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The Effect Of Fluorides In The Tio2(B) Anode On The Hydrogen Evolution Reaction In Aqueous Electrolytes, Khoi-Nguyen Nguyen, Lam Hoang Nguyen, Jozel John Salvacion, Nam Huu Nhat Nguyen, Samuel Ming Tuk Yeung, Seung Woo Lee, Liat Rosenfeld, Chengyu Song, Dahyun Oh Jan 2026

The Effect Of Fluorides In The Tio2(B) Anode On The Hydrogen Evolution Reaction In Aqueous Electrolytes, Khoi-Nguyen Nguyen, Lam Hoang Nguyen, Jozel John Salvacion, Nam Huu Nhat Nguyen, Samuel Ming Tuk Yeung, Seung Woo Lee, Liat Rosenfeld, Chengyu Song, Dahyun Oh

Faculty Research, Scholarly, and Creative Activity

For aqueous lithium-ion batteries (A-LIBs), the hydrogen evolution reaction (HER) poses a significant challenge, as it competes with the primary electrochemical processes of the anode, resulting in capacity loss and reduced cycling stability. In this study, we investigate the use of fluorine-based additives in anodes to mitigate HER in LIBs with aqueous electrolytes including low or high amounts of salt (water-in-salt electrolytes (WiSE)). We synthesized and incorporated three distinct materials into TiO2(B) anodes: aluminum fluoride (AlF3), lithium fluoride (LiF), and 1H,1H,2H, 2H-perfluorooctyltriethoxysilane (FAS) using a solution-based method. Among these fluorides containing composite anodes, FAS containing anodes delayed HER onset potentials …

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Flip This Library Again! A Metaphorphosis: Evolving The School Library Into An Innovation Lab & Library Learning Commons (Illc), David Vickers Loertscher, Fran Kompar Jan 2026

Flip This Library Again! A Metaphorphosis: Evolving The School Library Into An Innovation Lab & Library Learning Commons (Illc), David Vickers Loertscher, Fran Kompar

Learning Hub

Drawing on significant reform education voices, the authors propose that credentialed school librarians add to their various library or learning commons services an innovation laboratory. Like a true laboratory, this includes physical and virtual space tests of major ideas, learning strategies and initiatives by administrators, teachers, and students as a major collaborative effort of the credentialed librarian. Such real world experiments happen in the spirit of a try before you buy strategy where some ideas will succeed, fail, or need modification before going viral in the school. It also places the library at the center of teaching and learning in …

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Hybridsense-Llm: A Structured Multimodal Framework For Large-Language-Model–Based Wellness Prediction From Wearable Sensors With Contextual Self-Reports, Cheng Huan Yu, Mohammad Masum Jan 2026

Hybridsense-Llm: A Structured Multimodal Framework For Large-Language-Model–Based Wellness Prediction From Wearable Sensors With Contextual Self-Reports, Cheng Huan Yu, Mohammad Masum

Faculty Research, Scholarly, and Creative Activity

Wearable sensors generate continuous physiological and behavioral data at a population scale, yet wellness prediction remains limited by noisy measurements, irregular sampling, and subjective outcomes. We introduce HybridSense, a unified framework that integrates raw wearable signals and their statistical descriptors with large language model–based reasoning to produce accurate and interpretable estimates of stress, fatigue, readiness, and sleep quality. Using the PMData dataset, minute-level heart rate and activity logs are transformed into daily statistical features, whose relevance is ranked using a Random Forest model. These features, together with short waveform segments, are embedded into structured prompts and evaluated across seven prompting …

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Codegen-3d: A Benchmark For Evaluating Llms In Zero-Shot And Iterative 3d Modeling In Blender, Hao Ji, Kotha Aditya, Sebastian Escalante, Yunjian Qiu Jan 2026

Codegen-3d: A Benchmark For Evaluating Llms In Zero-Shot And Iterative 3d Modeling In Blender, Hao Ji, Kotha Aditya, Sebastian Escalante, Yunjian Qiu

