Physical Sciences and Mathematics Commons^™

Leveraging Large Language Models To Create Learner Personas For Training Design, N. Lovett, M. Yang, K. Herman, B. Li, M. Sosonkina, W. Purwanto, P. Jiang, M. H. Wu

Electrical & Computer Engineering Faculty Publications

This case examines the innovative use of Large Language Models (LLMs) to generate learner personas for developing learner-centered cybersecurity training materials when direct access to initial learner data is not available. The team developed a nine-stage iterative process for creating and refining AI-generated personas to address this constraint, integrating ethical review, stakeholder feedback, and action research principles. The process expanded upon Kouprie and Visser’s (2009) empathic design framework to ensure cultural responsiveness and mitigate potential biases in LLM outputs. Through multiple refinement cycles, initial generic personas evolved into detailed, context-rich archetypes which informed the development of effective and context-responsive training …

Time-Marching Quantum Algorithm For Simulation Of Nonlinear Lorenz Dynamics, Efstratios Koukoutsis, George Vahala, Min Soe, Kyriakos Hizanidis, Linda Vahala, Abhay K. Ram

Electrical & Computer Engineering Faculty Publications

Simulating nonlinear classical dynamics on a quantum computer is an inherently challenging task due to the linear operator formulation of quantum mechanics. In this work, we provide a systematic approach to alleviate this difficulty by developing an explicit quantum algorithm that implements the time evolution of a second-order time-discretized version of the Lorenz model. The Lorenz model is a celebrated system of nonlinear ordinary differential equations that has been extensively studied in the contexts of climate science, fluid dynamics, and chaos theory. Our algorithm possesses a recursive structure and requires only a linear number of copies of the initial state …

Energy-Aware Swarm Robotics In Smart Microgrids Using Quantum-Inspired Reinforcement Learning, Mohamed Shili, Salah Hammedi, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

The integration of autonomous robots with intelligent electrical systems introduces complex energy management challenges, particularly as microgrids increasingly incorporate renewable energy sources and storage devices in widely distributed environments. This study proposes a quantum-inspired multi-agent reinforcement learning (QI-MARL) framework for energy-aware swarm coordination in smart microgrids. Each robot functions as an intelligent agent capable of performing multiple tasks within dynamic domestic and industrial environments while optimizing energy utilization. The quantum-inspired mechanism enhances adaptability by enabling probabilistic decision-making, allowing both robots and microgrid nodes to self-organize based on task demands, battery states, and real-time energy availability. Comparative experiments across 1500 grid-based …

Energy-Aware Sensor Fusion Architecture For Autonomous Channel Robot Navigation In Constrained Environments, Mohamed Shili, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

Navigating autonomous robots in confined channels is inherently challenging due to limited space, dynamic obstacles, and energy constraints. Existing sensor fusion strategies often consume excessive power because all sensors remain active regardless of environmental conditions. This paper presents an energy-aware adaptive sensor fusion framework for channel robots that deploys RGB cameras, laser range finders, and IMU sensors according to environmental complexity. Sensor data are fused using an adaptive Extended Kalman Filter (EKF), which selectively integrates multi-sensor information to maintain high navigation accuracy while minimizing energy consumption. An energy management module dynamically adjusts sensor activation and computational load, enabling significant reductions …

Flux-Weakening Control Methods For Permanent Magnet Synchronous Machines In Electric Vehicles At High Speed, Samer Alwaqfi, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Permanent magnet synchronous motors (PMSMs) are widely favored by manufacturers for use in electric vehicles (EVs) because of their many benefits, which include high power density at high speeds, ruggedness, potential for high efficiency, and reduced control complexity. However, since the Back Electromotive Force (EMF) increases proportionally with the motor’s rotational speed, it must be carefully controlled at high speeds. Flux-weakening (FW) control is required to avoid excessive electromagnetic flux beyond the power source and inverter’s voltage restrictions. This paper aims to compare various FW control strategies and analyze their effectiveness in maximizing the speed of PMSMs in EV applications …

