Digital Commons Network^™

Reday Program 2026, Bryant University

Bryant REDay (Research and Engagement Day)

Program for the 2026 Bryant REDay (Research and Engagement Day). Program includes schedule at a glance, descriptions for panels, workshops, and presentations, along with sign-up links for specific sessions in the electronic version of the program. Printed program was in color with double-sided printing on 8 1/2" x 11" paper stapled together in the upper left corner.

Ski Industry Professionals In New Hampshire Are Worried About Climate Change, Jacklyn Tracy, Elizabeth Burakowski

Carsey Publications

In this brief, authors Jacklyn Tracy and Elizabeth Burakowski report the results of an online survey conducted in June 2025 with New Hampshire ski industry professionals to gain insight into how they perceive climate change. Understanding the perspectives on climate change is an important first step in working to preserve a vital industry to the state as temperatures rise and winters shorten. The results of the survey revealed that the majority of New Hampshire ski industry professionals are concerned about the effects of global warming on the ski industry in the state and believe more should be done to address …

At-Home Computational And Data Literacy For Pre-K–5 Students: A Review Of The Literature, Marc Sager, Sarah Miller, Zarek Drozda

Journal of Educational Research and Practice

This systematic review investigates best practices for promoting data literacy development in pre-K–5 learners, with a specific focus on caregiver involvement in at-home learning environments. A comprehensive search and screening process identified 42 studies for inclusion. The studies were analyzed to determine effective strategies for fostering early data literacy. Key findings emphasize (1) early, developmentally appropriate engagement with attention to equity; (2) core learning outcomes in computational and data literacy; (3) learning approaches integrating real-world contexts and hands-on experiences; (4) balanced use of digital tools and unplugged activities; and (5) essential parental and caregiver involvement. The review highlights integrating data …

Complex Systems Mapping Of Fiscal Growth Dynamics At Strategic Maritime Chokepoints Using Time-Series Slopes, Rahul Balamurugan, Preethi Nanjundan, Avichal Sharma

Northeast Journal of Complex Systems (NEJCS)

This study examines how maritime and trading states allocate public resources between defence, health, and economic growth around three strategic chokepoints the Strait of Malacca, the Strait of Hormuz, and the Suez Canal. The analysis extends the classic “guns versus butter” framing by treating defence and health spending as co-evolving components of an interconnected fiscal-growth system. Using World Development Indicators data (1999-2024), trend slopes are estimated for military spending (% of GDP), healthcare spending (% of GDP), and GDP growth (annual %). Two derived indicators are computed, a defence-to-health slope ratio (military slope/health slope) and a fiscal-balance proxy (health slope …

Arum–D Nexus: Adaptive Reflexive Urban Metabolism For Complex Construction And Demolition Waste Governance In Bengaluru, Talat Naaz, Rosewine Joy

Northeast Journal of Complex Systems (NEJCS)

Urban material systems exhibit nonlinear dynamics governed by feedback, adaptation, and emergent coupling among institutions, markets, and behaviors. Construction and demolition (C&D) waste in Bengaluru is a great example of such complexity, where fragmented regulation, informal actors, and digital asymmetries coalesce into unstable waste flows and resource leakages. This study conceptualizes Bengaluru’s C&D waste system as a Complex Adaptive System (CAS), where institutional, market, behavioral, and metabolic subsystems co-evolve through nonlinear feedback interactions. A meta-analysis of secondary literature combined with benchmarking of government datasets is used to evaluate two key complexity indicators, i.e., response speed and feedback density. The advancement …

Ai Exposure And The Future Of Work: Tasks, Skill Demand, And Education, Erik Vasilauskas, Michael Horrigan

External Papers and Reports

No abstract provided.

Multiple-Valued Quantum Automata For Robotics, Yuchen Huang

Dissertations and Theses

This dissertation introduces a new type of quantum automata, their encoding and circuit realization. I concentrate on possible applications in robotics. Several methods and application of quantum automata and quantum circuit-based controllers for elementary robotic systems, with a focus on humanoid robot motion, emotion, and behavior generation are illustrated in detail. The research introduces several novel methodologies that bridge quantum computing principles with robotic control, aiming to overcome the limitations of classical deterministic and probabilistic approaches.

