Digital Commons Network^™

Bridging The Gap: A Systematic Review Of Cyber Conflict Forecasting Models And The Case For Ai-Driven Dynamic Frameworks, Salim Arfaoui, Youssef Harrath, Omar El-Gayar

Research & Publications

Cyber conflict forecasting remains constrained by static models that overlook the integration of geopolitical context with technical indicators. This systematic literature review examines 58 studies (2010–2025) using PRISMA guidelines and an InputProcess-Output framework to classify approaches and identify key gaps. Quantitative methods dominate (67%), yet only 14% incorporate geopolitical variables, despite the political nature of cyber conflict. Major limitations include adversarial adaptation blindness (85% assume static behavior), coarse temporal granularity (72% use daily+ intervals), lack of uncertainty quantification (75%), and minimal modeling of cross-domain escalation (92% cyber-only focus). Strategic forecasting is rare, with just 14% providing long-term insights and 16% …

Datamut: Deterministic Algorithms For Time-Delay Attack Detection In Multi-Hop Uav Networks, Keiwan Soltani, Federico Corò, Punyasha Chatterjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs), also known as drones, have gained popularity in various fields such as agriculture, emergency response, and search and rescue operations. UAV networks are susceptible to potential security threats, such as wormhole attacks, jamming, spoofing, and false data injection. Time-Delay Attack (TDA) is a unique attack in which malicious UAVs intentionally delay packet forwarding, posing significant threats, especially in time-sensitive applications. It is challenging to distinguish malicious delay from benign network delay due to the dynamic nature of UAV networks, intermittent wireless connectivity, or the Store-Carry-Forward (SCF) mechanism during multi-hop communication. Some existing works propose machine learning-based …

Pciafl: Personalized And Class Imbalance-Aware Federated Learning For Driver Behavior Classification, Osho Osho, Shubh Garg, Suchetana Chakraborty, Sajal K. Das

Computer Science Faculty Research & Creative Works

Automated understanding of driver behavior from vehicular kinematics is vital for safety-aware intelligent transportation systems. However, centralized cloud processing suffers from latency, scalability, and privacy issues. Federated Learning (FL) provides a decentralized alternative but faces two major challenges: (i) non-IID client data due to heterogeneous driving styles and sensors, and (ii) severe class imbalance, as risky behaviors are inherently rare. In this work, we propose a personalized FL framework that uses a shared CNN-LSTM backbone with client-adaptive classifiers and incorporates a cost-sensitive loss to address behavior skew. Evaluated on the UAH-DriveSet dataset, our method achieves 92.60% accuracy and 91.68% macro-F1, …

2026 Revised Draft Final Bpsou Backfill And Cover Material Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Statistics Of Glinting Clouds Observed By Dscovr And Geostationary Satellites, Tamás Várnai, Alexander Marshak, Alexander Kostinski

Michigan Tech Publications

This study examines how frequently the specular reflection of sunlight—that is, sun glint—reveals the presence of ice crystals that maintain a steady horizontal orientation. The study analyzes data from the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft and from collocated images taken by geostationary satellites. The analysis of spatio-temporal variations in glint frequency over vegetated land surfaces reveals that (a) year-to-year variations are modest with no clear trends; (b) glints typically occur 7%–8% more frequently than previously estimated; (c) glints are most frequently observed during the May-August period, and over Asia. The results also …

Optimizing Proaftn Classifier With Ant Colony Algorithm: Enhanced Diabetes Detection Benchmarking, Feras Al-Obeidat

All Works

The increasing global prevalence of diabetes highlights the need for accurate diagnostic tools to improve early detection and effective treatment planning. Traditional classification models often struggle to achieve optimal performance due to limitations in parameter tuning and adaptability to complex datasets. To address these limitations, this article introduces PROAnt, an innovative learning approach designed to enhance the robustness and efficiency of the PROAFTN multicriteria classification method. PROAnt leverages the computational power of ant colony optimization (ACO) to dynamically fine-tune and optimize the key parameters, such as intervals and weights, at the core of the PROAFTN classification process. This learning methodology …

