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Spartan Daily, April 28, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 38

Power Fuzzy Clustering: Flexible Distance Metrics And Inclusion Of Covariates, Phuc T. Nguyen, Cristina Tortora, Antonio Punzo

Faculty Research, Scholarly, and Creative Activity

Clustering is a fundamental task in statistics and machine learning aimed at identifying homogeneous groups within data. Among the available approaches, fuzzy clustering (FC) is particularly suited to poorly separated boundaries, as it allows partial memberships and captures uncertainty and overlapping structures. We introduce power fuzzy clustering (PFC), a general framework that unifies several FC methods, including fuzzy K-means and probabilistic distance clustering. By complementing the classical fuzzifier with a power parameter on distances, PFC enhances model flexibility while retaining interpretability. To accommodate clusters with different shapes and scales, we incorporate a volume parameter and alternative distance metrics (e.g., Mahalanobis …

Spartan Daily, April 23, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 37

Spartan Daily, April 22, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 36

Reconstructing Fire Progression From Uas Observations To Evaluate Bioaerosol Transport Sensitivity In Coupled Fire–Atmosphere Simulations, Isaac Forrest, Ali Tohidi, Angel Farguell, Aurélien Costes, Leda N. Kobziar, Phinehas Lampman, Eric Rowell, Adam Kochanski

Faculty Research, Scholarly, and Creative Activity

Bioaerosols released during wildland and prescribed fires may influence ecosystems, air quality, and microbial dispersal, yet their transport and deposition remain poorly understood. This study combined infrared uncrewed aircraft system (UAS) observations of a prescribed burn with the coupled fire–atmosphere model WRF-SFIRE and a Lagrangian particle model in order to evaluate how uncertainties in simulated fire behavior affect predicted bioaerosol (bacterial cell) transport and deposition. A reconstruction of the observed spatiotemporal evolution of the fire was derived from thermal UAS measurements acquired during the burn and incorporated into a WRF-SFIRE simulation, in which the modeled fire spread was constrained to …

Deep Learning Framework For Quantifying Self-Organization In Myxococcus Xanthus, Jiangguo Zhang, Eduardo A. Caro, Peiying Chen, Trosporsha Tasnim Khan, Patrick A. Murphy, Lawrence J. Shimkets, Ankit B. Patel, Roy D. Welch, Oleg A. Igoshin

Faculty Research, Scholarly, and Creative Activity

Under starvation, Myxococcus xanthus bacteria initiate a multicellular developmental program in which cells move to form fruiting bodies and differentiate into distinct cell types. Many genes affecting this process have been identified, and it is assumed that perturbing genes within the same pathway induces similar changes in the phenotype, although these changes may be subtle or obscured by pleiotropy. However, these pathways cannot be systematically mapped because there are no reliable methods for quantifying phenotype similarity. Here, we applied deep learning to quantify phenotype patterns and self-organization dynamics of 292 genetically distinct strains. We integrated ResNet and StyleGAN2 into a …

Nightlights For Older Adults: Enhancing Bedroom-To-Bathroom Transitions With Community Resident Feedback, Yue Luo, Aubrey Contreras, Susana Valdivia-Rivas, Yuhao Chen, Boyi Hu

Faculty Research, Scholarly, and Creative Activity

This study aimed to inform nightlight design by analyzing older adults’ subjective feedback and kinematic responses during evening activities. Twenty-seven older adults (mean age: 81 ± 6 years; 14 females) participated in the study. Their preferences for nightlight illuminance and hue were surveyed, and gait and posture adaptations under two illuminance levels were analyzed using spatiotemporal comparisons, principal component analysis (PCA) based analysis, and waveform reconstruction. The results revealed that older adults preferred low illuminance over high illuminance, with warm white and cool colors as the favored choices for evening lighting. Significant differences were observed in spatiotemporal gait variables, particularly …

Letter From The Dean: Research As A Way Of Becoming, Mehrdad Aliasgari

School of Information Student Research Journal

No abstract provided.