Streamer Discharge Modeling For Plasma-Assisted Combustion, Stuart Reyes, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

Some of the popular and successful atmospheric pressure fuel/air plasma-assisted combustion methods use repetitive ns pulsed discharges and dielectric-barrier discharges. The transient phase in such discharges is dominated by transport under strong space charge from ionization fronts, which is best characterized by the streamer model. The role of the nonthermal plasma in such discharges is to produce radicals, which accelerates the chemical conversion reaction leading to temperature rise and ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to develop a predictive model. We examine the important characteristics of streamers that influence combustion and develop some …

Advances In Battery Modeling And Management Systems: A Comprehensive Review Of Techniques, Challenges, And Future Perspectives, Seyed Saeed Madani, Yasmin Shabeer, Ananthu Shibu Nair, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, Shi Xue Dou, Khay See, Saad Mekhilef, Françios Allard

Electrical & Computer Engineering Faculty Publications

Energy storage systems (ESSs) and electric vehicle (EV) batteries depend on battery management systems (BMSs) for their longevity, safety, and effectiveness. Battery modeling is crucial to the operation of BMSs, as it enhances temperature control, fault detection, and state estimation, thereby maximizing efficiency and preventing malfunctions. This paper thoroughly examines the most recent advancements in battery and BMS modeling, including data-driven, thermal, and electrochemical methods. Advanced modeling approaches are explored, including physics-based models that incorporate mechanical stress and aging effects, as well as artificial intelligence (AI)-driven state estimation. New technologies that facilitate data-driven decision-making, real-time monitoring, and simplified systems include …

The Effect Of Electrode Geometry On Excited Species Production In Atmospheric Pressure Air-Hydrogen Streamer Discharge, Shirshak Kumar Dhali, Stuart Reyes

Electrical & Computer Engineering Faculty Publications

When a gas is overvolted at or near atmospheric pressure, it results in a streamer discharge formation. Electrode geometries exert significant impact on the electrical breakdown of gases by altering the spatial profile of the electric field. In many applications the efficient generation of radicals is critical and is determined by the characteristics of the streamer discharge. We examine the effect of electrode geometry on the streamer characteristics and the production of radicals. This is performed for three different electrode geometries: plane–plane, pin–plane, and pin–pin. A two-dimensional rotationally symmetric fluid model is used for the streamer discharge simulation in the …

The Effect Of Electrode Geometry On Excited Species Production In Atmospheric Pressure Air–Hydrogen Streamer Discharge, Shirshak Kumar Dhali, Stuart Reyes

Electrical & Computer Engineering Faculty Publications

When a gas is overvolted at or near atmospheric pressure, it results in a streamer discharge formation. Electrode geometries exert significant impact on the electrical breakdown of gases by altering the spatial profile of the electric field. In many applications the efficient generation of radicals is critical and is determined by the characteristics of the streamer discharge. We examine the effect of electrode geometry on the streamer characteristics and the production of radicals. This is performed for three different electrode geometries: plane–plane, pin–plane, and pin–pin. A two-dimensional rotationally symmetric fluid model is used for the streamer discharge simulation in the …

Enhancing Cyber Situational Awareness Through Dynamic Adaptive Symbology: The Dass Framework, Nicholas Macrino, Sergio Pallas Enguita, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The static nature of traditional military symbology, such as MIL-STD-2525D, hinders effective real-time threat detection and response in modern cybersecurity operations. This research introduces the Dynamic Adaptive Symbol System (DASS), a novel framework enhancing cyber situational awareness in military and enterprise environments. The DASS addresses static symbology limitations by employing a modular Python 3.10 architecture that uses machine learning-driven threat detection to dynamically adapt symbol visualization based on threat severity and context. Empirical testing assessed the DASS against a MIL-STD-2525D baseline using active cybersecurity professionals. Results show that the DASS significantly improves threat identification rates by 30% and reduces response …

