Digital Commons Network^™

On-Demand Scenario Generation For Testing Automated Driving Systems, Songyang Yan, Xiaodong Zhang, Kunkun Hao, Haojie Xin, Yonggang Luo, Jucheng Yang, Ming Fan, Chao Yang, Jun Sun, Zijiang Yang

Research Collection School Of Computing and Information Systems

The safety and reliability of Automated Driving Systems (ADS) are paramount, necessitating rigorous testing methodologies to uncover potential failures before deployment. Traditional testing approaches often prioritize either natural scenario sampling or safety-critical scenario generation, resulting in overly simplistic or unrealistic hazardous tests. In practice, the demand for natural scenarios (e.g., when evaluating the ADS's reliability in real-world conditions), critical scenarios (e.g., when evaluating safety in critical situations), or somewhere in between (e.g., when testing the ADS in regions with less civilized drivers) varies depending on the testing objectives. To address this issue, we propose the On-demand Scenario Generation (OSG) Framework, …

Ef21 With Bells & Whistles: Six Algorithmic Extensions Of Modern Error Feedback, Ilyas Fatkhullin, Igor Sokolov, Eduard Gorbunov, Zhize Li, Peter Richtarik

Research Collection School Of Computing and Information Systems

First proposed by Seide (2014) as a heuristic, error feedback (EF) is a very popular mechanism for enforcing convergence of distributed gradient-based optimization methods enhanced with communication compression strategies based on the application of contractive compression operators. However, existing theory of EF relies on very strong assumptions (e.g., bounded gradients), and provides pessimistic convergence rates (e.g., while the best known rate for EF in the smooth nonconvex regime, and when full gradients are compressed, is O(1/T2/3), the rate of gradient descent in the same regime is O(1/T)). Recently, Richtàrik et al. (2021) proposed a new error feedback mechanism, EF21, based …

Reimagining School Leadership: Latinx Administrators Leveraging Community Cultural Wealth To Support Latinx Student Success: A Qualitative Study In East San Jose Grounded In Counter-Storytelling, Critical Race Theory, And Latino Critical Theory, Alexis Corona Pimentel

Social Justice in Educational Leadership EdD Dissertations

This qualitative study examines how Latina administrators in East San Jose leverage their Community Cultural Wealth (Yosso, 2005) to support Latinx student success in K-12 education. Although Latinx students comprise the largest racial/ethnic group in California public schools (California Department of Education, 2021), Latinx leaders remain significantly underrepresented in educational leadership. Guided by Critical Race Theory (Delgado & Stefancic, 2017), Latino Critical Race Theory (LatCrit) (Solórzano & Bernal, 2001), and Yosso’s (2005) framework of Community Cultural Wealth, this study centers the counter-stories of three Latina administrators to explore how their cultural identities, lived experiences, and relational practices inform leadership.

Data …

Igniting Action To Reduce Gas Flaring: Real Opportunities. Real Projects. Real Results., Andrew Bernstein, Mark Davis, Thomas Mitro, Perrine Toledano

Columbia Center on Sustainable Investment

Gas flaring is a major global challenge. Despite bold commitments from governments, national oil companies (NOCs), international oil companies (IOCs), and leading independents, global flaring levels have stagnated at around 140–150 BCM per year, emitting up to 1 billion tonnes of CO2-equivalent greenhouse gases annually, while representing as much as $30 billion per year in potential lost revenue.

Numerous studies have outlined how flared gas can be captured and monetized – through power generation, fertilizers, petrochemicals, LNG and pipeline exports, among other use cases. Substantial reductions in flaring are not only technically achievable but can often create significant commercial value …

Addressing Missingness In Serialized Bureaucratic Data: The Case Of Chinese Courts, Xiaohan Wu, Margaret Roberts, Rachel E. Stern, Benjamin L. Liebman, Amarnath Gupta, Luke Sanford

Faculty Scholarship

Courts around the world are putting their data online, making information about caseloads, parties, and decisions available to the public. Yet, this data is far from complete, and often only reflects a portion of courts’ dockets. We offer and validate a set of tools for leveraging serialized bureaucratic data from courts to estimate the proportion of cases available to the public and the time courts take to make decisions. Using data from more than 3,000 courts in China, our methods allow us to assess patterns of missingness in court data across provinces and cities by type of case and to …