The dissertation first presents a quantum-circuit-based framework for generating non-repetitive and expressive (e)motions in a humanoid robot actor, using superposition and entanglement to produce …

What It Takes To Solve The Origin Of Life: An Integrated Review. Part 1–Experimental Methods And Data Repositories, Silke Asche, Carla Bautista, Celia Blanco, David Boulesteix, Alexandre Champagne-Ruel, Cole Mathis, Omer Markovitch, Zhen Peng, Avinash Vicholous Dass, Eloi Camprubi

School of Integrative Biological & Chemical Sciences Faculty Publications

The origin(s) of life (OoL), which has puzzled scientists for centuries, remains a major scientific challenge in the 21st century. Research on OoL spans many disciplines, including chemistry, physics, biology, planetary sciences, computer science, and mathematics. The sheer number of different scientific perspectives relevant to the problem has resulted in the coexistence of diverse tools, techniques, data, and software in OoL studies. This has made communication between the disciplines relevant to the OoL extremely difficult because the interpretation of data, analyses, or standards of evidence varies dramatically. Here, we hope to bridge this wide field of study by providing common …

Ai Method For Classification Of Diagnosis Of Near-Infrared Breast Lesion Images, Kaiquan Chen, Fangyang Shen, Honggang Wang, Zhengchao Dong, Jizhong Xiao, Ming Ma, Afroza Aktar, Christopher Chow, Wenxiong Zhang

Publications and Research

In near-infrared optical breast lesion screening and diagnosis systems, high-speed four-dimensional scanners can dynamically acquire tens of thousands of lesion images within a five-minute period. Currently, manual computer annotation is required to generate standard samples from these scanned breast lesion images, a process that depends heavily on physicians with clinical expertise. On average, a single physician can annotate only approximately ten samples per working day. As a result, this process is time-consuming and labor-intensive, and the collected samples often suffer from low accuracy, large variability, and limited diagnostic reliability. Several AI-based annotation tools, such as QuPath, HALO AI™, and X-AnyLabeling, …

Instructors' Lived Experiences Of Using Authentic Assessments In College Calculus Courses Across The United States: A Phenomenological Study, Christy Hart Kains

Doctoral Dissertations and Projects

The purpose of this transcendental phenomenological study was to describe the lived experiences of instructors with authentic assessments in college calculus courses across the United States. The theory guiding this study was Astin’s student involvement theory, which provided a framework to study the involvement of students in higher education. The central research question for this study was: What are the lived experiences of instructors who utilize authentic assessments in college calculus courses across the United States? This study used a qualitative design following the transcendental phenomenological approach of Moustakas. The sample included 12 instructors from two-year and four-year colleges in …

Solving Wordle Using Information Theory, Talal Aladaileh, Donald Stephens, Mallak Alqaisi, Congyu Wu

Northeast Journal of Complex Systems (NEJCS)

Wordle, a popular word-guessing game, challenges players to identify a five-letter secret word through iterative guesses and feedback on letter placement. The players must figure out the secret word within six guesses. After each guess, the letters will be color-coded based on different criteria. Optimizing the choice of guesses is critical for maximizing success within the limited attempts allowed. In this study, the application of Shannon entropy is explored as a strategy for selecting words that maximize information gain at each step of the game. By quantifying the uncertainty reduction achieved by potential guesses, this method prioritizes words that are …

A Multi-Layer Complex Adaptive System Framework For Ai-Driven Robo-Advisory Services, Jesty Mariam Philip, Mohit Boralkar, Alwin Joseph

Northeast Journal of Complex Systems (NEJCS)

The rapid integration of Artificial Intelligence (AI) into investment advisory services has changed financial decision-making, giving rise to adaptive robo-advisory systems capable of real-time analysis, personal recommendations, and autonomous portfolio optimization. Existing research evaluates these systems primarily through technological performance or investor adoption, overlooking the complex feedback-driven interactions that emerge when AI analytics, data environments, and human behavior operate together. This study addresses this gap by conceptualizing AI-enabled robo-advisors as a multi-layered Complex Adaptive System comprising historical data, real-time data, AI analytics, investor perception, and decision-making layers. A simulation model grounded in machine learning dynamics, behavioral finance, and complexity theory …