Ai-Based Steganography Method To Enhance The Information Security Of Hidden Messages In Digital Images, Nhi Do Ngoc Huynh, Jiajun Jiang, Chung-Hao Chen, Wen-Chao Yang

Electrical & Computer Engineering Faculty Publications

With the increasing sophistication of Artificial Intelligence (AI), traditional digital steganography methods face a growing risk of being detected and compromised. Adversarial attacks, in particular, pose a significant threat to the security and robustness of hidden information. To address these challenges, this paper proposes a novel AI-based steganography framework designed to enhance the security of concealed messages within digital images. Our approach introduces a multi-stage embedding process that utilizes a sequence of encoder models, including a base encoder, a residual encoder, and a dense encoder, to create a more complex and secure hiding environment. To further improve robustness, we integrate …

Enhancing Channel Data Savings And Information Transfer Efficiency In Ultrasound Imaging, Sai Konda, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Ultrasound is a popular imaging technique mainly due to its non-invasive nature. And so, it is being used in a variety of applications. Due to plane wave imaging technique in ultrasound, frame rate of ultrasound imaging has the potential for being very high. Due to which, many channel data frames are being generated within a few seconds. As a result, tasks such as storing data frames and transferring them from front end ultrasonic system to processing computers are presenting significant challenges. Our current research work minimized these issues. We proposed and implemented: (a) Data encoding technique - We combined every …

Quantum Efficiency, Electron Spin Polarization And Lifetime Study For Gaas Based Truncated Nanocone Array Photocathodes, Md. Aziz Ar Rahman, Greg Blume, Md Abdullah Mamun, Shukui Zhang, Hani Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

[First slide] Direct band-gap photocathode (Eg = 1.42 eV).

Valence band maximum (VBM) is doubly degenerate, Max. electron spin polarization (ESP) ~35-40%.

Strained-supperlattice (SSL) removed the VBM degeneracy, ESP ~85-90% with QE of ~1% at 780 nm.

Requires UHV: Lifetime ~200 C with ~200 μA beam current.

Ion-back bombardment degrades the lifetime.

Improvement in charge lifetime required for JLAB polarized positron source program: 1mA-10mA beam current for 2 weeks ~ 10³10⁴C.

An Overview Of Video Game Biometrics Collection And Considerations For Cyberbiosecurity, Lucas Potter, Christen Westberry, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Over the past fifty years, the global cost of consumer electronics has significantly decreased, leading to greater accessibility to both biosensing systems and interactive entertainment platforms. This increased access has naturally resulted in higher usage of medical and entertainment electronics. However, the intersection of these technologies, combined with invasive data harvesting practices, has raised concerns about the potential misuse of biological signals to manipulate individuals' behavior both within and beyond the video game environment. Currently, biometric data in video games are employed in various ways, such as using Heart Rate Variability (HRV) as a performance metric and integrating eye tracking …

Scope And Mechanism Of The Ruthenium-Catalyzed Sp3 C–H Coupling Reaction Of 2-Alkylindoles With Enones For The Synthesis Of Carbazole Derivatives, Krishna Prasad Gnyawali, Mina Son, Donghun Hwang, Nuwan Asanka Pannilawithana, Mu-Hyun Baik, Chase S. Yi

Chemistry Faculty Research and Publications

The catalytic system consisting of a cationic Ru–H complex 1 and 3,4,5,6-tetrachloro-1,2-benzoquinone (L1) was found to be highly effective for the dehydrative sp³ C–H coupling reaction of 2-alkyl substituted indoles with enones to form 2,4-disubstituted carbazole products. The analogous coupling reaction of 2-alkylindoles with linear enones bearing the cyclic olefinic group afforded tetracyclic carbazole products. A normal deuterium kinetic isotope effect was measured from the coupling reaction of 1,2-dimethylindole versus 1-methyl-2-(methyl-d₃)indole with (E)-3-penten-2-one (k_H/k_D = 2.5). The Hammett plot was constructed from the reaction of para-substituted …