Brief Insights, June 2025: Learning And Leading Together: Highlights From A Multilingual And Mathematics Focused Research, Practice, Policy Partnership, Magaly Lavadenz Ph.D., Elvira G. Armas Ed.D., Linda R. G. Kaminski Ed.D., Kaivan Yuen Ed.D., Miguel Valencia, Teacher Researchers, Montebello Unified School District

Education and Policy Briefs

The Center for Equity for English Learners (CEEL) at Loyola Marymount University collaborated with Montebello Unified School District (MUSD) leaders and teachers in a Research, Practice, Policy Partnership (RPP) to investigate Spanish oral language production in TK to 2^nd grade students enrolled in three Dual Language Immersion Academies providing Cognitively Guided Instruction (CGI) in mathematics. Teacher researchers collected pre- and post-video samples of students explaining their CGI Counting Collections strategy. After establishing inter-rater reliability, MUSD teachers and the CEEL Research Team individually and independently analyzed characteristics of students’ academic Spanish oral language production using two focal California Spanish Language …

Advances In Using Primary Historical Sources To Teach Mathematics: A Special Issue Introduction And Invitation, Janet Heine Barnett, Dominic Klyve, Daniel E. Otero

The Mathematics Enthusiast

In this introductory article, the guest editors describe the genesis of this special issue of The Mathematics Enthusiast, provide an overview of its contents, and invite readers to join the authors of these articles and others in contributing to the ongoing efforts to bring primary historical sources to the mathematics classroom and research their impact on students and teachers.

Team Teaching With Primary Historical Sources, Tara Davis

The Mathematics Enthusiast

This article describes experiences involving team teaching using primary source projects. Both educational techniques are important on their own, and the novelty introduced is using them together. Both interdisciplinary and disciplinary courses were taught, so this article may be of interest to those teaching liberal arts, general education, or pure mathematics. Impacts on student learning and instructor professional development will be described, as well as challenges and benefits.

Student Disengagement In Years 7 To 9 In Victoria: A Review Of Recent Evidence, Fabienne Van Der Kleij, Suijing Yang, Romany Manuell

Student learning processes

The research reported here was conducted as part of the Reclaiming the Lost Years project, which aims to raise awareness of the need for structural reform in Years 7 to 9 schooling in Victoria, Australia. As an initial research paper within the project, this review adopted a rapid review methodology to review relevant literature and broader evidence about student disengagement in Years 7 to 9 in Victoria. Findings can inform the project’s advocacy for reform and key policy recommendations by defining and measuring student engagement and disengagement, and analysing evidence about rates of student disengagement in Victoria.

Impact Of Student Voice In The (Dis) Engagement Of Middle School Students In Urban Elementary School And Academic Achievement, Valandra N. Lloyd

Dissertations

This formative mixed-methods evaluation study explores the impact of culturally inclusive teaching practices on student voice, engagement, and academic outcomes among middle school students in an urban elementary school. Grounded in the theoretical frameworks of Culturally Relevant Pedagogy (Ladson-Billings), Culturally Responsive Teaching (Gay), and Culturally Sustaining Pedagogy (Paris & Alim), the study addresses persistent academic disparities experienced by students of color. Using classroom observations, student surveys, student focus groups, and teacher interviews, the research examines how teacher facilitation and inclusive classroom environments affect behavioral, emotional, and cognitive engagement. Findings will inform actionable strategies to amplify student voice and promote culturally …

Computerized Diagnostic Decision Support Systems-Isabel Pro Versus Chatgpt-4 Part Ii, Joe M Bridges, Xiaoqian Jiang, Michael Ige, Oluwatoniloba Toyobo

Faculty, Staff and Student Publications

Objective: Does a Tree-of-Thought prompt and reconsideration of Isabel Pro's differential improve ChatGPT-4's accuracy; does increasing expert panel size improve ChatGPT-4's accuracy; does ChatGPT-4 produce consistent outputs in sequential requests; what is the frequency of fabricated references?

