Digital Commons Network^™

Hardware Cluster For Key Security And Education Experiments, Michelle Mcaveety, Rylan Pietras, Ahmed Ghoneim, Robert Karam

Bellini College REU Symposium (BCREUS)

In response to increased cyberattacks against digital infrastructures, significant contributions have been made to the education of software-based cybersecurity principles through online resources, coursework, and other means. However, there is a lack of accessible platforms dedicated to the learning of hardware-based cybersecurity principles. Specifically, topics such as side-channel attacks or fault injection attacks can be challenging to study without expensive hardware resources. To address this need, we propose the Hardware Cluster for Key Security and Education Experiments (HaCKSEE) platform. HaCKSEE is an experiment-oriented platform designed to democratize hardware security education. The proposed platform allows students to conduct configurable hardware security …

Neurons Of Bias: Power-Mediated Compliance And Mitigation In Large Language Models, Anubhav Gupta, Otavio Rosa, Mahammed Kamruzzaman, Gene Kim

Bellini College REU Symposium (BCREUS)

Introduction & Problem Statement

Large language models (LLMs) are increasingly deployed in sociotechnical systems involving power, authority, and compliance, raising important questions about fairness, consistency, and reliability across diverse user populations. As these systems are integrated into hiring tools, customer service systems, assistive technologies, and decision-support pipelines, they are expected to operate consistently regardless of the identity they are prompted to adopt. However, when demographic attributes are introduced into prompts, model behavior may shift even when identity does not change the underlying task.

In power-mediated settings, such variation is especially important because differences in compliance, refusal, or loophole-seeking behavior may …

Misty: An Llm-Driven Recipe Recommender Robot, Alina Pineda, Stuti Goyal, Jingjing Li, Zhao Han

Bellini College REU Symposium (BCREUS)

Introduction & Problem Statement

Meal planning requires balancing nutritional needs, available ingredients, and user preferences, which can be time-consuming and cognitively demanding. While mobile recipe applications provide personalized recommendations, they lack interactive and socially engaging communication. In contrast, social robots such as Misty enable expressive interaction through speech, gestures, and emotional cues, but typically rely on rigid, pre-programmed behaviors and lack domain-specific knowledge for tasks such as recipe recommendation.

This gap highlights the need for a system that combines the strengths of both technologies. Recipe recommendation is inherently multimodal, requiring both social interaction for engagement and visual presentation for detailed …

Strider: Human Re-Identification Using Gait Recognition, Mark Calvelo, John Pham, Aleksandre Papunashvili, Mauricio Pamplona Segundo

Bellini College REU Symposium (BCREUS)

Gait Recognition pipelines have shown promise in recent years with modern models such as SkeletonGait [1] and GPGait [2] demonstrating decent performance on known benchmarks. These Gait Recognition models utilize resource and computationally expensive pipelines for full end-to-end Gait Recognition. This overhead can prove to be a problem for real-time tasks such as on-device recognition. In this project, we aim to reduce one of the most important phases of the Gait Recognition pipeline which is Skeleton and Silhouette generation. We build off of the YOLOv11 architecture [3] simplifying aspects of the existing model to create a model that can efficiently …

Last-Mile Autonomous Delivery Robot, Lucas Araujo Bianco, Clement Joseph, Chance Hamilton, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

Autonomous delivery robots require robust, real-time navigation systems to safely traverse dynamic outdoor environments like college campuses. This project presents an edge-optimized vision pipeline deployed on a resource-constrained Jetson Nano-based robot to accurately identify drivable surfaces and detect path intersections. We employ a lightweight semantic segmentation Convolutional Neural Network (LRASPP MobileNetV3-Large), initially pretrained on the Cityscapes dataset. By applying transfer learning to a manually refined, locally labeled dataset of our campus, we significantly improved feature extraction for urban textures and adapted the model to our specific use case. To ensure efficient edge deployment, the network is optimized using TensorRT [1], …

