital Commons Network^™

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 …

Generating Synthetic Malware Samples Using Generative Ai, Tiffany Bao, Kylie Trousil, Quang Duy Tran, Fabio Di Troia, Younghee Park

Faculty Research, Scholarly, and Creative Activity

Malware attacks have a significant negative impact on organizations of varied scales in the field of cybersecurity. Recently, malware researchers have increasingly turned to machine learning techniques to combat sophisticated obfuscation methods used in malware. However, collecting a diverse set of malware samples with various obfuscation techniques is challenging and often takes years, especially for newly developed malware. This issue is further compounded by a well-known limitation of machine learning models: their poor performance when training data is scarce. In this paper, we propose a new system for generating synthetic malware samples to augment imbalanced malware dataset. Our approach decomposes …

Finding Floral And Faunal Species Richness Optima Among Active Fire Regimes, Zachary L. Steel, Alissa M. Fogg, Raphaela Floreani Buzbee, Kate Wilkin, Brandon M. Collins, Ryan Burnett, Marc D. Meyer, Amarina Wuenschel, Scott L. Stephens

Faculty Research, Scholarly, and Creative Activity

Changing fire regimes have important implications for biodiversity and challenge traditional conservation approaches that rely on historical conditions as proxies for ecological integrity. This historical-centric approach becomes increasingly tenuous under climate change, necessitating direct tests of environmental impacts on biodiversity. At the same time, widespread departures from historical fire regimes have limited the ability to sample diverse fire histories. We examined 2 areas in California's Sierra Nevada (USA) with active fire regimes to study the responses of bird, plant, and bat communities to a broad spectrum of temporal, spatial, and severity patterns of fire. Bird and plant species richness peaked …

Reinforcement Learning Methods For Assistive And Rehabilitation Robotic Systems: A Survey, Mojtaba Sharifi, Shreesh Tripathi, Yun Chen, Qiang Zhang, Mahdi Tavakoli

Faculty Research, Scholarly, and Creative Activity

Advancements in robotic systems aimed at improving mobility for individuals with disabilities have required more sophisticated control and navigation methods. Traditional control approaches often lack the complexity and adaptability needed for the high-dimensional nature of human activities. Consequently, reinforcement learning (RL) has emerged as a dynamic and effective framework for managing robotic actions in complex and unpredictable human environments. This article reviews the integration of RL in robotic systems for enhancing the mobility of individuals with disabilities, addressing the limitations of traditional control methods in complex and unpredictable environments. We critically analyze various RL algorithms, discussing their advantages and challenges …

From Disciplinary Enthusiasm To Soulless Tasks: Norms Behind Computing Educators' Emotion Display, Virginia Grande, Päivi Kinnunen, Matthew Barr, Anne Kathrin Peters, Mihaela Sabin, Matilde Sánchez-Peña, Ethel Tshukudu

Faculty Research, Scholarly, and Creative Activity

Computing educators' emotion display is regulated by various norms and conventions. These (unwritten) rules affect which emotions educators feel comfortable expressing to different extents when students can perceive such displays. We draw on emotions and norms literature to investigate higher education computing educators' perceptions of what kinds of norms they have as criteria when considering which emotions they are (not) comfortable showing when teaching. Based on the qualitative content analysis of 22 interviews with computing educators from seven countries, we present various–sometimes connected or conflicting–norms that influence emotion display. These norms comprise moral, national, societal, professional, and affiliation norms that …

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 …

Poster: Synthetic Malware Generation Using Generative Models, Tiffany Bao, Kylie Trousil, Quang Duy Tran, Fabio Di Troia, Younghee Park

Faculty Research, Scholarly, and Creative Activity

Malware poses significant challenges to cybersecurity, exacerbated by the scarcity of high-quality datasets. This paper explores the use of Diffusion and Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) to generate synthetic malware samples as opcode sequences. The synthetic data, validated through classification metrics, demonstrates improved malware detection accuracy across families, particularly in addressing zero-day attacks. Results show that Diffusion achieves up to 99.6% accuracy in multi-class classification, outperforming WGAN-GP, which reaches up to 96.1%. Incorporating synthetic samples improves detection accuracy for rare malware families by up to 100%, underscoring the potential of generative models in enhancing malware detection.

