Digital Commons Network^™

Searching For Cause Of Unexplained Protein Interaction With Multiple Assembly Methods, Gavin Anderson

Master's Projects

Research into colistin adjuvants has identified interactions between a host of proteins and proteins found within certain strains of bacteria. BLAST, a widely adopted local sequence alignment tool, was used to create a database containing the genomes of relevant bacterial strains, which would then be used to query against the previously identified proteins. Many of these strains do not have publicly available assemblies, which makes database construction difficult. CATwalk, a new naïve fragment extender, is first described in this paper and used to extend fragments of interest. BLAST results first identified short fragments with sufficient similarity, which can then be …

Exploring Parents’ Perspective Of Outdoor Occupational Therapy Sessions, Harold Ho, Michelle Huynh, Christina Le, Amy Morrison

Master's Projects

Introduction: Outdoor play is recognized as critical for supporting children’s development across physical, cognitive, and social-emotional domains (Firby & Raine, 2022; Walker & Ray, 2024; Zhu et al., 2024). The current literature suggests that outdoor play strengthens executive functioning, early learning skills, and enhances social-emotional competency (Dinkel et al., 2019; Walker & Ray, 2024; Zhu et al., 2024). Furthermore, accessibility to outdoor play is shaped by contextual factors, including parental perceptions of safety, environmental barriers, and broader societal influences (Cox et al., 2025; Faulkner et al., 2025; Jelleyman et al., 2019). The research suggests that common parental concerns have emerged …

Combining Crispr And Nanoasv To Uncover The Rare Bacterial Communities Of The Human Oral Microbiome, Gilma Ruth Sevilla Alvarez

Master's Projects

Studying the oral microbiome is vital because its health implications are not contained to the mouth. Cariogenic bacteria cause tooth demineralization and oral microbes that translocate to extra-oral organ systems are linked to conditions like Alzheimer’s disease, heart disease, diabetes, and cancer. Some of these pathogens belong to the most abundant phyla in the oral cavity: Bacillota, Pseudomonadota, Bacteroidota, Actinomycetota, Spirochaetota, and Fusobacteriota, which together comprise 94% of the oral microbiome. This project uses CRISPR-Cas9 to deplete sequences from highly abundant phyla and the Eubacteria domain, enriching the remaining 6% of rarer taxa. Paired with NanoASV for single-nucleotide resolution, this …

Memory Effects In Many-Body Systems, Jeffrey Beckstrand

Master's Projects

This thesis investigates memory effects in many-body systems through the MoriZwanzig Formalism for projected dynamics of a Hamiltonian System which yields the Generalized Langevin Equation (GLE). The GLE is a stochastic differential equation (SDE) that studies the dynamics of observables under the effects of many other observables in the system. Although satisfying, the GLE has a term called the Memory Kernel that encodes the past of the system and introduces a computational challenge by introducing a non-Markovian property to the equation. The kernel is often approximated by introducing a delta function, which simplifies the computation, but at the loss of …

Investigating Ui Based And Ai Based Interactions In Vr Environments For Human Anatomy Education, Siddharth Sondhi

Master's Projects

Traditional approaches to learning and simulation often struggle to convey the complexity of three dimensional structures. In anatomy education, methods such as textbooks, lectures, and cadaver based learning are used, but can make it difficult to understand the complex structure of organs within the human body. Virtual Reality (VR) offers a promising alternative by providing immersive and interactive 3D environments that allow users to explore and manipulate anatomical structures more intuitively. These environments can be further enhanced by integrating large language models (LLMs) as intelligent agents capable of guiding users through natural language interaction. This project presents a Unity-based VR …

Sjsu Erfa News, Winter 2026, San Jose State University, Emeritus And Retired Faculty Association

Emeritus and Retired Faculty Association (ERFA) Newsletter

Volume 39, No 2

Scoring Equitable Transit: A Data-Driven Framework For Affordable Transit-Oriented Development In California, Ahoura Zandiatashbar, Anton Rozhkov, Stephanie Nemet, Atticus Washington, Mounashree Prasanna

