Digital Commons Network^™

The Long And Short Of It: Exploring The Essential Dynamics Of Select Geophysical Flows, Adhithiya Sivakumar

Doctoral Dissertations

Geophysical flows are central to important climatological processes, yet their strong turbulence and additional complexities -- density stratification, wave-current interaction, and phase change -- make analytical prediction and direct numerical simulation infeasible in many regimes. This dissertation adopts a reductionist approach in which simplified representations -- often inspired by observed scale disparities -- are utilized to isolate and investigate the organizing mechanisms of these complex flows. Within this framework, three distinct but thematically connected problems are studied.

We first study Langmuir turbulence in the open ocean, in which surface gravity waves interact with wind-driven currents to organize the mixed layer …

Threshold Asymmetric Conditional Autoregressive Range (Tacarr) Model, Isuru Ratnayake, V. A. Samaranayake

Mathematics and Statistics Faculty Research & Creative Works

This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed to vary across regimes. A self-adjusting threshold component, determined by past values of the series, is used to identify the prevailing market regime. In this way, the model is able to capture asymmetric and heteroscedastic volatility behavior in financial markets. The TACARR model is designed to address several limitations of existing price range models, including …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain

Journal of Marine Science and Technology–Taiwan

In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Using Remote Sensing Technology To Develop A Framework For Improving Hydrologic Models, Marissa Cook

Theses, Dissertations and Capstones

With increased storm intensity due to climate change and urbanization, flash flooding has become an increasingly significant issue globally and regionally. Although the factors influencing urban flash flooding are well-known, there is a growing need for technology to accurately and remotely predict the chance of a flash flood occurring from any given rain event to give people time to prepare. This study aims to use multispectral satellite imagery to provide a framework for improving near real-time flood predictions in an urban area of a high gradient, fourth order stream impacted by flooding. Specifically, we utilize satellite imagery to create the …

A Variance Decomposition Approach To Inconclusives In Forensic Black Box Studies, Amanda Luby, Joseph B. Kadane

Mathematics and Statistics Faculty Work

In the USA, ‘black box’ studies are increasingly being used to estimate the error rate of forensic disciplines. A sample of forensic examiner participants is asked to evaluate a set of items whose source is known to the researchers but not to the participants. Participants are asked to make a source determination (typically an identification, exclusion, or some kind of inconclusive). We study inconclusives in two black box studies, one on fingerprints and one on bullets. Rather than treating all inconclusive responses as functionally correct (as is the practice in reported error rates in the two studies we address), irrelevant …

Different Destinations: Clarifying And Addressing Pipeline Problems For Women In Academic Archaeology, Scott R. Hutson, Jaycee Castro, Bruno Athie Teruel

Anthropology Faculty Publications

In STEM fields, women tend to leak out of the pipeline to the professoriate. In archaeology, however, robust databases and chronological control reveal that there is no leakage from earning a PhD to tenure-track positions. Nor is there a leak from assistant professor to associate professor. Nevertheless, men get hired as faculty in PhD programs more often than women. This is important because PhD programs are research-intensive and train future leaders. Furthermore, women PhD students have women as advisers more than often men and report advantages to this arrangement. Yet with fewer women faculty in PhD programs, women mentors are …

Chirp Imaging In Extant Lakes And Reservoirs, Kevin L. Woller, Edward W. Woolery, Eva C. Lyon, Michael M. Mcglue

Earth and Environmental Sciences Faculty Publications

Compressed high-intensity radiated pulse (CHIRP) acoustic reflection data acquired in lakes and other shallow water bodies can provide detailed imaging that is valuable for environmental and engineering geology applications well below the sub-bottom floors. However, it is often unclear to non-specialists which acquisition settings should be considered to achieve optimal imaging quality when beginning a new survey, particularly in an unfamiliar environment. We review fundamental concepts for optimizing signal design using coincident CHIRP lines from two extant glacial lakes in the eastern Sierra Nevada of California: Convict Lake and June Lake. As part of the optimization process, seismic data were …

Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik

Mechanical and Aerospace Engineering Theses

Autonomous unmanned aerial vehicles (UAVs) operating in contested environments must

complete mission objectives while avoiding restricted regions, radar exposure, and pos-

sible interception. This thesis develops a MATLAB-based simulation framework for

two-dimensional UAV mission planning under threat using model predictive control and

proportional-navigation chasers. The mission requires the UAV to travel from a start

location to a goal while visiting required checkpoints and avoiding no-fly zones and radar

regions. A chaser attempts to intercept the UAV using either a basic pure-pursuit-style

law or a proportional-navigation guidance law.