Microarchitectural Vulnerabilities And Performance Tradeoffs In Shared Scientific Computing, Zyad Abd-Elrahman, Santosh Pandey

Bellini College REU Symposium (BCREUS)

Introduction & Problem Statement

Shared scientific computing platforms are built for speed and utilization, but they create a security problem that isolation alone can't fully solve. Even with TEEs, containers, or a privilege separation in place, the hardware underneath remains a shared resource. Speculative execution, cache contention, interconnect timing, and similar microarchitectural effects can leak information or create integrity risks across protection boundaries without any malicious code involved. For CI operators running graph workloads, HPC kernels, or ML pipelines in co-tenanted systems, the threat is inherent in normal execution. The real question isn't whether these vulnerabilities exist, but it's what …

Optimizing Machine Learning Workloads Performance In Ml Accelerators, Chowdhury Nafiun Nuru, Santosh Panday

Bellini College REU Symposium (BCREUS)

This project explores how to improve the performance of machine learning systems at the kernel level. As models grow in size, efficient execution depends on reducing data movement and using limited on-chip memory effectively.

Techniques such as tiling and optimized execution order are used to improve data locality and reduce memory overhead. These approaches enable better use of fast on-chip memory and minimize costly data transfers.

Using benchmark workloads, improved scheduling strategies are shown to reduce latency by avoiding suboptimal local decisions and enabling better global execution patterns.

Overall, this work demonstrates that kernel-level optimization can significantly improve performance and …

Autonomous Indoor Mapping And Navigation Using Ros2-Based Slam On A Jetson-Powered Mobile Robot, Daniel Schagen, Mark Halim, Chance Hamilton, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

This project presents the design, implementation, and evaluation of an autonomous indoor mobile robot capable of simultaneous localization and mapping (SLAM) using a ROS 2-based architecture on resource-constrained embedded hardware. The system is built on a Yahboom ROSMASTER X3 platform equipped with a Slamtec RPLidar A1, IMU, and wheel odometry, running ROS 2 Foxy on an NVIDIA Jetson Nano 4GB inside a Docker container. The primary objective is to enable the robot to autonomously map an indoor hallway environment while navigating without human intervention.

The mapping pipeline integrates slam_toolbox for occupancy grid generation, with loop closure enabled and parameters tuned …

Domain Randomization For Robot Navigation, John Hightower, Danae Ferguson, Brendon Johnson, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

Reinforcement learning enables robots to learn navigation policies in simulation, but performance often degrades during real-world deployment due to the sim-to-real gap. This work investigates domain randomization as a strategy to improve transfer for a Soft Actor-Critic navigation policy trained in a maze environment. Six targeted randomization methods are implemented including obstacle layouts, LiDAR noise, motion distance, positional noise, action perturbations, and maze switching to analyze how different sources of variability affect the robot’s ability to effectively navigate a maze. Results demonstrate the extent to which the robot can effectively generalize a policy for navigation given each domain randomization method, …

An Evaluation Of Biologically-Inspired Slam Models Against Traditional Models, Colby Mullins, Asadbek Nematov, Ross Volenec, Chance Hamilton, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

This research presents a comparative analysis of biologically-inspired SLAM models (RatSLAM [2], SeqSLAM [3]) versus traditional feature-based geometric SLAM (ORB-SLAM3 [1]) to establish a standardized framework for evaluating accuracy, robustness, and computational efficiency under varying environmental conditions. To ensure an equitable baseline, models are subjected to a unified testing pipeline across real-world datasets (Oxford RobotCar clear and overcast sequences) and controlled Webots simulations (day/night and seasonal centerlines) using timestamp-aligned 480p monocular PNG images. Within this pipeline, pose estimations are standardized to the TUM trajectory format, and spatial alignment and scale correction are applied via the evo evaluation library [4] to …

Investigating The Effect Of Input Modality On Reasoning In Vlms Using Zero-Shot Evaluation, Rodela Ghosh, Aviral Gupta, Ocean Monjur, Shrestha Datta, Anshuman Chhabra