Comparing E-Mosaics Predictions Of High-Redshift Proto-Globular Clusters With Jwst Observations In Lensed Galaxies, Joel Pfeffer, Duncan A. Forbes, Aaron J. Romanowsky, Nate Bastian, Robert A. Crain, J. M.Diederik Kruijssen, Kenji Bekki, Jean P. Brodie, Mélanie Chevance, Warrick J. Couch, Jonah S. Gannon

Faculty Research, Scholarly, and Creative Activity

High-resolution imaging and strong gravitational lensing of high-redshift galaxies have enabled the detection of compact sources with properties similar to nearby massive star clusters. Often found to be very young, these sources may be globular clusters detected in their earliest stages. In this work, we compare predictions of high-redshift (-10) star cluster properties from the E-MOSAICS simulation of galaxy and star cluster formation with those of the star cluster candidates in strongly lensed galaxies from JWST and Hubble Space Telescope (HST) imaging. We select galaxies in the simulation that match the luminosities of the majority of lensed galaxies with star …

A Close Look At Dissolved Silica Dynamics In Disko Bay, West Greenland, Mark J. Hopwood, Dustin Carroll, Yuanyuan Gu, Xin Huang, Jana Krause, Stefano Cozzi, Carolina Cantoni, María Fernanda Gastelu Barcena, Shandy Carroll, Arne Körtzinger

Faculty Research, Scholarly, and Creative Activity

Discharge of calved ice, runoff and mixing driven by subglacial discharge plumes likely have consequences for marine biogeochemistry in Disko Bay, which hosts the largest glacier in the northern hemisphere, Sermeq Kujalleq. Glacier retreat and increasing runoff may impact the marine silica cycle because glaciers deliver elevated concentrations of dissolved silica (dSi) compared to other macronutrients. However, the annual flux of dSi delivered to the ocean from the Greenland Ice Sheet is poorly constrained because of difficulties distinguishing the overlapping influence of different dSi sources. Here we constrain silica dynamics around Disko Bay, including the Ilulissat Icefjord and four other …

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 …

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 …

Bridging Sql Mastery And Career Confidence For Undergraduate Students Through Simulated Job Interviews, Dailin Zheng, Yu Chen, Leslie J. Albert

Faculty Research, Scholarly, and Creative Activity

Employers increasingly prioritize candidates who can solve real-world Structured Query Language (SQL) problems, particularly during technical interviews. However, many undergraduate students feel underprepared for these interviews because they have not engaged in the deep learning needed to apply SQL concepts confidently. Additionally, students often fail to recognize the career relevance of SQL skills. This Teaching Tip introduces an immersive SQL lesson designed to bridge the gap between conceptual learning and practical application. The lesson includes a mock SQL technical interview, where students apply their knowledge to solve real-world business problems, class discussions on SQL-related careers, and a post-interview debrief to …

Rondo: A Minimal Single Page Application For Digital Exhibits, Nick Szydlowski

Faculty Research, Scholarly, and Creative Activity

Minimal computing is a promising conceptual framework for digital humanities infrastructure, but the static site architecture most commonly associated with minimal computing can present a steep learning curve, particularly in a workshop or classroom context. This article introduces Rondo, a new minimal framework for digital exhibits which requires no software installation or command line interaction. Rondo differentiates itself from static site tools by adopting a single page application architecture with data stored in a Google Sheet, but it includes tools to disconnect from Google Sheets and create a static site with no external dependencies. Rondo’s reliance on Google Sheets reflects …

Rift - Reddit Information Falsity Tagger, Parth Joshi

Master's Projects

Social media platforms such as Reddit are widely used for sharing and consuming information. User-generated content poses a great risk for misinformation creation and dissemination on these platforms. “Fake news”, as it is commonly referred to, has far-reaching social implications, swaying public perception, making political viewpoints more radical, and adversely impacting health decisions. The covariable features that come with fake news make it even harder to detect because it is presented in the form of text, images, videos, and even social interactions. This paper describes a novel method for detecting fake news on Reddit: RIFT, short for Reddit Information Falsity …

Transformer Integration, Fine-Tuning And Zero-Shot Learning For State Of Health Estimation In Li-Ion Batteries Using Large Language Models, Chinmay Nilesh Mahagaonkar