Faculty Research, Scholarly, and Creative Activity

Large Language Models (LLMs) that generate executable code are opening a new path to text-to-3D by converting natural language prompts into scripts for modeling software like Blender. However, there is a lack of evaluation for such methods currently. Existing benchmarks focus on direct mesh synthesis and overlook critical factors like code execution reliability and human-aligned quality. To address this gap, we introduce CodeGen-3D, a comprehensive benchmark and protocol for assessing 3D modeling via code generation. The benchmark consists of 100 diverse prompts derived from Objaverse with rich captions (Cap3D, DiffuRank, and Llama-based), a standardized Blender execution and six-view rendering pipeline, …

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Intelligent Prediction Model For Icing Of Asphalt Pavements In Cold Regions Oriented To Geothermal Deicing Systems, Junming Mo, Ke Wu, Jiading Jiang, Lei Qu, Wenbin Wei, Jinfu Zhu Jan 2026

Intelligent Prediction Model For Icing Of Asphalt Pavements In Cold Regions Oriented To Geothermal Deicing Systems, Junming Mo, Ke Wu, Jiading Jiang, Lei Qu, Wenbin Wei, Jinfu Zhu

Faculty Research, Scholarly, and Creative Activity

To address traffic safety hazards from asphalt pavement icing in Xinjiang’s cold regions and inefficiencies of conventional deicing and imprecise geothermal deicing systems, this study focused on local asphalt surfaces. Using “outdoor qualitative screening and indoor quantitative verification”, key variables were identified via controlled tests and their coupling effects on the time to complete icing were quantified through an L16(44) orthogonal test (a 4-factor, 4-level design encompassing 16 test groups). A Backpropagation (BP) neural network model (3 inputs, 5 hidden neurons, and a learning rate of 0.7) optimized with 64 datasets was established to predict the time to …

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Generative Algorithms For Wildfire Progression Reconstruction From Multi-Modal Satellite Active Fire Measurements And Terrain Height, Bryan Shaddy, Brianna Binder, Agnimitra Dasgupta, Haitong Qin, James Haley, Angel Farguell, Kyle Hilburn, Derek V. Mallia, Adam Kochanski, Jan Mandel, Assad A. Oberai Jan 2026

Generative Algorithms For Wildfire Progression Reconstruction From Multi-Modal Satellite Active Fire Measurements And Terrain Height, Bryan Shaddy, Brianna Binder, Agnimitra Dasgupta, Haitong Qin, James Haley, Angel Farguell, Kyle Hilburn, Derek V. Mallia, Adam Kochanski, Jan Mandel, Assad A. Oberai

Faculty Research, Scholarly, and Creative Activity

Highlights: What are the main findings? Conditional generative algorithms trained on simulations of historic wildfires may be used to effectively reconstruct the early-time progression of wildfires given satellite active fire measurements and terrain height data. When applied to real wildfires, generated fire progression estimates compare favorably to ground-truth high resolution infrared perimeters measured via aircraft, with the ability to gather additional information about model uncertainty from generated samples. What are the implications of the main findings? Once obtained, fire progression estimates may be used to perform data assimilation, wherein the estimated fire state is used to initialize subsequent wildfire spread …

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Evaluating Impact Of Occupational Exoskeletons On Physical Fatigue Using Wearable Sensors And Deep Learning, Hardik Vora, Fatemeh Davoudi Kakhki, Armin Moghadam Jan 2026

Evaluating Impact Of Occupational Exoskeletons On Physical Fatigue Using Wearable Sensors And Deep Learning, Hardik Vora, Fatemeh Davoudi Kakhki, Armin Moghadam

Faculty Research, Scholarly, and Creative Activity

Musculoskeletal disorders remain a leading source of occupational injury in manufacturing and logistics industries, often resulting from repetitive lifting and load transfer tasks. While back-support exoskeletons have shown promise in alleviating physical strain, their biomechanical impact under realistic task conditions and their integration with intelligent monitoring systems require further exploration. This study investigates the efficacy of a passive lumbar-support exoskeleton in reducing muscle fatigue during manual material handling tasks by combining high-resolution surface electromyography (sEMG) data with a deep learning-based classification framework. Ten participants performed lifting and rotational (twisting) tasks with and without exoskeleton assistance, while EMG signals were collected …