Bellini College REU Symposium (BCREUS)

This project investigates how input modality affects mathematical reasoning in vision-language models (VLMs). Using 100 samples from the GSM8K benchmark, we evaluate Qwen2-VL-2B-Instruct and LLaVA-v1.6-Mistral-7B across three conditions: text-only, rendered image, and a modality mismatch condition where image and text describe different problems. Both models show substantial accuracy drops under visual input — Qwen2 falls from 55% to 30% and LLaVA from 40% to 21%. In the mismatch condition, both models follow the text modality in over 75% of cases, revealing strong text dominance when modalities conflict. These findings suggest that rendering math problems as images meaningfully impairs reasoning in …

Risa: Robotic Interface For Sit-To-Stand Assistance, Hieu Tran, Rinat Mynnakhmetov, Ricardo Frumento Sr, Yu Sun

Bellini College REU Symposium (BCREUS)

Mobility limitations in older adults are expected to become increasingly prevalent, along with the larger proportion of the world’s elderly population over the next decades [1]. Among these problems is the difficulty many elderly individuals face when transitioning from a seated to a standing pose. Loss of lower-body strength and balance makes this daily activity near impossible without assistance. To address this motor impairment, solutions were developed. For example, the Elderly Bodily Assistance Robot (E-BAR) provides body-weight support using handles, pulleys, and frames [2]. While these systems demonstrate the feasibility of robotic assistance, they present key limitations. Firstly, mechanical designs …

Modality-Specific Confidence And Uncertainty Metrics For Vision-Language Models, Sahasra Kondapalli, Poyraz An, Trung Dong, Lara Radovanovic, Xiaomin Lin

Bellini College REU Symposium (BCREUS)

Introduction and Problem Statement

Vision-Language Models (VLMs) are increasingly being integrated into high-stakes environments, such as autonomous robotics used in shared workspaces and as multimodal medical assistant systems. However, current models still have inherent uncertainties, often producing errors or false confidence in responses [1]. Such errors, when passed undetected, can cause serious issues in medical implementations. In shared workspaces, false confidence can lead to safety hazards, or disruption. Du et al. present an evaluation of uncertainty, specifically in the field of human-robot interaction [2]. Such faults are only magnified with the addition of the vision modality, thus highlighting the need …

Beyond Folded Proteins: Assessing The Limits Of Ai Structure Prediction For Intrinsically Disordered Complexes, Juan Velasquez, Faith Robinson, Sebastien Ghent, Taseef Rahman

Bellini College REU Symposium (BCREUS)

Introduction & Problem

Intrinsically disordered proteins (IDPs) and their associated “fuzzy” complexes represent a major unresolved challenge in structural biology. Unlike traditional protein complexes that adopt stable, well-defined tertiary structures, fuzzy complexes retain conformational heterogeneity even in the bound state [1]. This dynamic behavior is functionally important in processes such as transcriptional regulation, signaling, and phase separation, but it complicates both experimental characterization and computational prediction. Recent advances in deep learning-based protein structure prediction, particularly AlphaFold2 and its successors, have demonstrated near-experimental accuracy for ordered proteins [2]. However, these models are fundamentally trained on static structural data, primarily derived from …

Hacksee: Security Platform For All, Jamie Giarratana, Mohamed Eltonamly, Ben Gipalo, Robert Karam

Bellini College REU Symposium (BCREUS)

HaCKSEE intends to provide an online hardware security training platform to educators at a reduced cost. By centralizing physical experiment hardware to a provisioning service and implementing timesharing via a dynamic queue system and custom hardware, we can dramatically reduce costs while retaining a familiar workflow. HaCKSEE allows students to flash custom firmware and experiments to experiment boards and return outputs (e.g. power-consumption data) to be displayed in the development environment.

HaCKSEE offers a new approach that enables educators and trainees to get started without the high barrier-to-entry costs associated with traditional hardware security training.