Materials and methods: Isabel Pro, a computerized diagnostic decision support system, and ChatGPT-4, a large language model. Using 201 cases from the New England Journal of Medicine, each system produced a differential diagnosis ranked by likelihood. Statistics were Mean Reciprocal Rank, Recall at Rank, Average Rank, Number of Correct Diagnoses, and Rank Improvement. For reproducibility, the study compared the initial expert panel run …

Electroporation Protocol Development For Cal Poly Cell Therapy Laboratory Courses, Gabrielle Melamed

Biomedical Engineering

Cancer is a heterogeneous disease caused by unchecked cell proliferation. The disease contributed to 9.7 million deaths worldwide in 2022, with hematological malignancies (leukemias, lymphomas, and myelomas) accounting for over 1.4 million deaths in the United States from 1999 to 2020. This thesis focuses on the treatment of these cancers, with an emphasis on non-Hodgkin lymphomas (NHLs). R-CHOP (Rituximab-Cyclophosphamide, Doxorubicin hydrochloride, Oncovin/Vincristine, and Prednisone) is the standard of care first-line treatment for diffuse large B-cell lymphoma (DLBCL), the most common subtype of NHL, and encompasses a mixture of chemotherapy, immunotherapy, and corticosteroids. The R-CHOP regimen cures 50% to 70% patients, …

Framework For Multi-Agent Coordination And Distributed Localization In Micro-Uavs, Minwoo Park, Nikolas Tambornini

Electrical Engineering

Micro-UAVs (unmanned aerial vehicles) due to their inexpensive nature and compact form factor have shown an increase in prevalence throughout a multitude of applications including, but not limited to: search and rescue, military reconnaissance, and agriculture monitoring. However, for a majority of these high impact applications, a swarm of micro-UAVs are required and furthermore mandate that they are able to cooperatively and autonomously coordinate with each other. For long, controlling and communicating between a user and a singular micro-UAV has been a well known and solved problem, however the same can't be said for swarms of micro-UAVs. This project seeks …

An Analysis Of The Power Consumption Of Various Computer Vision Machine Learning Techniques On A Microcontroller Utilizing The Clusterduck Protocol, Kaveh Shafiei

Electrical Engineering

Constant data processing is essential for effective data collection, particularly in remote and hard-to-reach areas. The need for efficient, autonomous data acquisition and transmission is increasingly addressed by integrating machine learning within larger communication networks. This paper explores the application of machine learning techniques with Internet of Things (IoT) mesh networks. Utilizing the LoRa communication protocol, data is captured and analyzed on an edge device and transmitted to a larger communication network. The ClusterDuck Protocol (CDP), developed by OWL Integrations, serves as an IoT mesh network designed to allow for communication in areas lacking traditional static infrastructure such as WiFi …

Leader-Follower Platooning With Turtlebot3: A Low-Cost Ros Test-Bed Using Vision-Lidar Fusion, Patrick Kelly Crandall, Kalon Ma Bienz

Electrical Engineering

This report presents the design, implementation, and indoor validation of a two-robot leader–follower platoon built on low-cost Turtlebot3 platforms. Each robot runs ROS Noetic on an on-board Raspberry Pi 4, fusing a fisheye camera for HSV-based lane detection with an LDS-02 LiDAR for clustering-based leader identification. A dual-loop architecture (PD steering for lateral control and PID for longitudinal gap regulation) maintains a 0.40m headway and keeps the follower centered within +/- 5 cm of the lane midline, without any inter-vehicle communication or external localization. Track experiments at speeds up to 0.18m/s achieved mean gap error of +/- 3 cm and …

Advanced Light Dimming Power Converter, Jaden Nguyen, Edwin Lin, Alan Thai

Electrical Engineering

This senior project discusses and follows the development of the Advanced Light Dimming Power Converter meant to modernize the power electronics curriculum and improve student safety for a lab. The power converter attempts to replace the original experiment which includes a traditional TRIAC-based dimmer and focuses on demonstrating phase angle control for incandescent light bulbs. However, several drawbacks including high-voltage exposure and outdated technology warranted a revamp. The redesigned module includes a dual-experiment setup with an updated TRIAC-based dimmer circuit and a new AC-DC LED driver circuit with constant current control and PWM dimming capability. Both systems have been fabricated …