A Study Of Library Web Pages In Websites Of Government Degree Colleges In Telangana State, Dr. Mohammadi Asra Sultana

Library Philosophy and Practice (e-journal)

Libraries are an indispensable part of higher educational institutes. Academic websites provide us a virtual tour of the college. Library web pages in a college website are an important tool through which the students can be reached out to showcase and promote print and electronic resources, services, library activities, etc. The present study has been taken up to study the web pages of the websites of Government Degree Colleges in Telangana. Maximum number of colleges has uploaded information in their Digital Library button, followed by Library Services, Library Collection and Library Profile. A few colleges have uploaded information in other …

Agentic Hallucination Risk Scoring For Medical Llms Via Uncertainty Quantification And Clinical Knowledge Injection, Mayank Kapadia, Mohammad Masum

Faculty Research, Scholarly, and Creative Activity

Large Language Models (LLMs) have witnessed significant adoption across numerous domains since 2020, but their proclivity to hallucinate creates unacceptable dangers in high-risk environments like healthcare, where wrong outputs can directly jeopardize human safety. While present systems focus on pre-generation mitigation strategies, they cannot ensure the safety of individual outputs during inference. We provide a post hoc Hallucination Risk Scoring (HRS) methodology that intercepts questionable outputs before they reach patients via an agentic pipeline. Given a medical question, a domain-specific LLM generates an initial response from which five complimentary uncertainty signals are computed, which are then separated into a decision …

Spartan Daily, April 16, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 34

Beyond The Stacks: Borrowing Of Immersive Technologies And Smart Eco Systems To Reimagine Libraries., Vuppala Lingaiah

Library Philosophy and Practice (e-journal)

This theoretical Chapter explores the paradigm shift of knowledge access, user experience, and institutional viability through the integration of immersive technologies, such as augmented reality (AR), virtual reality (VR), mixed reality (MR), artificial intelligence (AI), and the Internet of Things (IoT), within the new paradigm of funky libraries, and how these technologies are changing knowledge access, user experiences, and the institutional sustainability of various library environments. Methodology: The research approach is non-empirical and exploratory-conceptual, based on a synthesis of systematic literature, thematic clustering of the existing literature, and theoretical critique of recent peer-reviewed findings. The chapter is based on more …

Equitable Estimation Of Accurate High Injury Networks (Hins) For Vulnerable Road Users, Anurag Pande, Anandamayee Majumdar, Lucas Roman Kantorowski

Mineta Transportation Institute

To improve traffic safety, communities first need to know where serious crashes are actually happening. High-Injury Networks are designed to identify these locations, but they are usually built using only police-reported crash data. This research asks: Are we missing crashes—and injuries—by relying on police data alone? The research team first demonstrates that data from Emergency Medical Services and those from official databases differ substantially, and neither data set captures the full extent of collisions in a community. Following that analysis, the research team concluded that a new data source may help complete this. Toward that end, the research team scraped …

Exploring The Stress-Strain Relationship Of Lightweight Concrete To Enhance The Lifecycle Performance Of Transportation Highways And Bridges, Fariborz M. Tehrani

Mineta Transportation Institute

Concrete is the primary construction material of bridges, roads, and other transportation infrastructure across the United States, but conventional normal-weight concrete (NWC) is heavy, prone to cracking, and expensive to maintain over time. This study examines the mechanical properties, durability, and lifecycle performance of lightweight aggregate concrete (LWC) and internally cured concrete (ICC) as alternatives in transportation infrastructure applications. Through laboratory testing, computer modeling, and lifecycle analysis, the research evaluates how these materials perform in terms of strength, flexibility, durability, cost, and environmental impact. The results show that LWC and ICC can meet required strength levels while being lighter and …

