Digital Commons Network^™

The Honored Children Of Adam: A Muslim Reading Of Magnifica Humanitas In The Age Of Artificial Intelligence, Iqbal Akhtar

The Journal of Social Encounters

No abstract provided.

Partial Coalitions And Peacemaking As Metaphor, Julie Hawke

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas, The ‘Universal Destination Of Goods,’ And Social Movements, John Sniegocki

The Journal of Social Encounters

No abstract provided.

Leo’S Choices, Katherine G. Schmidt

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas And The Obsolescence Of Just War, Noreen Herzfeld

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas For The Marginalized, Nabila Feroz Bhatti

The Journal of Social Encounters

No abstract provided.

Humanity’S Grandeur In The Balance: Theological Reflections On Magnifica Humanitas, William L. Portier

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas: Not Just About Artificial Intelligence, John Ashworth

The Journal of Social Encounters

No abstract provided.

The Fridge And The Drone: A Reflection From The Perspective Of Palestinian Liberation Theology On Magnifica Humanitas, Omar Haramy

The Journal of Social Encounters

No abstract provided.

Artificial Intelligence And The Rediscovery Of The Human: An Islamic Reflection On Magnifica Humanitas, Mazhar Ali Bari, Biliana Popova

The Journal of Social Encounters

No abstract provided.

Riyadh Charter On Artificial Intelligence For The Islamic World, - Islamic World Educational, Scientific And Cultural Organization (Icesco), - Saudi Data And Artificial Intelligence Authority (Sdaia)

The Journal of Social Encounters

The Riyadh Charter on Artificial Intelligence for the Islamic World was launched by the Islamic World Educational, Scientific and Cultural Organization (ICESCO) and the Saudi Data and Artificial Intelligence Authority (SDAIA) in September 2024, in collaboration with the Saudi National Commission for Education, Culture, and Science, during the third Global AI Summit (GAIN Summit) in Riyadh.

The Charter has been widely recognized and endorsed by Islamic scholars and policymakers. During the 26th Session of the Council of the International Islamic Fiqh Academy, it was highlighted as a moral and strategic compass for AI technologies, addressing the limitations of existing international …

Preliminary Report - Evidence-Based Assessment Of Opportunities, Risks And Impacts Of Artificial Intelligence, - United Nations Independent International Scientific Panel On Ai

The Journal of Social Encounters

No abstract provided.

Encyclical Letter "Magnifica Humanitas", - Pope Leo Xiv

The Journal of Social Encounters

No abstract provided.

Introduction: Essays On Artificial Intelligence And Magnifica Humanitas, Ron Pagnucco

The Journal of Social Encounters

No abstract provided.

Palmnet: Confidence-Calibrated Edge-Cloud Ai For Field Diagnosis Of Date Palm Diseases, Muntadher Kareem, Raed Majeed

Karbala International Journal of Modern Science

Date palm (Phoenix dactylifera L.) is a cornerstone crop for Iraq and the wider MENA region, yet reliable in-field diagnosis of leaf disorders remains slow, labour-intensive, and constrained by a limited pool of agronomists. This paper presents PalmNet, a full-stack diagnostic system that classifies nine leaf conditions through a calibrated edge-cloud framework. The system is developed and evaluated on a public dataset of 3,089 field images spanning the nine classes, using a 70/15/15 stratified split. A ShuffleNetV2 student network, distilled from a ConvNeXt-Tiny teacher, is deployed on two complementary edge endpoints: a Raspberry Pi Zero 2 W field station …

Proactive Deep Q-Learning Approach For Anomaly Detection In Iot Idss, Hawraa A. Habeeb, Mehdi E. Manaa

Journal of Intelligent Informatics, Networking, and Cybersecurity

Breach rates and unparalleled vulnerabilities are a constant feature of the cyber landscape these days, and the increasing complexity of the proliferation of Internet of Things (IoT) nodes is to be expected. With these challenges, the conventional intrusion detection systems (IDS) are proven to be unable to deal with the extensive and varied data streams. Such systems can be fundamentally attributed to the classical nature of these systems, which are lacking in flexibility to analyze traffic in real-time and thus have no proactive capabilities of identifying patterns of unknown attacks. Considering these technical barriers, in this paper, an offensive-defensive system …

Ai And The Danger Of Ontological Confusion, Derek Schuurman

University Faculty Publications and Creative Works

There is much in Jonathan Barlow’s piece that resonates with me. I appreciated how he cites some seminal thinkers like Neil Postman, Jacques Ellul, E.F. Schumacher, and Ivan Illich as he frames his argument. In particular, I think Barlow is insightful in identifying the pitfall of “commensurability” when comparing humans and AI in terms of performance. I am reminded of the words of the famous computer scientist Edsgar Dijkstra, who suggested that the question as to whether machines can think is about as relevant as the question of whether “submarines can swim.”