Teacher Candidates’ Reflective Practices Of Mathematics Curriculum From The Lens Of Universal Design For Learning, Weichen Zhao

Journal of Practitioner Research

The Universal Design for Learning (UDL) framework encourages educators to proactively remove barriers in curriculum and instruction to increase accessibility for all learners. While UDL is often applied during lesson planning, it can also serve as a powerful tool for critically examining and revising existing mathematics curricula. Drawing on qualitative data from teacher candidates’ reflective journals and curriculum artifacts collected over two semesters, this study examines how guided reflection supported teacher candidates in identifying barriers, proposing inclusive adaptations, and deepening their understanding of equity-oriented mathematics instructional design. As a self-study grounded in participatory action research, the findings also informed the …

(Re)Imagining Research-Practice Collaboration And Partnership: Constructivism By Way Of Interdisciplinarity, Multimodality, And Humanity, Bethany Silva, Alecia Magnifico, Laura Allen, David Baroody, Ashley Barry, Shawna Coppola, Cathy Fraser, Emily Geltz, Anne Mcquade, Christina M. Ortmeier-Hooper, Laura Smith, Donna Turco

Journal of Practitioner Research

Research-Practice Partnerships (RPPs) have become an important vehicle for educational research. By connecting researchers and educators, RPPs can couple systematic research and practical application. However, relational practices for building research collaboratives are understudied, and RPPs often reinscribe power imbalances among practitioners and researchers. With its focus on the centrality of practitioners and their knowledge, practitioner research offers possibilities for disrupting such power imbalances. In this reflective essay, our team describes our efforts to harness practitioner research’s capacity to identify and address salient school-level issues and RPPs’ power to impact a wider audience. We identify practices to build relationships, inform research …

Breathing Life Into Sel: A Practitioner Inquiry On Hā, Belonging, And Multilingual Learners In Hawai‘I, Mylia Briggs, Monica Gonzalez Smith

Journal of Practitioner Research

This practitioner inquiry explores how a Pacific-oriented social-emotional learning (SEL) framework, Nā Hopena A‘o (HĀ: BREATH), can affirm the cultural identities and emotional well-being of Filipino multilingual learners (MLs) in Hawai‘i. Implemented over a 15-week period in a third-grade classroom, the study draws on culturally adapted SEL lessons, student exit tickets and focus groups, and teacher reflections to examine how SEL shifts when grounded in Indigenous values, heritage language use, and community knowledge. Findings reveal three key themes: (1) Cultural Connection Fosters Belonging, (2) Language Visibility Promotes Emotional Safety, and (3) Identity-Affirming Practices Build Confidence and Voice. While students responded …

From Inquiry To Action: Leveraging Group Level Assessment To Elevate Teacher Voice, Claire C. Underwood, Leslie Kochanowski, Abraham Underhill

Journal of Practitioner Research

This methodological paper explores the use of Group Level Assessment (GLA) (Vaughn & Lohmueller, 2014; Vaughn, 2024) as a participatory approach to practitioner inquiry within an early childhood education program. Using Cochran-Smith and Lytle’s (2009) inquiry as stance as a guiding conceptual framework, GLA is framed as a methodology that affirms educator expertise, fosters collective reflection, and generates tangible action. We document the adaptation and implementation of the GLA protocol at the Arlitt Center, a university-affiliated early childhood laboratory school committed to teacher-led professional learning. Through an adapted GLA process, teaching staff engaged in identifying barriers and opportunities related to …

Exploring Researcher-Practitioner Authorship Collaboration In English, Foreign Language, And Mathematics Education, Rachel Cullen, Joseph Taylor, Matthew Laney, Mohamed Nouri

Journal of Practitioner Research

This study examined collaboration and bidirectional relationships between researchers and practitioners in the context of journal publications. Through exploration of research and practitioner journals in the areas of English, Foreign Languages, and Mathematics, we aimed to understand how authorship patterns and types of references illustrate the gap between research and practice. Findings indicate that collaboration between researchers and practitioners in the context of journal publications is minimal, and practitioner presence is scarce in research. The types of references included in publications are high quality regardless of authorship, but there is a problem of exposure that limits the research from reaching …