The framework integrates environment generation, augmented visibility-graph rout-

ing, waypoint management, UAV kinematic …

Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar

Mechanical and Aerospace Engineering Theses

This thesis presents a closed-loop control architecture for uncrewed aerial vehicles (UAVs) in which a large language model (LLM) serves as a high-level decision module operating over a persistent, metric 3D world model.

Rather than generating low-level commands or open-loop plans, the LLM selects one parameterized maneuver per decision step from a small, verified library of flight primitives conditioned on a structured representation of the drone state, tracked object positions, and mission specification.

Translational motion is executed by a planar model predictive controller (MPC) with soft obstacle avoidance, using obstacle hypotheses provided by the LLM, so that safety-critical constraint handling …

A Neo-Kuyperian Approach To Mathematics, Calvin Jongsma, Kevin Vander Meulen

Faculty Work Comprehensive List

This chapter develops a Reformational perspective on the discipline of mathematics that stems from the seminal ideas of Kuyper, Dooyeweerd, Wolters, Clouser, and others. The implications of the Biblical motif of Creation-Fall-Redemption is explored for the task of Christian scholarship in general and for the field of mathematics in particular, drawing upon relevant developments in the history and philosophy of mathematics.

Calculus In Context: The Five College Calculus Project, James Callahan, Kenneth Hoffman, David Cox, Donal O'Shea, Harriet Pollatsek, Lester Senechal

Open Educational Resources: Textbooks

Calculus in Context: The Five College Calculus Project is a thorough reframing of what it means to learn calculus. It starts with a “clean slate;” there is no presumptive commitment to any aspect of the traditional course. Instead, the curriculum is guided by the following principles:

• Calculus is fundamentally a way of dealing with functional relationships that occur in scientific and mathematical contexts. The techniques of calculus must be subordinate to an overall view of the underlying questions.
• Technology radically enlarges the range of questions we can explore and the ways we can answer them. Computers can be engaged as …

Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi

Mansoura Engineering Journal

This study examines the influence of Hall current and nth-order chemical reaction on unsteady three-dimensional magnetohydrodynamic (MHD) Williamson nanofluid flow over an inclined stretching sheet. The model incorporates thermal radiation, heat source, Brownian motion, and thermophoresis effects. The governing nonlinear partial differential equations are transformed into a system of ordinary differential equations using similarity transformations and solved numerically using the shooting method with a fourth-order Runge–Kutta scheme. The results indicate that an increase in the magnetic parameter significantly reduces velocity profiles while enhancing temperature and concentration distributions. The Hall parameter reduces surface drag and improves heat transfer, while decreasing mass …

Evaluating Matching Frontier Methods For Crash Modification Factor Estimation, Usama Elrawy Shahdah, Eman K . Ali, Sania Reyad Elagamy

Mansoura Engineering Journal

This study evaluates "matching frontier" methods against conventional approaches for estimating Crash Modification Factors (CMFs). Thirty-four method-model combinations were tested, including 16 frontier variants, 8 propensity-score-matching algorithms with negative binomial and mixed-effects models, and two benchmarks (empirical Bayes and cross-sectional), across multiple sample sizes and three true CMF values (0.80, 1.00, and 1.30). Of these, 30 converged successfully; 4 mixed-effects models with replacement-based matching failed due to duplicate control observations. Each scenario was evaluated across 10 Monte Carlo replications to quantify performance uncertainty.

Synthetic crash data were generated with known treatment effects, examining scenarios ranging from ideal (386 treated, 21,000 …

Remote Sensing-Based Rice Detection: Novel Indices From Optical And Sar Synergy, Kaifi Chomani

Mansoura Engineering Journal

Accurate rice mapping is challenging due to the lack of a simple, efficient approach and the complexity and limited ability of existing methods to distinguish rice fields from non-rice fields. This study proposes two novel indices: the Multispectral Rice Detection Index (MRDI), which utilises optical imagery, and the OptiRadar Rice Index (ORRI), which incorporates both optical and Synthetic Aperture Radar (SAR) data. Ground-truth data from the Cropland Cropping Systems (CROS) were used to assess the performance of both indices. The findings indicated that MRDI achieved an overall accuracy of 97.97% with perfect recall (100%) but lower precision (78.65%). However, the …