Fostering Critically Conscious Lesson Planning In A Generative Artificial Intelligence Era, Derek Riddle, Paula Cristina Azevedo, Catharyn Shelton, Jaime Colwell, Jori Beck

Teaching & Learning Faculty Publications

Teacher candidates (TCs) use digital resources and social media to plan and develop learning material, and with publically accessible generative artificial intelligence (GAI), TCs are able to generate lesson plans within seconds rather than hours or days. While there is research on how to support TCs' evaluation of reliable digital media, there is little known on how to prepare TCs for GAI content. Using the complementary frameworks of Freire’s (1970) critical consciousness and Jonnasen’s (1991) theory of constructivism, this in-progress design based research seeks to develop an adaptable framework that addresses the evolving nature of technology, specifically GAI, and the …

S-Methyl Cysteine Sulfoxide And Its Potential Role In Human Health: A Scoping Review, Caroline R. Hill, Alex Haoci Liu, Lyn Mccahon, Liezhou Zhong, Armaghan Shafaei, Lois Balmer, Joshua R. Lewis, Jonathan M. Hodgson, Lauren C. Blekkenhorst

Research outputs 2022 to 2026

Higher intakes of cruciferous and allium vegetables are associated with a lower risk of cardiometabolic-related outcomes in observational studies. Whilst acknowledging the many healthy compounds within these vegetables, animal studies indicate that some of these beneficial effects may be partially mediated by S-methyl cysteine sulfoxide (SMCSO), a sulfur-rich, non-protein, amino acid found almost exclusively within cruciferous and alliums. This scoping review explores evidence for SMCSO, its potential roles in human health and possible mechanistic action. After systematically searching several databases (EMBASE, MEDLINE, SCOPUS, CINAHL Plus Full Text, Agricultural Science), we identified 21 original research articles meeting our inclusion criteria. These …

A Swirling Offering: Climate Change Impacts On Incense And Other Useful Alpine Plants Of Bhutan, Nidup Gyeltshen, Choki Gyeltshen, Sangay Dema, Suresh K. Ghimire, Natalie Konig, Robbie Hart

Research outputs 2022 to 2026

Climate change impacts on social-ecological systems —such as useful plant harvest— can be elucidated through local perceptions and ecological monitoring. To better understand how these two approaches may show convergent or divergent perspectives on a shared system, we conducted semi-structured interviews on climate change impacts on useful plants in the alpine region of Central Bhutan, contextualized with results from ecological monitoring at the same site. Participants reported 42 useful alpine plant species. Incense plants were the most frequently cited and prioritized in free-lists (three times more likely to be mentioned first), ahead of other common uses (food, medicine). Most participants …

A Framework For Mixed Reality Within Healthcare Education, Benyamin Ebadinia

Theses

Understanding complex three-dimensional systems and spatial relationships is a recurring difficulty in healthcare education, where students are often expected to reason about internal structures and multi-system processes from 2D diagrams, textbook figures, and static mannequins. This thesis presents the design, implementation, and mixed-methods evaluation of Systems Simulation, a reusable mixed reality (MR) application intended to help undergraduate nursing students explore human anatomy and pathophysiology using immersive 3D visualization.