Results Of The Second Ice Shelf–Ocean Model Intercomparison Project (Isomip+), Claire K. Yung, Xylar S. Asay-Davis, Alistair Adcroft, Christopher Y.S. Bull, Jan De Rydt, Michael S. Dinniman, Benjamin K. Galton-Fenzi, Daniel Goldberg, David E. Gwyther, Robert Hallberg, Matthew Harrison, Tore Hattermann, David M. Holland, Denise Holland, Paul R. Holland, James R. Jordan, Nicolas C. Jourdain, Kazuya Kusahara, Dimitris Menemenlis, For Full Author List, See Comments Below

Faculty Research, Scholarly, and Creative Activity

Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2, which are ocean models with idealised, static ice shelf geometries, but where the ocean reaches …

Understanding Parents' Perspectives On Responsible Ai For Children's Self-Directed Learning, Jingyi Xie, Chuhao Wu, Ge Wang, Rui Yu, He Zhang, Ronald Metoyer, Si Chen

Faculty Research, Scholarly, and Creative Activity

Generative AI is increasingly present in children's learning environments, yet little is known about how families navigate this technology in middle childhood (ages 7-13), when parental guidance remains strong but children seek independence. Drawing on self-directed learning (SDL), we explore how parents in our exploratory sample perceived children's emerging self-directness and agency. Through focus groups with 13 parent-child pairs, we examine parents' views on children's AI literacy development, readiness factors, and mediation strategies. Parents described emergent pathways shaped by screen time, self-directness, and knowledge growth. They often confined AI to learning-only contexts, positioning it as a tutor while overlooking non-learning …

Spatiotemporal Dynamics Of Daily And Per Capita Vmt In California: A County-Level Analysis (2019–2023), Yong Lao, Bo Yang

Mineta Transportation Institute

Vehicle miles traveled (VMT) is a fundamental metric for assessing mobility trends and infrastructure needs. This study examines the spatial-temporal dynamics of daily VMT (DVMT) and per capita DVMT across California counties from 2019 to 2023, covering the pre-, mid-, and post-pandemic periods via GIS mapping and k-means clustering. To identify determinants of per capita DVMT, we compared traditional linear regression approaches (OLS, Ridge, LASSO, Elastic Net) with ensemble tree-based models. Specific results include: the ensemble models estimated using 2019–2022 data delivered substantially higher accuracy, achieving R² values exceeding 0.98; meanwhile, out-of-sample performance on 2023 data remained robust (R² ≈ …

The Responsibility Of Impact: Navigating Tech Awareness And Ethics In Leadership, Vishnu S. Pendyala

Open Educational Resources

This presentation was made as part of the Critical And Emerging Technology Seminar Series, Gilman International Scholarship Program held at MLK Library Room #217, San Jose, CA. USA.

Governance Challenges For A Rapid And Just Solar Energy Transition, Abigail Martin, Siddharth Sareen, Daniel M. Kammen, Dustin Mulvaney, Ryan Stock, Jonas Meckling, Ethan Elkind, Berenice Girard, Isa Ferrall-Wolf, Samuel Miles

Faculty Research, Scholarly, and Creative Activity

Solar energy is the fastest growing source globally, but must scale even more rapidly to meet climate change mitigation targets. Alongside this growth is a greater interest in avoiding the life cycle impacts of photovoltaics modules in evolving energy systems including undesirable land use change, unnecessary resource extraction, and opportunities for low impact designs. However, this presents numerous governance challenges. This study is motivated by the following research questions: 1) Where, how, and why does solar value creation entail the potential for social and environmental injustices? 2) What governance interventions are necessary to enable more equitable outcomes as these industries …

Spartan Daily, April 9, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 31

Audio Based Intelligence For Smart Autonomous Vehicles Using Deep Reinforcement Learning, Sweekruthi Balivada, Mansi Sanjaybhai Tanna, Meera Alpesh Dhedia, Jane Wu, Jerry Gao