Master's Projects

In this thesis, we present a comparative analysis of the use of transformerbased and Large Language Model (LLM) models for State of Health (SoH) and Remaining Useful Life (RUL) prediction of lithium-ion batteries. With electric cars and renewable energy systems based on batteries at the forefront, the need to predict degradation accurately in order to enhance the performance and reduce maintenance costs has become imperative. Most traditional prediction methods lag the complex and non-linear characteristics of degradation in batteries, and hence the usage of sophisticated methods becomes a necessity. The research employs the CALCE dataset, which includes long-horizon cycling data …

Image-To-Text Transcription: Analyzing And Describing Visual Content, Zixiao Fan

Master's Projects

Image captioning, which provides a textual understanding of visual content, is the fundamental support for the advancement of Human-A.I. Interaction technology. In the hope of exploring the application of such technology, this project focuses on two specific goals. One is to directly explore the application of the image informationretrieving abilities, and the other is to dive into the specifics of the pipeline and components of image captioning models. As a result, this project presents a working app that exploits the text retrieval functionalities to enable image storage with functions like tagging and transcription. It also supports search functionality with a …

Extraction Of A Knowledge Graph Of Biomedical Relationships, Brian Tran

Master's Projects

Rapid release in biomedical literature poses a challenge in linking information. This thesis aims to extract data from expanding datasets to identify and form meaningful relationships between biomedical entities. Large language models (LLMs) enable us to learn at a rapid pace. Creation of LLms from scratch are impractical. This thesis aims to collect a small dataset, containing biomedical papers, and use it to train large language models (LLMs) to extract entities from the text and learn the relationships between these entities. The experiment will be divided into two stages and utilize EU-ADR and ChemProt dataset. Starting with named entity recognition …

Advanced Knowledge Extraction With Biomedical Data Using Llms, Akshat Krishna

Master's Projects

The rapid growth of biomedical research has led to an overwhelming volume of unstructured textual data in the scientific literature. This has necessitated the development of an automated approach for knowledge extraction and integration. In

this project, we present a comprehensive pipeline for constructing a unified biomed- ical knowledge graph by combining two well-known datasets: CHEMPROT [1],

which captures chemical–protein interactions, and EU-ADR [2], which annotates drug–gene–disease relationships. In order to identify important biomedical entities and interactions from CHEMPROT dataset, we perform Named Entity Recognition (NER) and relation Extraction (RE) using state-of-the-art biomedical models like BioBERT [3], BioGPT [4] and …

Mitigating Cold Start Problem Through Metadata Integration And User Preference Analysis, Prabaljit Walia

Master's Projects

Recommendation systems power the most popular platforms in the world: from content catalogs on Netflix to custom feeds on TikTok – the importance of recommendation systems is significant. Collaborative filtering, the most popular recommendation technique, is essentially based on the idea of leveraging collective user intelligence i.e., creating recommendations by finding similar users. But this technique suffers when there is not enough data in the profiles of users, formally termed as the cold start problem. This research focuses on this problem by introducing an approach that integrates metadata-driven similarity measures with profile expansion techniques. Our approach combines traditional collaborative filtering …

Machine Learning Based Network Traffic Classification With Cosine-Similarity Based Out-Of-Distribution Detection, Prabhat Edupuganti

Master's Projects

The changes occurring in the amount of encrypted network traffic is growing at an alarming rate. This development has created intricate problems in traffic classification which is vital for effective cybersecurity. Moreover, most frameworks seem to ignore OOD detection, model calibration and novel pattern detection as cornerstone problem areas. The due analysis is presented as a machine learning approach aimed at resolving encrypted traffic classification issues and focuses on novel OOD detection and calibration issues. Primary contributions comprise detection of out-of-distribution states using softmax scaled cosine similarity, advanced variance-based feature elimination, and lowering ECE using stringent NNs. This work demonstrates …

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 …

The Inequitable Access: Black And Latinx Students In Ap Courses, Jean C. Woolcock

Dissertations

This study posits that in American high schools, the preparation of Black and Latinx students, starting from the freshman year, can be effective in helping to increase their participation in Advanced Placement (AP) courses. Structural inequities, in how schools are resourced, affect the ways in which Black and Latinx students are denied equal opportunities. On the contrary, members of their peers do obtain this kind of preparation. As a framework, Critical Race Theory (CRT) contends that race, the law, and power are deeply ingrained in maintaining established bastions of wealth and dominance. Gaps in opportunity and achievement spill over into …