Inhomogeneous Branching Random Walks: Incorporating Genealogy And Density Effects, Lauren Ajax, Beatrice Durham, Pratima Hebbar, Cade Johnston, Jiayi Zhang

Spora: A Journal of Biomathematics

We introduce a novel framework using inhomogeneous branching random walks (BRWs) to model biological processes, specifically by introducing genealogy-dependence in branching rates and displacement distributions to model bacterial colony growth. Current stochastic models often either assume independent and identical behavior of individual agents or incorporate only spatiotemporal inhomogeneity, ignoring the effect of genealogy-based inhomogeneity on the long-time behavior of these processes. Such asymptotics are of independent mathematical interest and are crucial in understanding the emergence of patterns. We propose several inhomogeneous BRW models in 2D space where displacement distributions and branching rates vary with time, space, and genealogy. A combined …

The Sunday Math Circle, Nathan Pflueger

Journal of Math Circles

Bob and Ellen Kaplan envisioned and organized a style of math circle centered on the idea that children of all ages can work like mathematicians do: creatively, collaboratively, and ecstatically. This article surveys four sample topics covered during a Sunday morning math circle in the Boston area, based on Bob and Ellen's invaluable guidance. I also offer some reflections on what I learned from Bob and Ellen, and how it is reflected in these math circles.

Infinite Line, Infinite Knowledge: The 'Spera' And Organized Chaos In Lambert's Encyclopedia, The 'Liber Floridus', Ava Romano

Theses and Dissertations

The Liber Floridus is a medieval encyclopedia renowned for its program of circular diagrams, or sperae. Inside this manuscript of 190 chapters, these diagrams frame and embody written knowledge, revealing a connection between encyclopedism and life in the Benedictine monastery by creating a coherent visual organization of chapters.

Simulation Of Quantum Walks For Secure Data Access Patterns, Arslan Ahmad Janjua

Theses and Dissertations

Quantum computing is revolutionizing computational science, offering fundamentally new approaches to information processing that surpass classical limitations. One of the most versatile and powerful tools in this emerging field is quantum walks. Quantum walks are quantum analogs of classical random walks that leverage superposition and interference to explore complex spaces efficiently.

This thesis will explore how discrete-time scattering quantum walks can be simulated and analyzed to investigate patterns of secure data access. By modeling quantum walks on a variety of graph structures and studying the dynamics of marked vertices, the project aims to demonstrate how quantum interference and graph topology …

Structural Characterization Of Peptide Nanoaggregates At Varying Concentrations And Their Impact On Cellular Responses, Malika Rozmetova

Theses and Dissertations

Peptide nano-assemblies can regulate cellular pathways in a structure-dependent manner. Here, we show that the enzyme-responsive peptide NapFFK(NBD)Yp forms distinct nanoscale assemblies at different concentrations, triggering differential ER stress and extracellular vesicle release in MDA-MB231 cells. These results highlight the importance of supramolecular organization in peptide–cell interactions.

Ai In Society: A Regulatory Framework For Responsible Integration, Ziad Doughan, Sari Itani, Hadi Al Mubasher

BAU Journal - Science and Technology

This review paper studies the influence of Artificial Intelligence (AI) and Machine Learning (ML) on society in various categories in detail. AI and ML have developed rapidly in the past two decades, thus changing our lifestyles. These developments have various positive and negative impacts on society. This paper explores the many societal impacts of AI and ML, in economics, social aspects, ethics, and policy, shedding light on the opportunities and challenges that arise. An interdisciplinary insight is capable of understanding the challenges society faces when it uses AI and ML, locking opportunities that lie ahead and identifying promising paths towards …

Crystal Structure Of Methanococcus Jannaschii Dihydroorotase With Substrate Bound, Jacqueline Vitali, Jay C. Nix, Haley E. Newman, Michael J. Colaneri