Ai And The Environment: Solutions For Advancing Technology Safely, Kaitlynn Baker

Discovery Day - Daytona Beach

Since 2022, the world of Artificial Intelligence (AI) has boomed. AI went from a special and rare entity to a commonly used resource available to all through web sites, and phone apps. AI has benefitted everyday activities by making office, class, and personal tasks easier through grammar help, informational citations, and as someone to bounce ideas off of. Additionally, many companies have begun utilizing AI to improve customer service and experience, and train workers more efficiently, therefore, saving thousands of dollars. Despite the benefits humans reap from its use, AI has been harming our environment at growing rates. Data centers …

Assessing Attachment To Ai: Understanding The Theoretical Correlations And Consequences, Brianna Broderick

Discovery Day - Daytona Beach

Current research on Artificial Intelligence (AI) focuses on its capabilities and our understanding of it as an instrumental tool (i.e., utility completing tasks). However, as its ability to replicate natural language improves through both text and voice, an ever-growing number of users have turned to AI for emotional companionship. Concern grows as prior research on technology dependency suggests AI bonding may lead to less interaction with others and, in extreme circumstances, has already led to cases of suicide and divorce. Kasturiaratna & Hartanto (2025) developed the AI Attachment (AIA) scale, consisting of three factors, which include: emotional closeness (i.e., personal …

Quantifying Grain Size In Scanning Electron Microscopy Images, Katherine Hoffsetz

Discovery Day - Daytona Beach

This project explores advanced image analysis techniques to assess the microstructure of highly strained austenitic stainless steel. Utilizing Python imaging libraries such as scikit-image and OpenCV, we aim to extract precise measurements for grain size from scanning electron microscopy (SEM) images. These metrics will be examined against the computed grain sizes of the sample from electron backscatter diffraction measurements. By automating the extraction of grain size measurements from SEM images, this study contributes to steamlining the quality assurance/ quality control of industrially processed materials.

High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin

Discovery Day - Daytona Beach

Site exploration requires in-situ resource utilization when the physical properties of resources are unknown. Therefore, a generalizable object manipulation method is crucial for extraterrestrial environments. Existing studies develop reinforcement learning policies that enable interaction with objects, in which quadruped robots learn to reach commanded goals with one foot while balancing with the remaining legs. However, in these studies, goal-oriented task execution relies on high-level trajectories provided by human experts, which limits autonomous robotic operations. In this study, we propose a hierarchical DRL in which a high-level pedipulation policy outputs commands for a low-level reach policy, enabling autonomous, smooth and affordable …

Ai Race Between The Us And China, Kennedy Lyon-Lindersmith

Discovery Day - Daytona Beach

Technological leadership in AI and semiconductor manufacturing are both directly linked with military power and geopolitical influence. At the same time, the U.S. and China are currently defining the future of conflict in the cyber domain and are in strategic competition as China attempts to displace the U.S. as a global leader in AI. These factors contribute to an important national security threat that the U.S. is facing right now: An AI race between the U.S. and China, specifically regarding military cyber operations. This paper discusses some of the implications of a digital battlefield and analyzes international laws, international institutions, …

Geometry-Conditioned Adversarial Defense For Sar Automatic Target Recognition Via Regime-Specialist Classification Heads, Skyler Fabre

Discovery Day - Daytona Beach

This project, titled Geometry-Conditioned Adversarial Defense for SAR Automatic Target Recognition via Regime-Specialist Classification Heads, addresses the critical vulnerability of deep neural networks deployed in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems to adversarial perturbations. This is where imperceptible pixel-level modifications cause confident misclassification, posing serious risks in defense and aerospace applications. The objective is to develop and evaluate RegimeResNet, a geometry-conditioned classification architecture that exploits sensor metadata unique to SAR collection systems. Rather than treating all images uniformly, RegimeResNet partitions the SAR capture space into nine geometric regimes defined by depression angle and target azimuth angle extracted …

Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison

Discovery Day - Daytona Beach

Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …

Energy-Aware Bimodal Contact Detection For Leg Odometry, Emre Girgin

Discovery Day - Daytona Beach

Autonomous exploration of extraterrestrial environments using legged robots requires robust GNSS-free 3D state estimation. Standard leg odometry relies on Zero-Velocity Updates (ZUPT), which assume a grounded foot remains completely stationary. This assumption consistently fails on deformable granular terrain due to unobservable slippage, rapidly degrading state estimation. To mitigate this critical failure mode, we propose a dual contact-detection framework designed to robustly gate an Error-State Extended Kalman Filter (ESEKF) tracking pose, velocity, and IMU biases.   The architecture isolates physical load and kinematics by modeling contact detection as two independent parallel Hidden Markov Models (HMMs). The Load HMM processes Ground Reaction Forces, …

Motivational Outsourcing: Ai, Self-Determination, And The Changing Nature Of Adult Learning, Zoe Spanos

Discovery Day - Daytona Beach

Artificial intelligence (AI) is increasingly embedded into adult learning and higher education, serving not only as a support tool for cognitive aid but also as a system that can shape how learners regulate their motivation and engagement. This presentation examines how the use of AI in adult learning contexts may support or undermine self-determined motivation, drawing from Self-Determination Theory (SDT). It is a conceptual paper that draws on existing literature and theoretical analysis, examining AI reliance from minimal use to full automation across SDT's three basic psychological needs: autonomy, competence, and relatedness. Motivation is essential for learning, but the quality …

Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter

Discovery Day - Daytona Beach

Lightweight UAV-to-UAV Detection and Tracking for Advanced Air Mobility Applications addresses the significant challenge of reliable UAV-to-UAV detection on resource-constrained platforms, particularly within Advanced Air Mobility (AAM) environments where dense, low-altitude airspace requires robust detect-and-avoid capabilities. This work presents the development and experimental evaluation of a lightweight detection and tracking framework for autonomous detect-and-avoid applications. The approach is designed to support real-time onboard operation in multi-vehicle environments characteristic of emerging AAM systems. The proposed framework integrates optical and LiDAR sensing with a low-complexity machine learning decision-support layer that reduces false detections without replacing the underlying control-oriented detection pipeline. This design …

Ai-Driven Predictive Analysis Of Airline Profitability Under Macroeconomic And Sustainable Aviation Fuels, Shivika Singh

Discovery Day - Daytona Beach

This study presents an AI-enhanced predictive model to assess airline profitability under the combined influence of macroeconomic trends and the adoption of sustainable aviation fuel (SAF). By including economic indicators such as GDP growth, inflation rates, and fuel price volatility with airline operational data, including ticket prices and fuel costs, the model simulates profitability across multiple carriers. Scenario-based analyses, encompassing optimistic, moderate, and pessimistic projections, illustrate different financial sensitivities between low-cost and legacy airlines.

Determinants And Invertibility In Finite Modular Systems, Osasu Omobude

Discovery Day - Daytona Beach

This project investigates determinants and matrix invertibility in finite modular systems, focusing on matrices over Zn. Using the Hill cipher as context, it examines the algebraic conditions under which a matrix is invertible in modular arithmetic. In particular, the project studies how the determinant determines invertibility, showing that a matrix over Zn is invertible if and only if its determinant is coprime with n.   The project further compares invertibility over the real numbers with invertibility over modular systems, highlighting the distinction between prime moduli Zp and composite moduli. In the prime case, matrices behave similarly to those over fields, where …

Designing Process-Focused Feedback For College Writers Using Genai, Beata Blood, Maissane Aik, Zoey Zaldivar

Discovery Day - Daytona Beach

As generative AI tools like ChatGPT become more common in higher education, writing instructors face the challenge of guiding students toward effective and ethical use, particularly in asynchronous environments where immediate feedback is limited. This presentation reports on an exploratory study that addresses this challenge by shifting attention from AI’s outputs to students’ moment-by-moment writing processes. Grounded in applied linguistics approaches to writing research and process-tracing methods, the project employed case studies with both expert and novice users of GenAI. Expert participants, including academics and industry professionals, completed writing tasks while integrating AI into their workflows. Their sessions were recorded …