Regional Drought Modulation By Enso And Iod As Indicated By The Standardized Precipitation Index, Arpit Tiwari, Preethi Nanjundan, Tanu Sharma, Ravi Ranjan Kumar, Satyaban Bishoyi Ratna

Northeast Journal of Complex Systems (NEJCS)

Understanding the modulation of drought by large-scale ocean–atmosphere teleconnections is crucial for strengthening drought prediction and resilience in India. This study investigates the influence of the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on meteorological drought characteristics across India from 1950 to 2024 using the Standardized Precipitation Index (SPI) at a 12-month timescale. Drought events were quantified in terms of frequency, duration, severity, and intensity and linked to ENSO–IOD variability through composite, correlation, and mediation analyses. Results reveal that El Niño events consistently correspond to widespread and severe droughts, particularly over central and southern India, with drought …

Improving User Experience And Functionality: The Redesign Of Sorora In React Native*, Katherine A. Arroyo, Oswin S. Shin

Campus Research Month

This project redesigned and extended Sorora, a safety-focused mobile application built in React Native. The original Android Minimum Viable Product (MVP) included location tracking, an SOS button, and a basic contact list, but the interface lacked clarity, and the feature set created friction during urgent situations. We improved the UI and UX using Nielsen's usability heuristics, reduced navigation complexity, and redesigned the emergency workflow for deliberate, fast interaction.

Chat Component For Php Web Apps*, Linton W. Feitosa, Caleb N. Hoffman

Campus Research Month

Chat rooms are a common feature in much of today's software. While many web applications could benefit from them, developing individual chat implementations can be repetitive and time consuming. Furthermore, publicly available and integrable chat components are difficult to find.

We created a general-use chat component for PHP web applications using the Yii2 framework. Our component features chat rooms, asynchronous messaging, and contact management. It is widely applicable, customizable, documented, and can be easily extended by future developers.

Bgc-Argo Float Reveals Shifts In Nitrogen-Carbon Cycling In An Oxygen-Deficient Zone, Mariana B. Bif, Colette Kelly, Mark A. Altabet, Annie Bourbonnais, Claire Elbon, Edgart Flores, Alanna Mnich, Josh Plant, Kenneth S. Johnson

Faculty Publications

Oxygen-deficient zones are hotspots of marine fixed nitrogen loss, but the temporal dynamics of their microbial processes remain poorly resolved. Here we present a nearly three-year high-resolution record from a Biogeochemical Argo float in the Eastern Tropical North Pacific that captures a decline in nitrite concentrations, reflecting a shift in nitrogen redox balance. Using a stoichiometric mass-balance model, we quantify nitrogen transformations, including dissimilatory nitrate reduction to nitrite, denitrification, anammox, and nitrite oxidation, and their coupling to carbonate chemistry. The model shows that dissimilatory nitrate reduction to nitrite dominates nitrogen transformations, while denitrification and anammox vary over depth, biogeochemical transition, …

Sandag’S Regional Climate Action Planning, San Diego Regional Climate Collaborative, Brenda Castruita

San Diego Regional Climate Collaborative

The San Diego Association of Governments (SANDAG) is the regional planning agency responsible for transportation planning, public transit development, and environmental planning in the San Diego metropolitan area.1 Beyond these focus areas, SANDAG aims to promote sustainable growth, enhance mobility, and improve the quality of life of local citizens through comprehensive planning and collaboration with local governments, communities, and various partners. SANDAG is governed by a Board of Directors made up of elected officials from each of the region's local city councils and County Board of Supervisors. In addition to developing plans for how people and goods will move …

Spatial Future Ahead! Augmented Reality And Anticipated Life Consequences, Sergio Barta, Reto Felix, Chris Hinsch, Mahdokht Kalantari, Nina Krey, Philipp A. Rauschnabel

Marketing Faculty Publications

Purpose: This study explores how initial exposure to immersive spatial computing experiences using AR headsets generates lasting inspiration and shapes consumers expected long-term life consequences (i.e., enhancement of reality, perceived substitutability and social impact).