An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare

Mansoura Engineering Journal

The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …

Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy

Mansoura Engineering Journal

Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …

Frequency Ranking Of Imaging Biomarkers For Lung Cancer Risk Stratification Using A Hybrid Elastic Net Method, Mohamed Jaber, Emmy Stevens, Nezamoddin N. Kachouie

Mathematics and System Engineering Faculty Publications

Lung cancer remains the leading cause of cancer-related mortality worldwide, emphasizing the critical need for novel and robust biomarkers to improve prognostication and guide precision oncology. While traditional clinical variables such as tumor stage, age, and sex are routinely used for survival prediction, their prognostic performance is limited. Imaging biomarkers derived from radiomic analysis of advanced medical imaging have emerged as a promising class of noninvasive cancer biomarkers, enabling quantitative characterization of tumor phenotypes. In this study, we investigated the prognostic utility of radiomic imaging biomarkers, with a particular focus on the texture-based feature Busyness, and compared their performance against …

Enoch’S Measuring, Counting, Weighing, And Balancing Creation In 2 Enoch, Andrei Orlov

Theology Faculty Research and Publications

In recent years one can see increased scholarly attention to the epistemological dimension of early Jewish apocalyptic writings and, in particular, to the ways by which divine knowledge was harvested and cultivated by the protagonists and antagonists of those early Jewish accounts. The early Enochic booklets have traditionally played a central role in these epistemological probes since they contain the earliest descriptions of the transmission and acquisition of divine knowledge in Jewish apocalypticism.  These accounts deal both with revelations unveiled by God and angels to the patriarch Enoch and with illicit transmission of divine knowledge by the rogue group of …

A Hierarchical And Multidimensional Approach To Profiling Students’ Digital Skills In Educational Technology, Emil S. Frashëri, Eleni F. Vangjeli

Journal of Educational Technology Development and Exchange (JETDE)

This study investigates university students’ digital competence through a multidimensional and person‑centered analytical framework grounded in bifactor–Exploratory Structural Equation Modeling (B‑ESEM). Digital competence was conceptualized across four functional skill domains and a general competence factor, reflecting contemporary perspectives on technology‑enhanced learning and student readiness. To overcome a common limitation in traditional Latent Profile Analysis (LPA), the conflation of overall competence levels with relative skill configurations, this study employed B‑ESEM–derived factor scores to preserve both hierarchical structure and multidimensionality. Using data from 599 university students, a four‑profile solution emerged, capturing distinct patterns of digital skill strengths and weaknesses. Gender and programming …

Exploring Teachers’ Perceptions Towards Using Ict With Dialogic Teaching In The Primary Science Classroom In Saudi Arabia, Yousef Alharbi, Sue Johnston-Wilder

Journal of Educational Technology Development and Exchange (JETDE)

This study examines the implications of teachers’ perceptions of using ICT to support dialogic teaching in primary science classrooms in Saudi Arabia. It employed questionnaires distributed electronically to science teachers working in state primary schools in Riyadh, and 305 completed responses were analyzed using SPSS. The majority were found to implement a variety of activities to support dialogue and to use several ICT tools in their science lessons. In addition, most teachers reported positive attitudes toward ICT, dialogic teaching, and ICT-supported dialogic teaching in science lessons. However, the results indicated that some teachers currently adopt a dominant role in dialogue …

Application Of Artificial Intelligence In Case-Based Teaching: A Qualitative Study In Mba Education, Tianjiao Xu, Mohd Nazir Bin Zabit

Journal of Educational Technology Development and Exchange (JETDE)

This study examines the incorporation of artificial intelligence (AI) into case-based teaching (CBT) within Master of Business Administration (MBA) programs in China, amidst the rapid digital transition in higher education. Guided by the Context–Input–Process–Product (CIPP) evaluation framework, the study adopted a qualitative design and conducted semi-structured interviews with five instructors from three core MBA courses. The findings indicate that AI enhanced classroom interaction and reduced teachers’ workload by supporting real-time feedback and dynamic discussion processes. Institutional support, including teacher training, digital infrastructure, and technical assistance, was recognized as a vital facilitator of effective implementation. Despite its various benefits, the study …