Antiviral Prescription In Children With Influenza In Us Emergency Departments: New Vaccine Surveillance Network (Nvsn), 2016-2020., Tess Stopczynski, Justin Z. Amarin, James W. Antoon, Olla Hamdan, Laura S. Stewart, James Chappell, Andrew J. Spieker, Eileen J. Klein, Janet A. Englund, Geoffrey A. Weinberg, Peter G. Szilagyi, John V. Williams, Marian G. Michaels, Julie A. Boom, Leila C. Sahni, Mary Allen Staat, Elizabeth P. Schlaudecker, Jennifer E. Schuster, Rangaraj Selvarangan, Christopher J. Harrison, Heidi L. Moline, Ariana P. Toepfer, Angela P. Campbell, Samantha M. Olson, Natasha B. Halasa

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Influenza contributes to a high burden of pediatric emergency department (ED) visits annually. Guidelines recommend outpatient antiviral treatment for children at higher risk of severe influenza and recommend considering treatment for those who present within 2 days of symptom onset. We describe antiviral prescription in children with influenza presenting to the ED.

METHODS: We analyzed data from the New Vaccine Surveillance Network (2016-2020), including children presenting to the ED and enrolled with confirmed influenza at one of seven pediatric academic centers. We compared characteristics of children prescribed antivirals to those who were not, using generalized estimating equations models to …

Integrating Pedagogy And Mathematics Content In Content-Focused Professional Development, Liza Bondurant, Joey Rutherford, Shannon Sharp

Publications

In this Perspective on Practice, we describe how we interpreted, built on, and adapted the design principles shared in “The Content- Focused Methods Course: A Model for Integrating Pedagogy and Mathematics Content” by Steele and Hillen (2012). Using evidence of learning from that report as a foundation, we provide insights into how integrating pedagogy and mathematics content in content-focused professional development (CFPD) influenced our evidence of learning.

Predicting Consumers’ Purchase Intention Of Browsed Products: A Study Based On Eye‑Tracking, Feiyan Jia, Choon Ling Sia, Yani Shi, Fiona Fui-Hoon Nah, Keng Siau

Research Collection School Of Computing and Information Systems

Predicting consumers’ purchase intention of browsed products enables sellers to implement nuanced promotion strategies to stimulate purchase. But how can we predict consumers’ purchase intention of browsed products? Our research demonstrates that consumers’ eye movement data collected when they browse products can serve this aim. We train and test the prediction model using logistic regression and random forest algorithms. Using data collected in a laboratory experiment, our empirical results show that both algorithms perform much better than a random guess, and the logistic regression performs slightly better than the random forest. Our findings imply that eye movement data enable sellers …

Verify All Traffic: Towards Zero-Trust In-Network Intrusion Detection Against Multipath Routing, Ziming Zhao, Zhaoxuan Li, Xiaofei Xie, Zhipeng Liu, Tingting Li, Jiongchi Yu, Fan Zhang, Binbin Chen

Research Collection School Of Computing and Information Systems

With the popularity of encryption protocols, machine learning (ML)-based traffic analysis technologies have attracted widespread attention. To adapt to modern high-speed bandwidth, recent research is dedicated to advancing zero-trust intrusion detection by offloading feature extraction and model inference into the network dataplane. Especially, with the rise of programmable switches, achieving line-speed ML inference becomes promising. However, existing research only considers a single switch node as a relay to conduct evaluation. This is far from real-world deployments involving multiple switches (given that zero-trust security assumes that threats can originate from anywhere, including within the network), particularly the multipath routing phenomenon that …

Arkansas Corn And Grain Sorghum Research Studies 2024, Jason Kelley, Travis Faske

Arkansas Agricultural Experiment Station Research Series

The 2024 edition of the Arkansas Corn and Grain Sorghum Research Studies Series includes research results on topics pertaining to corn and grain sorghum production, including weed, disease, nematode, and insect management; economics; irrigation; agronomics; soil fertility; drone use; and research verification program results.

Our objective is to capture and broadly distribute the results of research projects funded by the Arkansas Corn and Grain Sorghum Board. The intended audience includes producers and their advisors, current investigators, and future researchers. The Series serves as a citable archive of research results.