Physics Faculty Publications

Here, we report the X-ray structural analysis of dihydroorotase from Methanococcus jannaschii co-crystallized with dihydroorotate at pH 6.5. The crystals are isomorphous with the crystals of the apoenzyme, with space group P3₂21 and unit-cell dimensions a = b = 111.4, c = 101.2 Å. The structure was refined to R = 0.169 and R_free = 0.186 at a resolution of 1.87 Å at room temperature. During crystallization the degradative reaction took place, and the electron density in the active site corresponds to the substrate carbamoyl aspartate. Carbamoyl aspartate interacts with the protein in the active site …

The Ai Revolution In Virtual Try-Ons: A Means-End Chain Model Perspective, Ju-Young M. Kang, Ji Young Lee, Dooyoung Choi, Sumin Helen Koo, Jeehyun Song, Youngjin Bahng

Educational Leadership & Workforce Development Faculty Publications

Leading brands have begun to implement artificial intelligence-driven virtual try-on (AI VTO) technology, which helps reduce returns and increase conversion rates, repeat purchases, and customer loyalty. This research aimed to examine how retail user experience with specific perceived quality factors of AI VTOs influences users’ value equity and downstream loyalty and to investigate the moderating effects of clothing in relation to the self as structure and concern for physical appearance, based on a Means–End Chain model. Data were collected from 509 U.S. online apparel shoppers using a consumer panel. Structural equation modeling and multigroup analysis were used for data analysis. …

Ai Tips And Traps, Patrick Barry

Books

Based on a series of popular courses and workshops that Professor Patrick Barry has created for students, professionals, and anyone else interested in taking a skills-based approach to artificial intelligence, this book gives you a chance to engage with important AI concepts, experiment with exploratory AI exercises, and then ultimately develop your own customized list of AI traps to try as well as AI traps to avoid.

Llm-Driven Weekly Newsletter To Assess Open Source Software Project Github Health, Christian Novalski, Christopher Chavez, Ghalian Fayyadh, Kostadin Damevski

UROP Posters

Open Source Software (OSS) projects increasingly depend on a diverse set of contributors, including episodic participants who contribute intermittently. Episodic contributors represent a large portion of OSS communities, yet projects often struggle to retain them, leading to decreased project health and continuity. While dashboards and real-time communication tools support continuously active contributors, they often fail to serve the unique needs of episodic participants, who may struggle to remain informed and re-engage with project activity after periods of absence. In this study, we examine the effect of a weekly, email-based newsletter intervention designed to improve awareness and engagement among episodic OSS …

Use Of Generative Ai In Scholarly Research: Challenges And Opportunities, Marco Marabelli, Robert M. Davison, Giovanni Gatti, Ankita Srivastava, Monideepa Tarafdar

Computer Information Systems Faculty Publications

The focus of this panel report is to present evidence of a panel discussion that took place in October 2025 on the use of generative artificial intelligence (GAI) in academic research and publishing. The panel included publishers (Elsevier, Emerald, Gailot Press, MIT Press, Nature/Springer, Wiley) and editors in chief (representing the Information Systems Journal, Journal of the AIS, Journal of Data Science and ICES Journal of Marine Science). Key outcomes of the panel are the following: 1) publishers and editors have some disagreements regarding GAI use; 2) besides disagreements, all recognize that GAI is here to stay, therefore outstanding issues …

Multi-Grade Deep Learning, Yuesheng Xu

Mathematics & Statistics Faculty Publications

Deep learning requires solving a nonconvex optimization problem of a large size to learn a deep neural network (DNN). The current deep learning model is of a single-grade, that is, it trains a DNN end-to-end, by solving a single nonconvex optimization problem. When the layer number of the neural network is large, it is computationally challenging to carry out such a task efficiently. The complexity of the task comes from learning all weight matrices and bias vectors from one single nonconvex optimization problem of a large size. Inspired by the human education process which arranges learning in grades, we …

A New Functional Setting For Term Structure Modeling Using The Health-Jarrow-Morton Framework, Michael Pokojovy, Ebenezer Nkum, Thomas M. Fullerton Jr.