Mineta Transportation Institute

Transit-Oriented Development (TOD) is a cornerstone of California’s climate and land use policy, promising walkable, compact neighborhoods near high-quality transit. However, these benefits are not always distributed equitably. This study introduces a scalable framework for identifying and scoring Affordable Transit-Oriented Development (A-TOD) across the state’s High-Quality Transit Areas (HQTAs). The goal is to equip policymakers, planners, and housing agencies with tools to evaluate station areas based on their physical form, affordability, and equity outcomes. Using a 1.5-mile network-based pedestrian buffer around over 66,000 transit stations, the research team developed a three-stage clustering and scoring system. Station areas were classified by …

Workforce Development Academy For Youth, Hassan Hashemian

Mineta Transportation Institute

To address the need for a diverse workforce in the 21st century and create an awareness of the career paths and opportunities that exist in the transportation industry, the College of Engineering, Computer Science, and Technology at the California State University, Los Angeles (CSULA) has created the Workforce Development Academy for Youth (WDAY). The goal of this program is to build a pipeline of diverse, well-qualified young professionals for the transportation industry. The program works with high school students and teachers to offer academic courses, basic skills, workforce readiness training, internships, extracurricular activities, and career placements to prepare students and …

Re-Evaluating Virtual Reality Manipulation Techniques For Precise Alignment Of Complex 3d Objects, Cherelle Connor, Alexander Giovannelli, Leonardo Pavanatto, Francielly Rodrigues, Haichao Miao, Vuthea Chheang, Brian Giera, Peer Timo Bremer, Doug A. Bowman

Faculty Research, Scholarly, and Creative Activity

Prior research has developed a number of manipulation techniques that can achieve precise object placement in virtual reality, but studies of these techniques typically use simple objects. We conducted a study comparing two existing techniques, (AMP-IT and WISDOM), during alignment of objects with complex geometry to evaluate the potential influence of geometric complexity on performance, usability, workload and preference. Our findings indicate that participants had faster completion times and higher trial completion rates with AMP-IT on high-precision alignment tasks, contrary to earlier findings that used simple objects. Yet WISDOM is still preferred and considered more usable, despite increased workload and …

Real-Time Defect Detection In Ceramic Additive Manufacturing Using Deep Convolutional Neural Networks, Dylan Doan, Amir Armani, Marcia Golmohamadi

Faculty Research, Scholarly, and Creative Activity

Although ceramic additive manufacturing technologies have greatly advanced over the past decade, they are still far from perfect. Even small printing defects can have a severe impact on the mechanical properties of additively manufactured ceramic parts due to their low fracture toughness. The objective of this study was to detect these defects during the printing process for a new ceramic additive manufacturing technique, called ceramic on-demand extrusion (CODE). Images were collected, pre-processed, augmented, and separated based on their distinctive classes (i.e., type of defects). Deep convolutional neural networks were developed to identify multiple types of defects in real-time.

The Ideological Work Of Penal Reform: How Reformers Justify Penal-Welfare Hybridization, John Halushka, Brandon Miller

Faculty Research, Scholarly, and Creative Activity

This article uses the Santa Clara County Reentry Resource Center (RRC) as a case study to explore the cultural content of penal reform. Specifically, we explore the discourses that officials use to publicly justify projects of penal-welfare hybridization, or the linking of state systems of punishment and welfare to manage criminalized populations. Our qualitative analysis draws on a dataset consisting of county planning documents, budgets, videos, press releases, and newsletters published online between 2011 and 2023. By examining these materials over time, we are able to chart patterns of consistency and variation in how officials justify hybridization. We find that …

The Energy Change Of Graphs Under Some Edges Deletions, Huan Lei Shi, Wen Huan Wang, Wasin So

Faculty Research, Scholarly, and Creative Activity

The energy ε(G) of a graph G is the sum of the absolute values of all the eigenvalues of its adjacency matrix. Gutman (2001) pointed out a problem to characterize the graph G and the edge e of G such that ε(G − e) ⩽ ε(G). Tang et al. (2023) gave a sufficient condition for ε(G − e) ⩽ ε(G), where e is not necessarily a cut-edge set or a cut edge. We deduce here a stronger conclusion than the results obtained by Tang et al. (2023). Our findings cover some known conclusions, such as the results obtained by Gutman …

South Asian Nutrition Guide For Heart Health: A Practical Guide To Sodium, Saturated Fat, Packaged Foods, Recipes And Meal Planning, Ashwini Wagle

Open Educational Resources

South Asians, including people with ancestry from India, Pakistan, Bangladesh, Sri Lanka, Nepal, Bhutan, and the Maldives, have a higher risk of cardiovascular disease and diabetes than many other populations. They often develop heart disease at younger ages and sometimes at lower body weights. (Jose, 2024; Patel et al., 2021; Volgman et al., 2018).