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Development And Characterization Of Compression-Molded Chitosan Composite Films Reinforced With Silica And Titania Fillers, Bhuvaneswari Koti, Vuong Do, Yanika Schneider, Vimal Viswanathan Jan 2026

Development And Characterization Of Compression-Molded Chitosan Composite Films Reinforced With Silica And Titania Fillers, Bhuvaneswari Koti, Vuong Do, Yanika Schneider, Vimal Viswanathan

Faculty Research, Scholarly, and Creative Activity

This study investigates the development of biodegradable chitosan-based films as a sustainable alternative to conventional non-biodegradable food packaging materials. Chitosan, a naturally occurring polymer, possesses inherent film-forming ability and biodegradability; however, its limited mechanical and thermal properties constrain its practical applications. In this work, chitosan films were fabricated via compression molding, and their thermo-mechanical performance was systematically evaluated. The incorporation of fillers, such as titanium dioxide and silica, resulted in a 50% enhancement in tensile strength and an 86% improvement in flexibility. Further optimization of dual-filler compositions led to an additional 45% increase in elasticity, demonstrating the potential of synergistic …

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Ga2o3 Tcad Mobility Parameter Calibration Using Simulation Augmented Machine Learning With Physics-Informed Neural Network, Edric Khai Jieh Ong, Le Minh Long Nguyen, Matthew Eng, Yuhao Zhang, Hiu Yung Wong Jan 2026

Ga2o3 Tcad Mobility Parameter Calibration Using Simulation Augmented Machine Learning With Physics-Informed Neural Network, Edric Khai Jieh Ong, Le Minh Long Nguyen, Matthew Eng, Yuhao Zhang, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

In this article, we demonstrate the feasibility of performing automatic technology computer-aideddesign (TCAD) parameter calibration and extraction using machine learning (ML), with the machine trained solely by TCAD-simulation data. The methodology is validated using experimental data. Schottky barrier diodes (SBDs) with different effective anode workfunctions (WF) are fabricated with emerging ultrawide bandgap material, Gallium Oxide (Ga2O3), and are measured at various temperatures (T). Their current-voltage (I–V) curves are used for automatic Ga2O3 Philips unified mobility (PhuMob) model parameters calibration. Five critical PhuMob parameters (µmax, µmin, Nref, α, and θ) were calibrated. The machine consists of an autoencoder (AE) and a …

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Scoring Equitable Transit: A Data-Driven Framework For Affordable Transit-Oriented Development In California, Ahoura Zandiatashbar, Anton Rozhkov, Stephanie Nemet, Atticus Washington, Mounashree Prasanna Jan 2026

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 …

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Numerical Modeling Of Climate Change Impacts On Transportation Embankments, Amr Morsy, Mamata Sapkota, Emma Varela, Odalys Portillo Jan 2026

Numerical Modeling Of Climate Change Impacts On Transportation Embankments, Amr Morsy, Mamata Sapkota, Emma Varela, Odalys Portillo

Mineta Transportation Institute

Embankments are essential components of transportation infrastructure, providing crucial support for long stretches of highways, railways, and other routes in California and around the world. Clay embankments are susceptible to weather-related deterioration processes that can gradually compromise their stability and, in some cases, lead to unexpected failures. Climate change, along with the associated shifts in weather patterns, is projected to adversely impact the weather-related deterioration processes, leading to exacerbated failures and/or shorter service life. Additionally, climate change is projected to increase the frequency of extreme precipitation events, leading to an increase in embankment failure potential. This study evaluated (1) the …

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Ideology And Iconography In Gustav Machatý’S Ecstasy (1933), Karl E. Toepfer Jan 2026

Ideology And Iconography In Gustav Machatý’S Ecstasy (1933), Karl E. Toepfer

Open Educational Resources

This essay discusses the cinematic construction of sexual ecstatic experience in Gustav Machaty's 1933 film Ecstasy. Sergei Eisenstein's theory of cinematic montage governs the shapes the way the filmmakers organize the representation of erotic desire and rapture. But the film also shows affinity with the Czech "Poetist" movement of the 1920s in constructing a guiding view of ecstatic experience. The essay analyzes many images in the film, and concludes with an application of montage theory of ecstatic cinema to the consumption of erotic videos and internet imagery.