Mathematics & Statistics Faculty Publications

The well-known Heath–Jarrow–Morton (HJM) framework provides a universal and efficacious instrument for modeling the stochastic evolution of an entire yield curve by explaining the interest rate dynamics in continuous time under no-arbitrage conditions. Existing implementations involve exponentially weighted function spaces as theoretical settings for the former stochastic evolution. While the choice of weight can have a drastic effect on model calibration and subsequent forecasting, it cannot be estimated from market data and does not allow for any objective interpretation. The proposed approach does not have this shortcoming as it adopts a suitably designed unweighted function space. The HJM equation is …

Genre Based Analysis Of Sustainability In Contemporary U.S. Film Production: Inception Or Illusion?, Tanner Ennis

Interdisciplinary Studies | Senior Theses

Anthropogenic activity is actively leading to environmental degradation, highlighting the need for large industries to take responsibility for their environmental impact, particularly the film industry. While sustainable practices in the film industry such as virtual production, recycling of set construction materials, or the use of renewable energy present opportunities to improve sustainability, there is still a substantial amount of progress to be made. For example, research has demonstrated that increases in production budget correlate with higher carbon dioxide emissions, with fuel, utilities, and travel acting as the top contributors (Sustainable Entertainment Alliance, 2022). Conversation among the scholarly community is centered …

Aura: An Ai-Powered Multimodal Prototype For Adaptive Apraxia Of Speech Therapy And Communication Support, Omotayo Omoyemi, Rachel K. Johnson

Speech-Language Pathology Faculty Publications

Apraxia of Speech (AOS) is a motor speech disorder that significantly limits communication and requires intensive, long-term therapy. Access to consistent treatment is often constrained by shortages of speech-language pathologists, high costs, and limited opportunities for continuous monitoring outside clinical settings. Recent advances in Artificial Intelligence (AI) provide new opportunities to support scalable and personalized speech therapy.

This paper presents AURA (Adaptive Understanding and Relearning Assistant for Apraxia), a multimodal AI framework designed to support speech therapy, progress monitoring, and communication for individuals with AOS. The system integrates speech analysis, machine learning–based error detection, reinforcement learning for adaptive therapy, and …

Setting The Recycling Narrative: A Thematic Analysis Of Recycling Webpages In The United States, Haley Nolde

Dissertations and Theses

Recycling is widely promoted in the United States as a central strategy for waste diversion and sustainable materials management, yet recycling outcomes remain inconsistent and public understanding is often fragmented. While substantial research examines recycling behavior, infrastructure, material science, and markets, less attention has been paid to how recycling itself is framed and communicated to the public. This thesis addresses that gap by examining narratives produced by recycling thought leader organizations (TLOs) in the United States. Using thematic analysis, this study analyzes publicly available recycling webpages from 99 TLOs, including state government agencies, state-level non-governmental organizations (NGOs), national and regional …

A Deep Neural Approach To Network-Based Obfuscated Malware, Meera Parmar, Sunil Gautam

ASEAN Journal on Science and Technology for Development

The rising prevalence of obfuscated malware poses a critical threat to network security, undermining traditional detection methods and jeopardizing data integrity and system reliability in an increasingly connected world. This growing danger highlights the urgent need for advanced solutions to protect against evolving cyber risks. This research intro-duces a novel framework to enhance malware detection, employing a hybrid architecture that integrates spatial and temporal analysis with attention mechanisms. The approach leverages a large dataset subsample, focusing on key feature selection and augmentation to improve robustness against evasion techniques. This innovative framework offers a significant advancement in identifying malicious network traffic, …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

Examining The Association Between Ddt Exposure And Parkinson’S Disease, Hodges Mccathern