Design/methodology/approach: The study uses a time-lagged research design based on 148 first-time users of spatial computing devices (AR headsets). Respondents were interviewed once shortly after being exposed to AR and a few days later. Data is analyzed using partial least squares structural equation modeling (PLS-SEM).

Findings: Users' immediate “inspired-by” experiences predict increased “inspired-to” intentions days later. Such inspiration translates into anticipated consequences such as virtually customizing …

Unequal Recovery: Climate Gentrification And The Marginalization Of Southern Urban Communities In Disaster Relief, Ryan Simone Anderson '26

Honor Scholar Theses

Increases in the severity and frequency of natural disasters in the United States have highlighted the vast inequalities that low-income communities must be prepared to face and rapidly recover from. In the Southern US, this dilemma is prevalent, with a higher risk of flooding, hurricanes, and tornadoes due to increased exposure to natural disasters and climate-related events. These climate-induced issues have revealed a connection between environmental risks and socio-economic vulnerability. Climate gentrification occurs when lower-income communities are displaced to hazardous or vulnerable areas, while wealthier communities relocate to safer, more protected areas. Well-documented, large-scale disasters such as Hurricane Katrina (2005) …

Adopting Artificial Intelligence: Cross-Sector Analysis Of Ai Adoption Risks, Brandon Saari, Yona Berger, Yanett Munoz, Alex Agnick, Paul Wagner, Robert J. Honomichl

Journal of Cybersecurity Education, Research and Practice

Artificial intelligence (AI) is rapidly being adopted across public and private sectors. This offers significant gains in efficiency, decision making, and access to information. At the same time, AI introduces complex risks related to cybersecurity, privacy, bias, transparency, accountability, and equity that existing governance and security frameworks do not fully address. This paper presents a cross-sector literature review and comparative analysis of AI adoption risks and mitigation strategies across four critical domains: the federal government, libraries, K–12 education, and healthcare. Drawing on peer-reviewed research, institutional frameworks, and policy guidance, the study identifies sector-specific challenges alongside shared systemic gaps, including insufficient …

Innovations And Applications Of Virtual Private Networks And Sustainable Security In Society 5.0 Libraries, Stella Chinnaya Nduka Dr., Adeyinka Tella Prof, Petros Dlamini Dr

Journal of Cybersecurity Education, Research and Practice

In order to improve digital resilience, privacy, and access equity in contemporary library environments, this study investigates the role of Virtual Private Networks (VPNs) in fostering sustainable cybersecurity within the framework of Society 5.0 libraries. It does this by looking at the latest developments, applications, difficulties, moral dilemmas, and tactical methods associated with VPN deployment. Using peer-reviewed journal articles, conference proceedings, white papers, and policy documents published between 2010 and 2024, a methodical approach to literature review was used. The literature that bridges the fields of cybersecurity, library science, and Society 5.0 concepts was the main focus of the review. …

Preliminary Sonification Of Enso Using Traditional Javanese Gamelan Scales, Sandy Hs Herho, Rusmawan Suwarman, Nurjanna J. Trilaksono, Iwan P. Anwar, Faiz R. Fajary

Northeast Journal of Complex Systems (NEJCS)

Sonification—the mapping of data to non-speech audio—offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870–2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two- dimensional acoustic phase space. Recurrence-based diagnostics, convex hull ge- ometry, and coupling analysis reveal that the sonification …

Cloud-Based Lightweight Spatiotemporal Deep Learning Sign Language Recognition Model With Digital Twin Avatar, Mohammed Zuhair Abduljabbar

Thesis/ Dissertation Defenses

This dissertation proposes a full framework for sign language recognition (SLR). This study introduces Meta AI concept and a cloud-based framework that integrates a spatial detection and recognition model for sign language alphabet, and a spatiotemporal Transformer model for word-level SLR. The framework design also integrates a 3D digital twin that acts as a sign language interpreter on real time enhancing user friendliness and human computer interaction with the system. The major focus is finding the balance between performance accuracy and computation complexity efficiency starting with the framework communication between AI agents and the SLR models and digital twin efficiency. …

Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert

Doctoral Dissertations and Master's Theses

Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …

The Expanding Digital Border: Ai, Surveillance, And The Fight For Justice, James Chesser

Immigration and Human Rights Law Review

As artificial intelligence transforms the mechanisms of immigration control, the modern border has become a digital filter—one governed less by geography and more by code. This Article examines the legal, technical, and ethical implications of AI-driven systems now central to global border enforcement, including biometric surveillance, algorithmic risk scoring, and predictive profiling. It explores how states use these technologies not only to manage irregular migration, but to compete for global talent—constructing migration regimes that reward capital and compliance while eroding transparency, due process, and equality.