This increased risk is not caused by a single factor. Evidence points to a combination of inherited, metabolic, lifestyle, and social influences. Common contributors include insulin resistance, abdominal or visceral fat, type 2 diabetes, high triglycerides, low HDL cholesterol, elevated lipoprotein(a), family history, stress, migration-related changes …

South Asians And Renal Disease: Traditional Food Lists For Management Of Chronic Kidney Disease, Ashwini Wagle

Open Educational Resources

The renal food list is a culturally tailored nutrition education tool designed to address the specific dietary needs of the South Asian population. It is an original intellectual work created by Ashwini Wagle, Ed.D., MS, RD, FAND, Chair and Professor, Department of Nutrition, Food Science, and Packaging at San José State University (SJSU).

An earlier version of this tool was published in 2011 with the assistance of graduate student Kalpana Balasubramanian. The development of this renal food list was strengthened by the encouragement and support of the registered dietitian community, whose contributions included verifying the accuracy of the nutritional information …

Multi-Agent Path Planning And Optimization Using Q-Learning, Chirag Rudrish

Master's Projects

Robot navigation in a multi-agent setting requires a balance between safety and efficiency, especially in dense environments. In these two-dimensional spaces, the scope for geometric errors is much less and could lead to collisions or immobility. This project proposes to address the navigation task using a two-phase path planning pipeline that combines reinforcement learning and convex optimization in a scalable and robust manner. The first phase consists of generating diverse collision-free paths using a Q-learning agent that is trained on a visibility graph representation of the environment. The discretization of the environment using waypoint-based graphs allows the agent to train …

Multimodal Emotion Detection System, Shubhankar Sameer Munshi

Master's Projects

Trying to understand emotion from speech is a problem that is present in human computer interaction. Nevertheless, there are still some shortcomings in current SER methods. Text-based systems may miss vital vocal cues, such as sarcasm, tone changes, and delivery. On the other hand, purely audio-based systems are prone to noise and unstable acoustic features. The combination of linguistic and acoustic features in multimodal approaches partially solves this problem, but many existing approaches use inflexible multimodal fusion techniques that cannot adjust their behaviors according to the quality of input signals. In this work, we propose a multimodal approach based on …

Emotional Patterns In Conversational Social Media Using Graph-Based Context, Sai Sanjay Yerunkar

Master's Projects

Most social media datasets for emotion detection have not been constructed to account for conversational structure‚ so we investigate whether it carries signal for emotion prediction. Using Sentiment140 and GoEmotions Reddit threads‚ we construct their thread-based conversation graphs and compute the aggregated features of neighbors as well as the transformer and TF-IDF representations of comments. Connected comments are 4.5× more similar in emotions than expected by chance. Pairwise emotional similarity decays exponentially with geodesic distance (e.g.‚ after 2 hops). Pairs separated by a 30s timestamp difference have the highest emotional similarity. These results suggest that emotion is structured locally and …

Cost-Aware Predictive Routing For Vision-Language Models, Sahil Sait Naveed

Master's Projects

Vision-language models (VLMs) are increasingly used for multimodal tasks, but their inference costs vary widely across model tiers. This work presents a predictive routing framework that assigns each query to the most cost-effective VLM by using multimodal embeddings, clustering, and per-cluster model error estimates. Evaluated on six commercial VLMs, the selected router reduces average cost by about 49 percent relative to the quality-first setting on both validation and test. This comes with accuracy losses of 0.4 percentage points on validation and 0.9 on held-out test data. It also outperforms K-NN and ZeroRouter routing baselines while providing lowercost operating points than …

Adaptive Real-Time Fraud Detection Using Online Learning And Explicit Concept-Drift Detection, Purva Govind Tugaonkar