Undergraduate Honors Theses

Dichlorodiphenyltrichloroethane, commonly known as DDT, was an organochlorine pesticide widely used in the mid-20th century. It is highly stable and resistant to degradation, leading to its long-term presence in the environment. This chemical bioaccumulates in ecosystems and in human tissue, particularly adipose tissue, raising concerns about chronic exposure. Emerging research links DDT exposure to adverse neurological outcomes, including increased risk for neurodegenerative disorders such as Parkinson’s Disease. Mechanistically, DDT and its metabolites may disrupt dopaminergic neurons, induce oxidative stress, and interfere with mitochondrial function, contributing to neurotoxicity. Understanding the environmental fate of DDT and its bioaccumulative properties is essential for …

When Words Flow Like Water: How The Enbridge Line 3 Pipeline Environmental Impact Statement Failed To Prevent Hydrogeologic Harm In Minnesota, Carly Gutzmann

Journal of Earth and Life Science

For the aquifers of Minnesota, the environmental impact statement (EIS) was a promise of protection that never left the page. An environmental impact statement is meant to be an aid in the decision making process in order to ensure that projects consider potential environmental harms that may occur. However, they are often used instead as another regulatory box to check, rather than as active considerations when planning. As such, a project plan can be flawed from the start—if project developers only consider environmental impacts after they have already put considerable time, effort, and funding into their project as-is, they may …

Carbon Storage In Headwaters Can Respond Rapidly To Climate Change, Maddie Benello, Carl Renshaw, Joshua Landis

Wetterhahn Science Symposium Posters

Headwater streams play a critical role in the global carbon cycle, serving as significant sites of carbon storage. While there have been recent efforts to quantify carbon storage in headwater streams in the western United States, there remains limited understanding of both the volume and timescale of carbon storage in northeastern forests which often have extensive logging and agricultural histories. Here, we quantify the carbon stock, residence time, and flux of a zero-to-first order headwater stream in Charles Downer State Forest (DF), VT using novel fallout radionuclide (FRN) chronometry. We find DF headwaters have a carbon stock of 66.2 Mg …

Digital Redlining In The Smart City: Artificial Intelligence, Housing Law, And Structural Urban Inequality, Spurthi Nrusimhadevara

Undergraduate Scholarship and Creative Works

Artificial intelligence is increasingly used in urban housing systems, where it shapes decisions about tenant screening, rent pricing, lending, zoning, and neighborhood investment. Although these tools are often promoted as efficient and impartial, they frequently rely on historical data that reflect racial, economic, and spatial inequality. As a result, AI systems can reproduce discriminatory outcomes even when protected characteristics are not directly used. This paper examines digital redlining in the smart city and argues that algorithmic housing tools mirror long standing structural inequities that raise significant concerns under fair housing and civil rights law. It evaluates how automated screening, predictive …

Summary Of Beaver And Iron Counties’ Water Conservation And Provisioning Strategies, Lisa Welsh, Joanna Endter-Wada, Burdette Barker, Bethany Neilson, Anna Mcentire, Melissa Stamp, Brian Steed

Reports

This report focuses on water conservation and provisioning strategies that both Beaver and Iron Counties are pursuing to help meet their citizens’ current and future water needs and to contribute to statewide water conservation efforts. It primarily relies on publicly available data from state, county, conservancy district, and city databases, plans, and documents. The purposes of this document are to provide regional context for understanding water use in Beaver and Iron Counties and to describe water conservation strategies that can influence the trajectories of their future water use. 

In both Beaver and Iron Counties, agriculture remains the primary user of …

Considerations For Assigned Water After Expiration Of The 2007 Guidelines, Kathryn Sorensen, Sarah Porter, Anne Castle, John Fleck, Eric Kuhn, Jack Schmidt, Katherine Tara

The Traveling Wilburys of the Colorado River

As Colorado River supplies and demands reach razor-thin margins, new tools to provide adaptive capacity will play a critical role in sustaining communities across the West. We must reduce our consumption of water, while finding ways to cushion the impact. One of the most innovative tools for doing this, developed over the last two decades, is “Assigned Water” - giving users the ability to store conserved water earmarked for their own future use. Originally developed as “Intentionally Created Surplus” in the 2007 Colorado River Interim Guidelines, Assigned Water has been revised and expanded through U.S. Mexico Treaty Minutes and as …