The reports inform and guide our long-term recommendations, but should not …

Understanding Teacher Attrition In Nebraska: A Quantitative Approach Using Markov Chains And Graph Theory, Md Tahidul Islam

Mathematics Theses, Dissertations, Research and Student Creative Activity

Teacher attrition is a growing concern in Nebraska, particularly in rural and high-need districts where staffing challenges are most acute. This study applies a hybrid approach combining Markov Chain modeling and Graph Theory to analyze over three decades of longitudinal employment data from the Nebraska Department of Education. A discrete-time Markov model is used to estimate transition probabilities between roles such as Teacher, Administrator, and Exit, revealing high attrition risks among early-career educators and paraprofessionals. To complement this, a directed weighted graph is constructed to examine the structural properties of role transitions using centrality, clustering, and entropy metrics. Results show …

The Reign Of Cerberus: International Law And Technological Innovation, Paul B. Stephan

Chicago Journal of International Law

This Essay sketches an informal theory of the impact of technological change on international economics, and hence international relations expressed as international law. The theory points to a policy trilemma, something that I call Cerberus in a perhaps futile attempt at an arresting metaphor. The Essay uses the trilemma to illuminate the general trends in technology policy we see playing out in China, Europe, and the United States. It argues that we have the privilege of witnessing an ongoing natural experiment in optimal technology regulation and legal policy, with no guarantee as to which approach will prevail.

Of course, like …

Facial Recognition Ai, Margaret Hu

North Carolina Law Review

No abstract provided.

Graduate School Blog - June 2025, Cynthia Haynes

UofM Grad School Blog

The June 2025 edition of the UofM Graduate School Blog helps prospective and current students make informed financial decisions with Part 1 of the Graduate School Cost Guide, breaking down tuition structures such as per-credit hour versus flat-rate models, highlighting UofM’s tuition cap for in-state students, and explaining key university fees and cost differences between online and on-campus formats. The blog also features Brianna Reilly, a Doctor of Musical Arts graduate from New York, who shares how a graduate assistantship and her passion for music education led her to continue at UofM through the pandemic. Additional resources include an …

Does Third Party Litigation Funding Need Regulations On Consumer Protection, Ronen Avraham, Eric Schuller, Tony Sebok

Utah Law Review

Transcript of a roundtable discussion during the Third-Party Litigation Symposium at the S.J. Quinney College of Law

Revised Draft Final Bpsou Unreclaimed Sites: Ur-05 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Inferring The Timing Of Antiretroviral Therapy By Zero-Inflated Random Change Point Models Using Longitudinal Data Subject To Left-Censoring, Hongbin Zhang, Mckaylee Robertson, Sarah L. Braunstein, David B. Hanna, Uriel R. Felsen, Levi Waldron, Denis Nash

Biostatistics Faculty Publications

We propose a new random change point model that utilizes routinely recorded individual-level HIV viral load data to estimate the timing of antiretroviral therapy (ART) initiation in people living with HIV. The change point distribution is assumed to follow a zero-inflated exponential distribution for the longitudinal data, which is also subject to left-censoring, and the underlying data-generating mechanism is a nonlinear mixed-effects model. We extend the Stochastic EM (StEM) algorithm by combining a Gibbs sampler with a Metropolis–Hastings sampling. We apply the method to real HIV data to infer the timing of ART initiation since diagnosis. Additionally, we conduct simulation …

A Realizability Approach To Constructing Higher Types Via Classifiers, Benjamin Carrick Logsdon

Dartmouth College Ph.D Dissertations

We construct an interpretation of higher types into Peano arithmetic, showing in particular that every model of PA is a model of higher types. This is a reversal of Gödel’s Dialectica construction. We also define the classifier degrees, a degree structure which subsumes the Turing degrees, the enumeration degrees, and the many-one degrees. The classifier degrees boast a rich structure and many well-behaved operations.

Drone Package Delivery System, Aiden Tyler Sim, Ryan Anders O'Toole, Matthew Karl Wyant, James Shaw Glanville

Mechanical Engineering

In response to the demands of the 2025 C-UASC (California Unmanned Aerial Systems Competition), our team developed an autonomous drone payload delivery system capable of two distinct delivery modes: a precision-controlled descent and a high-speed aerial drop. Designed for modular integration with UAV platforms, the system prioritizes reliability, accuracy, and simplicity under desert environmental conditions. Our solution features a custom winch mechanism with a programmable stepper motor, a passive mechanical hook for tension-based release, and a servo-actuated trapdoor for high-altitude drops. The design was extensively tested for structural integrity, motor torque requirements, drop precision, and electronics reliability—culminating in a robust …