Master's Projects

Real-time credit card fraud detection faces challenges such as extreme class imbalance, delayed feedback, and concept drift in transaction streams. This project implements and evaluates an adaptive streaming fraud detection framework based on three methodologies: (1) online learning with incremental updates, (2) explicit conceptdrift detection using statistical monitoring, and (3) separate models for immediate and delayed supervision, combined with cost-sensitive learning and anomaly detection. The system processes the credit card fraud dataset in a batched streaming fashion, uses multiple online learners and ensembles. Experiments show that online, driftaware models maintain high recall on frauds while controlling false positives under imbalanced …

Modeling Sealed Deck Construction In Collectible Card Games Using Learning-To-Rank Approach, Michael Dinh Nguyen

Master's Projects

Artificial intelligence has demonstrated strong performance in complex decision-making domains such as chess and Go, motivating research into its application for games with even richer rules and combinatorial complexity. In collectible card games like Magic: The Gathering, deck construction from a constrained card pool is a critical and challenging task that requires evaluating card strength, synergy, and resource balance. This project explores whether machine learning, specifically learning-to-rank (LTR), can effectively model these human decision processes to construct competitive decks in a sealed format. The results found here can also be applicable to other areas of note, such as sports drafting …

Multi-Agent Path Planning And Optimization Using Q-Learning, Chirag Rudresh

Master's Projects

Robot navigation in a multi-agent setting requires a balance between safety and efficiency, especially in dense environments. In these two-dimensional spaces, the scope for geometric errors is much less and could lead to collisions or immobility. This project proposes to address the navigation task using a two-phase path planning pipeline that combines reinforcement learning and convex optimization in a scalable and robust manner. The first phase consists of generating diverse collision-free paths using a Q-learning agent that is trained on a visibility graph representation of the environment. The discretization of the environment using waypoint-based graphs allows the agent to train …

Uncovering The Disciplinary Pulse Of Library And Information Science Through Large-Scale Topic Modelling Of Openalex Scholarly Literature, Sailendra Malik, Sukumar Mandal

Library Philosophy and Practice (e-journal)

Library and Information Science is among the oldest and intellectually pluralistic scholarly disciplines but the inner thematic structure has not been established. The article develops a systematic and data intensive mapping of the field by the Latent Dirichlet Allocation topic modelling to 7,824 articles in the English language indexed in OpenAlex in the year 2000 to 2025. A ten topic solution is an optimised solution that identifies a group of readable and sensible thematic domains including information literacy digital libraries scientometrics archives and scholarly communication. The analysis of temporal trajectory reveals that there have been consistent expansion at the emergent …

Rethinking Library Opac: From Siloed Retrieval To Ai And Ml-Driven Discovery Using Fastapi And Mysql, Sukumar Mandal

Library Philosophy and Practice (e-journal)

The paper explores integration methods between MySQL and FastAPI to develop dynamic Online Public Access Catalog services including functionalities for modern libraries and information centers. It addresses evolving user expectations by replacing rigid keyword-based search models with adaptive, intelligent discovery experiences that prioritize search relevance. The goal involves transforming traditional library retrieval tools into contextual discovery platforms that effectively understand specific user intent and complex needs. The prototype was created on Ubuntu in a customized Python environment. It uses FastAPI to manage asynchronous API calls and MySQL to store bibliographic data. SQLAlchemy abstracts the database layer, and Pydantic validates data. …

Library Support For Massive Open Online Courses (Moocs) In The Philippines: The Case Of American Corners, Princess Grace Wooden, Darin Jan Tindowen

Library Philosophy and Practice (e-journal)

This study examined the role of libraries in supporting Massive Open Online Courses (MOOCs) in the Philippines, with particular focus on American Corners as library-based learning spaces. Grounded in the increasing demand for flexible and accessible education, the study aimed to assess the readiness of American Corner libraries and determine the extent of MOOC implementation, as well as examine the relationship between these variables. A quantitative descriptive-correlational research design was employed, involving 28 American Corner staff composed of directors and librarians from 14 participating institutions. Data were collected using a validated survey questionnaire and analyzed through frequency, percentage, weighted mean, …

Availability And Utilization Of School Library Resources And Its Impacts On The Academic Excellence Of Secondary School Students In Edo State., Iyobosa Ewere Mrs., Ben Asuquo, Glory Mbah Mrs.