Built in C# with the StereoKit framework for Microsoft HoloLens 2, Systems Simulation organizes nine anatomical body systems within a shared application. Learners can select a system, anchor the model in their …

Perceptions, Efficacy, And Adaptation Of Online Learning In Physics And Chemistry Education, Fun Man Fung, Jia Yi Han, Min Xin Pua

Journal of Educational Technology Development and Exchange (JETDE)

The COVID-19 pandemic forced a sudden shift to online learning in Physics and Chemistry in Singapore. As restrictions eased, researchers explored its impact through interviews with instructors and analysis of student data made available through a data lake managed by the National University of Singapore’s Institute for Applied Learning Sciences and Educational Technology. Interviews focused on instructor adaptation and beliefs about online teaching, while the data investigated student perceptions and changes in teaching efficacy pre- and post-pandemic. Analysis of the students’ course feedback indicated that Course Code C005 received more positive feedback from students, particularly towards the instructor’s effectiveness in …

An Exploratory Attempt To Incorporate Social Criteria Into Spent Nuclear Fuel Site Screening And Relocation, Julie M. Sorfleet

Cal Poly Humboldt theses and projects

Spent nuclear fuel, also known as nuclear waste, is the byproduct of nuclear power generation. The need for safe and responsible long-term storage and disposal of radioactive fuel presents significant technical and social challenges. These challenges are compounded by several factors, including the emerging nuclear renaissance in the United States, climate and coastal hazards, and the lack of consolidated interim or permanent storage. This research explores perceptions of risk, relocation, and siting spent nuclear fuel, predominantly focusing on Humboldt County, California. I used online surveys, the Analytic Hierarchy Process, and geographic information systems (GIS) analysis to inform how social and …

Campesino World-Building: Stories Of Migration, Memory, And Care In The Tension Of The Colonial Frame, Chelsea Ríos Gómez

Cal Poly Humboldt theses and projects

Campesinos, often reduced to the label of “farmworkers”, are too often seen only through the lens of their labor within profit-driven systems. This thesis disrupts that limited narrative by illuminating the rich, expansive nature of vivencias campesinas, ways of being that transcend capitalist measures of value. These vivencias are lived, embodied experiences rooted in campesino lifeways, encompassing cultural, spiritual, and relational practices that nurture and sustain life.

My research is guided by four central questions: (1) In what ways have campesinos in pixley resisted exploitative labor systems, and how can this resistance be understood as a form of care labor? …

North American River Otter (Lontra Canadensis) Prey Selection Of Wintering Waterbirds In A Wetland Complex, Gina Yael Culver

Cal Poly Humboldt theses and projects

Generalist predators are assumed to take a wide variety of prey throughout an annual cycle, often switching between food sources depending on availability. Prey selection is often studied by way of variables such as prey age class, body size, and various topics related to anti-predator behaviors, all variables used to measure how predators target prey. Following prior studies in coastal Northern California documenting that river otters (Lontra canadensis) had selected waterbirds as prey, we identified undigested prey items in scat to evaluate prey selection of waterbirds at the Arcata Marsh and Wildlife Sanctuary (AMWS). We compared feathers found …

An Economic And Production Analysis Of Seaweed Farms In California And The Pacific Northwest, Brian Donovan

Cal Poly Humboldt theses and projects

Since the early 2010s, the seaweed aquaculture industry has steadily expanded in the United States, with states like Alaska, Maine, Hawaii, and Connecticut leading the way in the development of this emerging sector. However, information gaps remain concerning certain aspects of the domestic seaweed aquaculture industry. The purpose of this study was to examine the status of the seaweed aquaculture industry along the West Coast of the United States; specifically in the states of California, Oregon, and Washington. Seaweed farmers in these states were invited to voluntarily complete surveys asking important production, economic, and commercial questions regarding their operations. Data …

Common Raven Habitat Selection Along The Northern California Coast, Alon Averbuj

Cal Poly Humboldt theses and projects

Nest predation by common ravens (Corvus corax) is considered one of the most significant barriers to the recovery of the population of the federally threatened western snowy plovers (Anarhyncus nivosus nivosus) in Northern California. To increase productivity of snowy plovers, conservation managers in Northern California employ three main techniques; placing symbolic fencing to deter pedestrian entrance to snowy plover nesting areas, invasive vegetation cutback, and deposition of oyster shells to increase snowy plover nest crypsis. However, little is known on how these techniques affect habitat selection of ravens in the area. I modeled habitat selection of …