Faculty Research, Scholarly, and Creative Activity

Efficient Advancements in intelligent transportation systems increasingly demand multimodal sensing frameworks capable of operating reliably under noisy, unpredictable real-world conditions. This research presents a Smart Car Audio Intelligence framework that leverages Machine Learn- ing (ML) and Reinforcement Learning (RL) to enhance real-time vehicle perception, safety, and situational awareness. Unlike traditional single-modality or static audio models, our approach integrates four specialized submodules - Emergency, Alert, Environmental/Human sounds, and Accident detection models which are each optimized through a combination of Transformer, CLAP, and CRNN architectures, augmented with adaptive RL agents. The ML models achieved strong baseline performance across all categories, with up …

Preparation And Characterization Of Double-Network Composite Hydrogels With Carboxymethyl Pachymaran In Promoting Wound Healing, Haodong Wu, Xi Feng, Zhinan Mei, Wen Huang, Ying Liu

Faculty Research, Scholarly, and Creative Activity

Utilizing food-derived bioactive polysaccharides in advanced biomedical applications offers significant potential. To effectively harness the inherent bioactivity of Poria cocos, a renowned edible and medicinal fungus, we developed a multifunctional double-network composite hydrogel (CPS) via a feasible one-pot strategy. This was achieved by incorporating functional carboxymethyl pachymaran (CMP) into a matrix of food-grade sodium alginate (SA) and polyacrylamide (PAM). This formulation endows the hydrogel with excellent extensibility, rapid self-healing capabilities, and strong tissue adhesion, all while preserving the biological activity of the natural macromolecules. In a mouse full-thickness skin defect model, the CPS significantly accelerated wound recovery, achieving a healing …

An Llm-Based Agentic Network Traffic Incident-Report Approach Towards Explainable-Ai Network Defense, Chia Hong Chou, Arjun Sudheer, Younghee Park

Faculty Research, Scholarly, and Creative Activity

Traditional intrusion detection systems for IoT networks achieve high classification accuracy but lack interpretability and actionable incident-response capabilities, limiting their operational value in security-critical environments. This paper presents a graph-based multi-agent framework that integrates ensemble machine learning with Large Language Model (LLM)-powered incident report generation via Retrieval-Augmented Generation (RAG). The system employs a three-phase architecture: (1) a lightweight Random Forest binary pre-detection, achieving 99.49% accuracy with a 6 MB model size for edge deployment; (2) ensemble classification combining Multi-Layer Perceptron, Random Forest, and XGBoost with soft voting and SHAP-based feature attribution for explainability; and (3) a ReAct-based summary agent that …

Simulations Of A High Ozone Episode And Heatwave Day Using A Coupled Multi-Layer Urban Canopy And Chemistry Model, H. Gamarro, W. M. Angevine, B. C. Mcdonald, R. Bornstein, P. Ramamurthy, F. Moshary, L. M. Judd, J. E. González-Cruz

Faculty Research, Scholarly, and Creative Activity

Coastal cities face critical challenges in managing ozone pollution because of high population density and complex interactions between urbanization and coastal meteorology. Using New York City (NYC) as a case study, this work examines how urban surfaces influence heatwaves, sea-breeze circulations, and boundary-layer dynamics, and how these processes shape nitrogen dioxide ((Formula presented.)) distributions and ozone formation. Observations from the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS), collected with an airborne high-resolution ultraviolet–visible spectrometer, provide tropospheric (Formula presented.) column densities for evaluating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in multiple urban canopy configurations. Results show …

Is Nostalgia The Hidden Mechanic Of Mmorpgs?, Zoee Sowders

ART 108: Introduction to Games Studies

Since the advent of online gaming, MMORPG video games have allowed players to socialize and collaborate within the bounds of a virtual world. For many, these online worlds were an escape from their daily lives, a place where they could meet people with similar interests and embark on adventures impossible in real life.1 While many of the early MMORPG games faded into obscurity after the genre lost its shiny new sparkle, there are still a handful today that maintain player counts in the millions even after nearly two decades of operation. Specifically, World of Warcraft, Runescape, and Final Fantasy XIV …