Analysis Of Policies And Incentives For The Successful Implementation Of Hydrogen-Fueled Medium-Duty And Heavy-Duty Vehicles In Humboldt County, California, Alka Verma

Cal Poly Humboldt theses and projects

The 21st century has seen a significant rise in global greenhouse gas (GHG) emissions, with the transportation sector contributing 23% of these emissions. Medium-duty and heavy-duty vehicles (MD/HD) are particularly impactful, accounting for over a quarter of transport-related emissions. In Humboldt County, California, transportation represents 53% of total emissions, with MD/HD vehicles being a major contributor. As light-duty vehicles shift to zero-emission alternatives, the MD/HD sector faces unique challenges. Hydrogen fuel cell vehicles offer a promising solution, providing longer range, higher energy density, and quicker refueling compared to battery electric vehicles (BEVs). These features make hydrogen an attractive option for …

Economic Inequality In California Counties: Same Patterns, Mixed Impacts After Covid-19, Justin Arellano

IdeaFest 2026

This project analyzes economic inequality across California counties before and after COVID-19 using Census data. Findings show that higher-income counties consistently have lower poverty and uninsured rates. Although COVID-19 caused changes in economic outcomes, the overall pattern of inequality remained stable, suggesting that income differences continue to be the primary factor shaping county-level economic conditions.

2026 Mcm Problem A: Modeling Smartphone Battery Drain, Jonathan David Juarez

IdeaFest 2026

This study develops a continuous-time model of smartphone battery discharge incorporating activity-dependent current demand and temperature-driven degradation. Simulations evaluate battery performance under common usage scenarios and varying states of health. Results indicate that high-energy activities significantly accelerate depletion, while battery aging and elevated temperatures reduce overall runtime. Model predictions align with benchmark data and observed usage patterns, demonstrating the framework’s ability to replicate realistic discharge behavior. The model provides a practical approach for estimating battery life and assessing the impact of user behavior and thermal conditions.

Modeling Murders: Following The Yorkshire Ripper, Alexis Garcia

IdeaFest 2026

When working to identify active serial killers, police collect data on the killer’s behavioral patterns to predict their activity. Peter Sutcliffe, also known as the Yorkshire Ripper, started killing in the 1900s and primarily targeted women from red-light districts. This project uses an agent-based modeling approach that incorporates the behavioral choices of Sutcliffe to predict the home location of a killer with similar traits. The accuracy of our model was measured by calculating the distance between the predicted and the true house location of the killer. This model shows the effectiveness of using an agent-based model to simulate a serial …

A Strawberry’S Meaning, Ava Bauch, Michaela Barthel, Cacee Danielson, Brooke Kraft

OER Materials

This lesson plan provides a culturally responsive and interdisciplinary learning experience for second-grade students by integrating social studies, literacy, and character education through the topic of strawberries in Cherokee culture. Using the 5E instructional model students learn that items in nature can hold important meaning for different cultures. The lesson aligns with standards focused on identifying how people are influenced by their environment and how natural resources can shape traditions and beliefs. Students begin by discussing their own experiences with strawberries and sharing what strawberries mean to them. This opening activity activates prior knowledge and helps students understand that objects …

Strawberry Exploration: Using Our Senses, Ava Bauch, Michaela Barthel, Cacee Danielson, Brooke Kraft

OER Materials

This lesson plan provides an engaging inquiry-based science experience for second-grade students by using strawberries as a hands-on tool for exploring the five senses and developing observation skills. The lesson aligns with science standards focused on planning and conducting investigations based on observable properties. Students learn how scientists use their senses to gather information while also building communication and collaboration skills. The central focus is for students to investigate strawberries through sight, touch, smell, and taste, then record and compare their findings with classmates. The lesson begins with an introduction to the five senses through visuals and guided discussion. Students …

Case Study Of The Loch Ness Monster, Ava Bauch, Cami Mayo, Sean Savage

OER Materials

This lesson plan presents an engaging interdisciplinary learning experience for fourth-grade students that integrates social studies and language arts through the mystery of the Loch Ness Monster. Using the 5E instructional model, students investigate the legend while developing literacy and geographic reasoning skills. The lesson aligns with standards requiring students to make inferences using text evidence and use geographic tools to gather and report information. Students begin by examining a map of Scotland through See-Think-Wonder and Think-Pair-Share strategies, using observation and discussion to identify locations and making predictions about where the Loch Ness Monster story takes place. This opening activity …