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Investigating Ui Based And Ai Based Interactions In Vr Environments For Human Anatomy Education, Siddharth Sondhi Jan 2026

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 …

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Javatutor: An Integrated Llm Framework For Structured Programming Tutoring And Problem-Solving In Java, Amey Makarand Dhongade Jan 2026

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 …

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Adaptive Real-Time Fraud Detection Using Online Learning And Explicit Concept-Drift Detection, Purva Govind Tugaonkar Jan 2026

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 …

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Stepwise Sudoku Reasoning Training Using Transformers, Lok Man Chu Jan 2026

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 …

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Measuring The Scholarly Impact Of A Bibliography Of Canadian Inuit Periodicals, Sharon Rankin Jan 2026

Measuring The Scholarly Impact Of A Bibliography Of Canadian Inuit Periodicals, Sharon Rankin

Library Philosophy and Practice (e-journal)

This study examines how the scholarly impact of specialized bibliographies can be measured over time. Using A Bibliography of Canadian Inuit Periodicals as a case study, it applies Maleki's (2021) framework of fourteen impact metrics to assess the influence of a bibliography documenting periodicals by, for, and about Inuit communities in Canada. Evidence was found for nine impact indicators, including citation, discoverability, and online engagement measures. The findings demonstrate sustained scholarly use and highlight the value of both print and web-based bibliographic resources. In an era increasingly shaped by artificial intelligence and automated information retrieval, the study argues that curated …

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Multi-Agent Path Planning And Optimization Using Q-Learning, Chirag Rudrish Jan 2026

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 …

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Memory Effects In Many-Body Systems, Jeffrey Beckstrand Jan 2026

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 …

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Modeling Sealed Deck Construction In Collectible Card Games Using Learning-To-Rank Approach, Michael Dinh Nguyen Jan 2026

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 …

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Multi-Agent Path Planning And Optimization Using Q-Learning, Chirag Rudresh Jan 2026

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 …

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Real-Time Defect Detection In Ceramic Additive Manufacturing Using Deep Convolutional Neural Networks, Dylan Doan, Amir Armani, Marcia Golmohamadi Jan 2026

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.

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Empowering Students To Engage With Climate Change Action: A Project-Based Module For Artificial Intelligence Literacy And Sustainability Thinking, Gabriel Granco, Yu Chen, Heather Macias, Yunfei Hou, Frank A. Gomez Jan 2026

Empowering Students To Engage With Climate Change Action: A Project-Based Module For Artificial Intelligence Literacy And Sustainability Thinking, Gabriel Granco, Yu Chen, Heather Macias, Yunfei Hou, Frank A. Gomez

Faculty Research, Scholarly, and Creative Activity

There is a growing need to prepare students to address complex environmental challenges, particularly climate change and the expanding role of artificial intelligence (AI). This article examines the adaptation of the Artificial Intelligence for Social Good (AI4SG) Ideation module, a pitch- and project-based teaching framework designed to integrate AI literacy and sustainability education. Implemented in an upper division climate change course, the module combines project-based learning, culturally responsive pedagogy, and geographic thinking to guide students in developing community-oriented AI proposals aligned with the United Nations Sustainable Development Goals (SDGs). Students were encouraged to approach their communities not through deficit lenses, …

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Generation Of Impact Factor-Driven Security Rating Questionnaire Using Llms For Aiot Applications, Yuna Han, Simon Shim, Deva Kumar Gajulamandyam, Yeji Choi, Hyunwoo Lee, Hangbae Chang Jan 2026