Numeracy-Based Civic Education Model: Needs Analysis Through An Explanatory Sequential Design, Sulkipani Sulkipani, Kokom Komalasari, Sapriya Sapriya, Susan Fitriasari, Vina Amilia Suganda Makenun

Numeracy

The United Nations Sustainable Development Goals emphasize numeracy as essential for quality education, and require its integration across the curriculum, including into civic education (CE). However, the integration of numeracy in CE in Indonesian universities has not yet been clearly mapped out. This study aims to analyze the need for numeracy integration in CE as a basis for developing a numeracy-based CE learning model. Using a mixed method with an explanatory sequential design, the study involved a convenience sample of 225 students and 10 lecturers from various universities through surveys, interviews, observations, and documentation studies. Quantitative findings show that numeracy …

Gnsi Decision Brief: Global Fragility Reauthorization Act: Through An America First Foreign Policy Lens, Greg Howell

GNSI Decision Briefs

Over the past several decades, positive collaboration between U.S. government departments and agencies supporting development, diplomacy, and defense (3D) has resulted in foreign policy success stories, improving international relations and saving lives around the world. Many of these positive outcomes were achieved when American assistance was requested in response to natural disasters or humanitarian crises, such as following the 2004 tsunami in Indonesia, the 2010 earthquake in Haiti, and the 2020 COVID pandemic. The Global Fragility Act (GFA) created a framework for interagency cooperation internationally, which produced a strong foundation to advance this promising 3D model for foreign assistance. The …

Needs Assessment Plan: For An Undergraduate In Reearch Administration (Ra) Curriculum With Artificial Intelligenc Integration., Jo Ann Smith

All Research Ops Exchange Publications

This needs assessment plan establishes a framework for developing an undergraduate Research Administration (RA) curriculum that integrates artificial intelligence (AI) competencies across all program components. The plan synthesizes findings from research literature across workforce competency studies, national RA curricula frameworks, e-mentoring models in undergraduate programs, and AI pedagogy in professional education. Key findings reveal that entry-level research administrators require core competencies, including critical thinking, interpersonal skills, written communication, and knowledge of the research enterprise, which are valued by hiring managers (Parker, 2024; Signorelli et al., 2025). The evolving research administration landscape increasingly demands AI literacy, including the ability to interact …

Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert

International Journal of Speleology

This study investigates the relationship between sinkhole occurrence and distance to drainage in the Sivrihisar region (Central Turkey) and evaluates the suitability of different regression approaches for modeling clustered count data in karst terrains. A comprehensive inventory of 104 sinkholes developed within the Neogene lacustrine limestones of the Akpınar Formation was compiled using official records, remote sensing analyses, and detailed field surveys. Sinkhole occurrences were analyzed relative to a drainage network derived from a high-resolution Digital Surface Model and grouped by proximity to drainage lines. Linear Regression (LM), Poisson Regression (PR), and Negative Binomial Regression (NBR) models were comparatively applied …

Cvnp Spring And Fall Census Dwight Chasar, Dwight Chasar

Cleveland Bird Calendar

No abstract provided.

Gull And Tern Comparisons, Chuck Slusarczyk Jr

Cleveland Bird Calendar

No abstract provided.

First Record Of Northern Wheatear For The Cleveland Region, Ray Hannikman

Cleveland Bird Calendar

No abstract provided.

Sightings Location Key, The Cleveland Bird Calendar

Cleveland Bird Calendar

No abstract provided.

Comments On The Season – Headlands / Mentor Lagoons, Fall 2014, Ray Hannikman

Cleveland Bird Calendar

No abstract provided.

The Year’S Latest / Earliest Dates, The Cleveland Bird Calendar

Cleveland Bird Calendar

No abstract provided.