Rosetta-Xai: An Automated Evaluation And Explainability Framework For Code Translation Models, Vishnu S. Pendyala, Neha Bais Thakur

Faculty Research, Scholarly, and Creative Activity

This paper presents Rosetta-XAI, a comprehensive software framework for evaluating and explaining Large Language Model (LLM) behavior in cross-language code conversion tasks. The system implements a four-stage automated pipeline: (1) code generation by LLMs accessed through the Ollama API inference service, (2) regex-based extraction of code blocks from markdown responses, (3) language-specific syntax and compilation validation with temporary artifact management, and (4) execution with timeout protections and CSV-based checkpoint recovery. The framework supports evaluation of 15 specialized code LLMs (1.3B–34B parameters), including DeepSeek Coder, Code Llama, CodeGemma, and Granite Code across 17 Rosetta Code programming tasks, generating 42 bidirectional conversion …

Library 5.0 And Predictive Intelligence: A Conceptual Literature Review, Shrikant Ramteke

Library Philosophy and Practice (e-journal)

Abstract

Purpose In this paper, the author will explore the nature of predictive intelligence developed in modern libraries as part of the overall progression of libraries toward Library 5.0. It aims to give a conceptual clarity of what predictive services are, how they have been influenced by technology and ethics, and how they fit into existing traditions of librarianship.

Design/methodology/approach This paper utilizes a qualitative, conceptual literature review method as a scholarly inquiry. Approximately 60 peer-reviewed journal articles and institutional reports published after 2018 and before 2025 were purposively sampled from leading databases in library and information science and information …

Artificial Intelligence And Chatgpt In Libraries: A Bibliometric Analysis Of Social Science Research (2022–2026), Shrikant W. Ramteke, Yogesh B. Daphal

Library Philosophy and Practice (e-journal)

Purpose

This paper will map the world of research on artificial intelligence and chatbots in libraries systematically by analysing the trends in publications, intellectual organization, pattern of collaboration, and the way the Social Science literature has evolved with the theme of artificial intelligence and chatbots published between 2022 and 2026.

Design/methodology/approach

We have conducted a thorough bibliometric search where we have considered 7,660 peer-reviewed journal articles found in Scopus database. The collection was compiled according to the PRISMA requirements, and later, both performance-based metrics and science mapping techniques were applied.The whole process of visualisation and analysis was carried out through …

Development And Service Performance Of Active Anti-Icing Pavement Materials For Energy Efficiency Optimization Of Low-Enthalpy Geothermal Deicing Systems, Junming Mo, Jiading Jiang, Ke Wu, Lei Qu, Wenbin Wei, Jinfu Zhu

Faculty Research, Scholarly, and Creative Activity

To address high thermal loads and energy costs in Geothermal Road Snow-Melting Systems (GRSSs) within cold regions, this study optimizes energy efficiency through material-level intervention. We developed a composite anti-icing modifier synergistic with low enthalpy geothermal systems, comprising slow-release agents, anti-corrosive components, reinforcing materials, and active chloride salts. By regulating the thermodynamic boundary of the pavement, the freezing point is suppressed to −21 °C. This eliminates the requirement for positive pavement temperatures, significantly reducing the design thermal power. Chloride ion release patterns were analyzed via dissolution and 20-day soaking tests to evaluate structural durability. Results show optimal performance at a …

Measuring Multimodal Equity In Resource-Challenged Mpos, Christopher Ferrell, David Reinke, John M. Eells

Mineta Transportation Institute

Ensuring transportation investments are equitable across different populations and travel modes is a priority for many agencies, yet existing tools often make these assessments difficult, especially for smaller and resource-constrained organizations. To address this gap, this report provides the findings of Phase II of our study on reviewing and developing transportation equity metrics. The Phase I project investigated transit equity metrics and provided recommendations on advancements in quantitative methods. Building on Phase I recommendations, this study investigates low-cost methods for comparing the equity between auto (roadway) and transit performance or investments for low resource transportation agencies. A literature review revealed …