Generation Of Impact Factor-Driven Security Rating Questionnaire Using Llms For Aiot Applications, Yuna Han, Simon Shim, Deva Kumar Gajulamandyam, Yeji Choi, Hyunwoo Lee, Hangbae Chang

Faculty Research, Scholarly, and Creative Activity

Industry 4.0 has transformed industries by accelerating the adoption of artificial intelligence of things (AIoT); however, it has also led to security risks, such as data leakage. Existing data protection research focuses on network layers, whereas application-layer rating systems rely on subjective evaluations, limiting consistency and applicability. This study proposes a scalable and objective AIoT security rating framework that clarifies ambiguities in the five-question rating system of the Korean Intellectual Property Office and unifies fragmented managerial and technical rating systems. By leveraging large language models (LLMs), the framework integrates a security rating model based on 14 impact factors with automated …

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Artificial Intelligence And Data Science In Agriculture Specialty Crops And Climate Change Modeling, Chandrasekar Vuppalapati Jan 2026

Artificial Intelligence And Data Science In Agriculture Specialty Crops And Climate Change Modeling, Chandrasekar Vuppalapati

Faculty Research, Scholarly, and Creative Activity

Specialty crops—fruits, vegetables, nuts, horticulture, and nursery crops—are a powerful engine of agricultural growth, contributing nearly one-fifth of U.S. farm revenues and driving a $1.6 trillion global market. As demand rises and climate challenges intensify, growers need smarter tools to stay competitive. This book brings together AI, data science, climate modeling, and economic forecasting to help farmers and innovators improve yields, manage risk, enhance sustainability, and secure long-term profitability. Designed for agricultural leaders, technologists, and policymakers, it delivers practical, future-ready solutions to strengthen specialty crop resilience and global food security. Presents the applications of data science and AI to agriculture …

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Workforce Development Academy For Youth, Hassan Hashemian Jan 2026

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 …

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Library Support For Massive Open Online Courses (Moocs) In The Philippines: The Case Of American Corners, Princess Grace Wooden, Darin Jan Tindowen Jan 2026

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, …

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Rethinking Library Opac: From Siloed Retrieval To Ai And Ml-Driven Discovery Using Fastapi And Mysql, Sukumar Mandal Jan 2026

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. …

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Uncovering The Disciplinary Pulse Of Library And Information Science Through Large-Scale Topic Modelling Of Openalex Scholarly Literature, Sailendra Malik, Sukumar Mandal Jan 2026

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 …

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Low-Carbon Green Hydrogen Strategies For Sustainable Development In Senegal: A Wind Energy Perspective, Astou Sarr, Mamadou Simina Dramé, Serigne Abdoul Aziz Niang, Abdoulkader Ibrahim Idriss, Haitham Saad Mohamed Ramadan, Ali Ahmat Younous, Kharouna Talla, John Robert Bagarino, Marissa Jasper, Ismaila Diallo Dec 2025

Low-Carbon Green Hydrogen Strategies For Sustainable Development In Senegal: A Wind Energy Perspective, Astou Sarr, Mamadou Simina Dramé, Serigne Abdoul Aziz Niang, Abdoulkader Ibrahim Idriss, Haitham Saad Mohamed Ramadan, Ali Ahmat Younous, Kharouna Talla, John Robert Bagarino, Marissa Jasper, Ismaila Diallo

Faculty Research, Scholarly, and Creative Activity

This study presents the first comprehensive techno-economic assessment of wind-based green hydrogen production across Senegal, a country highly dependent on fossil fuel imports. Using a novel integrated approach combining 30 years of ERA5 reanalysis data (1993–2023), turbine performance modeling and electrolyzer comparison, it fills an important gap for renewable hydrogen development in West Africa. Wind resources were analyzed at multiple altitudes, revealing strong potential in both coastal and northeastern regions, particularly during the dry season, with higher wind speeds at higher turbine heights. Four turbines (Vestas_150, Goldwind_155, Vestas_126 and Nordex_N100) and two electrolyzer types (alkaline and PEM) were evaluated. The …

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