Through an international and comparative lens, the piece highlights the expansion of algorithmic decision-making across …

Adaptive Parallel Downloader For Large Genomic Datasets, Rasman Mubtasim Swargo

Miners Solving for Tomorrow Research Conference

Modern next-generation sequencing (NGS) projects routinely generate terabytes of data that researchers download from public repositories such as SRA and ENA. Existing download tools typically employ static concurrency settings, leading to inefficient bandwidth utilization and prolonged download times under dynamic network conditions. We introduce FastBioDL, a parallel downloader for large biological datasets with an adaptive concurrency controller. FastBioDL frames downloading as an online optimization problem, using a utility function and gradient descent to adjust the number of concurrent socket streams during runtime. This approach maximizes throughput while minimizing resource overhead. Evaluations on public genomic datasets show that FastBioDL achieves up …

Robust Federated Learning With Strategic Adversaries, Manoj Twarakavi

Miners Solving for Tomorrow Research Conference

Federated Learning (FL) leverages the intelligence of untrusted distributed devices through collaborative training. This makes the training process susceptible to malicious behavior. Existing defense mechanisms largely consider an adversary who attacks a proactive FL server without any adaptability. However, they overlook the presence of a strategic adversary. To address this challenge, our work proposes a Robust Game-theoretic framework where the adversary is both strategic and is equipped with the capability of performing large-scale poisoning attacks.

Distributed Control Plane For Cross-Silo Federated Learning, Rabin Pandey

Miners Solving for Tomorrow Research Conference

Cross-silo federated learning (FL) trains shared models across geographically distributed institutions without centralizing raw data, but its reliance on wide-area networks makes round completion time highly sensitive to heterogeneous link conditions, congestion, and straggler clients. Existing SDN-based FL frameworks address this through centralized traffic engineering, an approach that breaks down when silos span independent administrative domains where no single entity can maintain complete, timely network knowledge. We replace the centralized control plane with a fully distributed overlay in which each silo gateway operates as an equal peer, continuously probing local links, exchanging EWMA-smoothed metrics via bounded gossip, and computing least-cost …

Literature Review Of Local Culture-Based Mathematics E-Module With Islamic Values In Probability, Maya Puspita Sari, Surya Sari Faradiba

Jurnal Pendidikan Sains

This study is grounded in the need to address the limitations of probability learning that is often procedural, decontextualized, and disconnected from students’ cultural and religious values. It aims to develop a comprehensive understanding of how local cultural contexts and Islamic values can be systematically integrated into mathematics e-modules, particularly for probability learning, and to formulate structured design principles and quality indicators for their development. This paper adopts a Systematic Literature Review (SLR) approach by analyzing empirical studies published between 2020 and 2025, using a structured selection process involving identification, screening, eligibility, and inclusion stages. A total of 11 high-quality …

The Effect Of Virtual Laboratories On Students Interest And Learning Outcomes In Spermatophyta At Sma Negeri 1 Sojol, Ismawati Ismawati, Sutrisnawati Sutrisnawati, Manap Trianto, Masrianih Masrianih, Abd Rauf, Musdalifah Nurdin

Jurnal Pendidikan Sains

Limited access to physical laboratory facilities and the abstract nature of Spermatophyta material reduce students’ learning interest and outcomes, necessitating the use of innovative digital learning media such as virtual laboratories. This study aims to analyze the effect of Virtual Laboratory (V-Lab) implementation on students’ learning interest and cognitive learning outcomes in Spermatophyta material at the senior high school level. A quantitative quasi-experimental design with a posttest-only control group was employed involving 66 eleventh-grade students divided into experimental and control classes; data were collected using a learning interest questionnaire and a multiple-choice test, and analyzed using independent samples t-test after …