Open Path Spectroscopic Detection Of The Hydroxyl Radical: A Comparison Between Broadband Cavity-Enhanced Absorption Spectroscopy (Bbceas) And Bbceas Coupled With A Fabry-Pérot Interferometer (Bbceas-Fp), Callum Flowerday, Ryan Thalman, Matthew C. Asplund, Samuel A. Badstubner, Adam K. Cook, Philip Lundrigan, Jaron C. Hansen

ScholarsArchive Data

Data collected by the BBCEAS and BBCEAS-FP instruments described in the paper "Open Path Spectroscopic Detection of the Hydroxyl Radical: A Comparison Between Broadband Cavity-Enhanced Absorption Spectroscopy (BBCEAS) and BBCEAS coupled with a Fabry-Pérot Interferometer (BBCEAS-FP)"

Exploring Coastal Spaces Of Tribal Sovereignty And Self-Determination In Ancestral Waters Proposed For Offshore Wind Development, Alyssa Suarez

Cal Poly Humboldt theses and projects

Proposed offshore wind development off California’s North Coast raises novel questions about Tribal sovereignty offshore. This project specifically engages claims, assuming the Yurok Tribe’s framing that offshore wind development poses a coastal hazard. The research followed a co-production framework. The research questions were co-designed with the Yurok Tribe and the research itself governed by a Data Sharing Agreement. The work presents findings from 13 semi-structured interviews with individuals and experts navigating sovereignty in the offshore wind space, including government representatives; lawyers; legal researchers; academics; foundation staff; journalists; and Humboldt Bay community members. Participants identified several key tensions surrounding claims of …

Machine Learning For Computer-Aided Diagnostics From Complex Medical Images, Afsah Saleem

Theses: Doctorates and Masters

Machine learning has significantly transformed medical image analysis in the current age of artificial intelligence offering vast potential in improving disease diagnosis and management. Cardiovascular diseases (CVDs) are among the leading cause of global mortality, emphasizing the need for early detection for effective intervention and prevention. Abdominal Aortic Calcification (AAC) is an early indicator and contributor to Atherosclerotic Cardiovascular Diseases (ASCVDs) and is commonly assessed through imaging modalities such as computed tomography (CT), X-rays, and Dual-energy X-ray Absorptiometry (DXA). Among these, lateral spine DXA scans, commonly used for osteoporosis screening, offer a cost-effective and low-radiation opportunity for opportunistic CVD risk …

Modelling The Impacts Of Recreational Catch-And-Release Variability On Fish Stock Dynamics, Brett Crisafulli

Theses: Doctorates and Masters

Recreational fisheries often lack sufficient data for robust stock assessments, and post-release mortality (PRM) of discarded fish, particularly demersal species, poses a significant threat to sustainability. Because demersal fish often experience higher PRM (often due to barotrauma and stress), the substantial global interest in their recreational fisheries (e.g., Australia, Gulf of Mexico, Western Baltic Sea) raises conservation concerns. This study employs three distinct modelling approaches, applied to four reef-dwelling demersal species, to support effective recreational fisheries management by addressing data uncertainty, unintended consequences of management changes, and PRM effects. Specifically, this thesis (1) evaluates variability in average weights of recreationally-caught …

Embodied Ai For Challenging Rearrangement Tasks In The Context Of Service And Assistive Robots, Mariia Khan

Theses: Doctorates and Masters

Embodied AI explores intelligent agents that learn through interaction with their environment, aiming to replicate human-like learning processes. Achieving this requires agents capable of understanding a scene via various sensors, reasoning about their actions, and reacting accordingly. These abilities are necessary for service domestic robots to assist humans in their day-to-day activities. Embodied AI tasks can include but are not limited to: visual exploration, visual navigation, instruction following and embodied question answering, which typically consider static (unchanging) environments, where objects do not move over time. This thesis addresses one of the most challenging Embodied AI tasks – visual room rearrangement, …