Library Philosophy and Practice (e-journal)

The study examines availability, and utilization of school library resources and its impacts on the academic excellence in secondary school libraries in Edo state. The descriptive survey research was adopted for the study. The population of the study was 2162 senior secondary school students from Idia Girls’ College, Boiling Point Academy and UNIBEN Demonstration Secondary School. The sampling techniques used for the study was Random Sampling Technique, a total of 216 respondents was used as the sample size representing 10% of the total population. A well structured questionnaire was designed and distributed to respondents .A total of 216 copies of …

Impact Of Cigarette Smoke On Immune And Stromal Cells, Justin Wong

Master's Projects

Cigarette smoke is a plight on human health, being a major contributor to lung diseases. The aryl hydrocarbon receptor (AHR) directs immune regulation and metabolic adaptation in response to environmental toxins. This study investigates transcriptomic changes between wild-type and AHR knockout mouse lung tissue under smoke and air conditions. Single-cell RNA sequencing data were generated by the Butcher Lab and analyzed in Seurat for differential gene expression (DGE) analysis. A two way ANOVA framework was used with DGE analysis to classify genes as smoke induced or suppressed in an AHR dependent or independent manner, and these gene sets were analyzed …

Detection And Characterization Of Cancer Using Cfdna Fragmentomic Analysis, Guneet Bhogal

Master's Projects

Cell-free DNA (cfDNA) fragmentomics has emerged as a promising non-invasive approach for detecting and characterizing cancer by analyzing DNA fragmentation patterns. These fragment patterns are unique and can be used to distinguish between tumor and healthy DNA. This paper uses machine learning models to detect cancer by evaluating Shannon entropy of fragment lengths at the first coding exon 1 regions and correlating them to targeted cancer genes. This approach was applied to two datasets consisting of samples with prostate, breast, and lung cancers. Our results indicated that exon 1 fragmentation entropy captures biologically relevant differences in cancer-specific chromatin organization and …

Javatutor: An Integrated Llm Framework For Structured Programming Tutoring And Problem-Solving In Java, Amey Makarand Dhongade

Master's Projects

Large Language Models (LLMs) are being adopted more actively to assist in pro- gramming tasks, but much of the available AI code assistants devices are encouraging the rapid generation of solutions, as opposed to assisting students in developing an understanding. As a result, they can give the students correct code without teaching on how to judge a problem and how to build solutions or how to debug their programs themselves. This study describes JavaTutor, an LLM-based tutoring system that is used to assist learners in the learning process in a three-step process of understand- ing, generating a solution, and refining …

Safe-R2r: A Safety-Aware And Budget-Optimized Retrieval Controller For Rag Systems, Mandar Sunil Gondane

Master's Projects

Retrieval-Augmented Generation (RAG) improves factual grounding in large language models by incorporating external evidence during inference. However, most RAG systems rely on fixed retrieval strategies that ignore query difficulty, computational cost, and prediction uncertainty. This project introduces SAFE-R2R (Safety-Aware and Budget-Optimized Reason-to-Retrieve), a retrieval controller that treats retrieval as a query-dependent decision problem. SAFE-R2R organizes retrieval into a multi-rung ladder ranging from no retrieval to deeper retrieval with reranking. At each rung, the system generates an answer, computes reliability signals, and combines them into a risk score used within a conformal calibration framework to decide whether to accept the answer …

Stepwise Sudoku Reasoning Training Using Transformers, Lok Man Chu

Master's Projects

Sudoku is a constraint satisfaction problem that serves as a testbed for studying reasoning and stepwise deduction. While many solvers can produce correct solutions, they often fail to generate human interpretable sequences of logically consistent steps. This study investigates whether a transformer trained on stepwise deduction traces can learn to solve Sudoku puzzles through sequential, logically deducible moves. Results show that solve accuracy improves significantly with more training data, reaching approximately 78% at 1500k samples. Stepwise analysis indicates that the model effectively learns simple strategies, achieving near-perfect performance. However, performance on more complex strategies remains limited. Overall, while the model …