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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 …

Spartan Daily, April 21, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 35

Generative And Large Language Models For Library Knowledge Graphs, Partha Sarathi Mandal, Sukumar Mandal Dr

Library Philosophy and Practice (e-journal)

Structured Abstract

Purpose - Knowledge graphs play a key role in modern library and information services for information discovery, advanced search, and explainable recommendation systems. Recent progress in generative and large language models (LLMs) is changing. The present paper presents a clear and concise overview of how these models support knowledge graph construction in library and information science.

Design/methodology/approach –This study shows a conceptual and analytical approach. It considers the latest trends in generative models and LLMs as applied to the construction of knowledge graphs. Their application in entity extraction, relation identification, schema mapping, and triple generation on unstructured text …

Decolonizing The Academic Library: Examining The Successful Indigenization Of Ubc And Unm’S Library Services, Emily T. Villars

School of Information Student Research Journal

This article examines decolonization and indigenization initiatives at two academic libraries: the University of British Columbia (UBC) and the University of New Mexico (UNM). It asks how these institutions have implemented indigenization in their libraries and what lessons can inform broader reconciliation work across North America. Through a comparative lens, it analyzes how national and organizational frameworks, such as the Canadian Federation of Library Associations (CFLA-FCAB) Truth and Reconciliation Report and Recommendations and the American Indian Library Association’s (AILA) organizational goals, can shape these efforts. The study highlights three core strategies: decolonizing access and classification, transforming library spaces, and expanding …

Book Review: Academic Librarian Burnout: Causes And Responses Edited By Christina Holm, Ana Guimaraes, And Nashieli Marcano, Brianna Gaffney

School of Information Student Research Journal

No abstract provided.

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

Spartan Daily, April 15, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 33

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 …

Spartan Daily, April 14, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 32

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 …

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

Spartan Daily, 2026

Volume 166, Issue 31

Spartan Daily, April 8, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 30

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 …

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 …

Spartan Daily, April 7, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 29

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 …

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 …

Exploring Stakeholder Awareness, Institutional Support, And Implementation Of Co-Design In Higher Education: Challenges And Ai Readiness, Shrikant W. Ramteke

Library Philosophy and Practice (e-journal)

Abstract

Purpose In this paper, the gap between the discussion of co-design in the theory and its application in the higher education practice is identified. By contrasting the level of knowledge that the stakeholders possess regarding co-design, the support that the institutions provide them, and their implementation of co-design in practice, it leaves a few general trends, attitudes, and problems.

Design/methodology/approach We were given a structured survey, which measured composite indices of awareness, institutional support, implementation and AI readiness. The study used non-probability purposive sampling technique since it will address the stakeholders who have firsthand experience in the participatory design …

Clinically Aligned Long-Context Transformers For Cross-Platform Mental Health Risk Detection, Aditya Tekale, Mohammad Masum

Faculty Research, Scholarly, and Creative Activity

Social media platforms contain rich but noisy narratives of psychological distress, creating opportunities for early mental health risk detection. However, existing datasets capture heterogeneous constructs such as suicide risk severity, depression diagnosis, and DSM-5 symptom presence, and most prior models are trained and evaluated on a single corpus, limiting their clinical alignment and cross-dataset generalizability. In this study, we fine-tune a domain-specific long-document transformer, AIMH/Mental-Longformer-base-4096, for binary mental health risk detection (risk vs. no risk) using two clinically aligned Reddit datasets: the C-SSRS Reddit corpus and the eRisk 2025 depression dataset. To handle long user histories, we introduce an LLM-based …

Automating Administrative Burden In Algorithmic Criminal Record Expungement, Sarah Esther Lageson, Ericka B. Adams, Elsa Y. Chen

Faculty Research, Scholarly, and Creative Activity

Administrative burden describes the learning costs, psychological costs, and compliance costs people face when attempting to interface with the government, particularly in seeking a benefit. Algorithmic and automated processes offer the potential of reducing administrative burdens, but scant empirical research has determined to what, if any effect. This study uses the case of criminal record expungement in two policy contexts: traditional, court petition-based systems and newly enacted automated systems, to understand if and how administrative burden persists, and whether and how these burdens operate differently in the context of the criminal legal system. Drawing on interviews with 105 expungement-eligible people, …

Spartan Daily, March 26, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 28

Spartan Daily, March 25, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 27

Spartan Daily, March 24, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 26

Spartan Daily, March 19, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 25

Evidence Of Emperor Penguins’ Sensitivity To Sea Ice Fluctuations, Rose T.N. Foster-Dyer, David Iles, Leo Salas, David G. Ainley, Birgitte Mcdonald, Sharon Stammerjohn, Lise Viollat, David Ortega, Annie E. Schmidt, Grant Ballard, Carolynne Hultquist, Jonathan D. Tonkin, Michelle Larue

Faculty Research, Scholarly, and Creative Activity

Using satellite-derived abundance indices over 20 years, we investigated population change among the seven Ross Sea emperor penguin (Aptenodytes forsteri) colonies. We found a 90% probability that the Ross Sea metapopulation had lower springtime attendance between 2005 and 2024 (mean change = -23%; 95% CI: -46 to +20%). We identified two distinct phases of change: slightly increasing 2005 to 2019/2020, followed by a steep decline 2020-2024, resulting in a decrease of approximately 23 000 birds in 5 years or approximately 32% of the regional population. Over the 20 years, the two southernmost colonies, Cape Crozier and Cape Colbeck, increased in …

Spartan Daily, March 17, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 23