Inspection Technologies For Construction And Maintenance Of Highway Infrastructure – Review And Analysis, Manideep Tummalapudi, Prem Raj Timilsena

Mineta Transportation Institute

The Federal Highway Administration (FHWA) and state Departments of Transportation (DOTs) seek to provide high quality infrastructure that meets or exceeds the desired quality standards crucial for ensuring safety and efficiency in our nation's transportation systems. Efficient inspection practices—which enable conformance with plans, specifications, and quality standards—are an essential part of this effort. In this digital age, state DOTs are relying on emerging technologies to improve inspection practices. However, there is limited knowledge available regarding various emerging technologies used for highway infrastructure construction and maintenance inspection. This study identifies various emerging technologies that are implemented at the state DOTs and …

Development Of Physics-Based Deterioration Models For Reinforced Soil Retaining Structures, Amr Morsy, Islam Ebo

Mineta Transportation Institute

Reinforced soil walls are key earth retention features in the transportation infrastructure. They are used to support and retain soil in a wide variety of crucial structures, such as highways, bridges, and railways, to ensure stability. They also provide solutions for constructing embankments and slopes in constrained spaces, allowing for efficient land use and improved infrastructure planning. This study used advanced numerical modeling to improve the understanding of the behavior and long-term performance of the aging reinforced soil walls from the 1970s for asset management purposes. An asset-scale model was created to simulate the effects of weather on these walls. …

Survey Of Building Information Modeling For Infrastructure (Bim4i), Maria Calahorra-Jimenez, Nigel Blampied, Elhami Nasr, Tariq Shehab

Mineta Transportation Institute

The rapid development of information technologies is transforming how data and information are produced, shared, exchanged, and managed. This transformation is accelerating in state departments of transportation (DOTs) across the country due to the pressing need for efficient means of delivering transportation projects and an enhanced need for internal and external collaboration. A key driver for this transformation is the implementation of Building Information Modeling for Infrastructures (BIM4I). The primary objective of this research was to develop actionable recommendations for DOTs to facilitate the effective adoption of BIM4I, based on national and international lessons learned and best practices. A four-step …

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 …

Conceptual Critical Success Factors Model On Infrastructure Sustainability Rating System For California Construction Projects, Joseph J. Kim, Jose A. Arroyo-Turcios

Mineta Transportation Institute

This report addresses the sensitivity and reliability of the sustainability rating systems by comparing each category’s verified scores with its respective submitted scores to evaluate how points are awarded for infrastructure projects, examine which categories present the most challenges for verification, and identify the best category for verification in the sustainability rating system. The authors conducted three analyses using credit score data obtained from fourteen actual civil infrastructure projects certified under Envision. First, the Natural World category had the highest average score from the submitted and verified data. Pairwise comparisons using t-tests indicate that the mean value of one category …

Evaluation Of A Community-Based Socialization Program For Independently Living Older Adults, Patricia A. Shane, Anne T. Ferguson, Erin L. Woodhead

Faculty Research, Scholarly, and Creative Activity

Social isolation among older adults is a major public health concern because of the adverse impact it has on health and well-being. Reducing social isolation can improve health and decrease the use of costly healthcare services. However, there is little consensus on the critical ingredients of programming to reduce social isolation. Bay Area Older Adults® (BAO) is a nonprofit organization whose community-based Healthy Living Program (HLP) focuses on building and nourishing older adults’ social networks through transitions such as retirement, divorce and loss of loved ones. The current study was a program evaluation of the HLP using a survey to …

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 …

Early Electronic Journals: A Preservation Survey, Nick Szydlowski, Rosa Salangsang, Daniella Kate Corpuz

Faculty Research, Scholarly, and Creative Activity

In 1994, the Association of Research Libraries (ARL) published a print directory containing information on every electronic journal that could be identified, anywhere in the world. Thirty years later, this study surveys the current availability and preservation status of those 443 journals. While a significant number of these journals are no longer available, the results indicate that independent preservation efforts by individuals and small groups were a major factor in preserving many of the remaining publications. This study uses the preservation survey method to assess the preservation environment for these journals, and also to build an online directory of the …