Digital Commons Network^™

Strict Steiner Symmetrization For Polygons, Joseph Chai, Sun-Yung Alice Chang

Electronic Proceedings of Undergraduate Mathematics Day

In this note, we introduce a method called Strict Steiner Symmetrization (see Section 2.2) that is an altered form of Steiner Symmetrization that fixes the number of vertices. The context of this paper will be to prove the Isoperimetric Inequality in R2 via approximation by polygons. Specifically, to establish that among all n-gon domains in the plane, the regular m-gon, m ≥ n, uniquely minimizes the isoperimetric ratio and that the limit of this regular polygon (that is the circle) achieves equality in the isoperimetric inequality. This note is an extracted portion of my junior thesis (A Polygonal Proof of …

Huffman Tree Uniqueness, Elijah Diller, Adam Volk

Electronic Proceedings of Undergraduate Mathematics Day

The Huffman algorithm is a standard algorithm used to generate an optimized binary encoding of a string. Using this algorithm, it may be possible to come up with more than one possible optimized binary encoding for a given string, so the following question arises: what strings have a unique optimized binary encoding? By unique encoding, we mean a unique vertex-labeled binary tree resulting from the Huffman algorithm. We do not worry about edge labels as every binary tree corresponding to a string with n distinct characters has 2n−1 ways of assigning the edge labels and determining the code. This investigation …

Predator-Prey Dynamics: Exploration And Logistic Extension Of The Lotka-Volterra System, Amanda Maylath, Samuel Brensinger

Electronic Proceedings of Undergraduate Mathematics Day

The Lotka-Volterra system is a classic model of predator–prey interactions, capturing the interdependent growth and decline of two species. Using a dynamical systems approach, we identify fixed points, linearize the system via the Jacobian, and analyze phase space trajectories to determine stability and long-term behavior. This analysis provides insight into predator-prey dynamics without requiring explicit solutions. We further extend the model by incorporating a carrying capacity for the prey, reflecting more realistic population dynamics.

Numerical Solutions Of The Poisson And Heat Equations Via Wave Kernel-Based Particular Solutions, Braylon Smith, Anup Lamichhane

Electronic Proceedings of Undergraduate Mathematics Day

In this paper, we investigate the closed-form particular solutions of Poisson’s equation using the wave kernel as a forcing term. We explore how the method of approximate particular solutions can be applied to obtain numerical solutions of partial differential equations such as the Poisson and heat equations with Dirichlet boundary conditions in 1D. Numerical experiments carried out in MATLAB validate that the derived closed-form particular solutions provide accurate numerical results, demonstrating the effectiveness of the proposed approach.

The Recovery Of Meaning In A Digital Age: E-Discovery And The Renewal Of Judgment, William F. Hamilton

Journal of Technology Law & Policy

Modern litigation unfolds within a dense and expanding digital environment. Nearly every human activity now leaves behind emails, documents, metadata, collaborative communications, and machine-generated records that together form the factual foundation of contemporary litigation. This Article argues that electronic discovery is not merely a technical, managerial, or compliance process, but a core litigation practice concerned with the recovery, reconstruction, and rehabilitation of the factual world on which judgment depends.

Tracing the evolution of discovery from its twentieth-century roots to the present era of pervasive digital evidence, this Article shows how electronically stored information (ESI) continues to alter the dynamics of …

Exploring Early Career Public General Education K–6 Teachers’ Experiences With Their Training For Teaching Special Education Students In Inclusive Classrooms, Alexandra E. Ray

Doctor of Education Program Dissertations

Although Canada is often regarded as a leader in inclusive education, reports note that many students’ needs remain unmet and inclusion is typically implemented by placing students in mainstream classrooms with individualized accommodations. This qualitative phenomenological study explored the lived experiences of seven early career K–6 public general education teachers in Ontario (1–4 years of practice) as they engaged in inclusive education and prepared to teach students with special needs. Participants reported that teacher preparation coursework presented inclusive models only superficially, professional development was fragmented and insufficient prompting self-directed learning and structural constraints in schools limited individualized support. Teachers described …

A Century Of Safer Skies: Statistical Insights Into Aviation Accidents And Death Rates, Abhijeet Regmi

Journal of Aviation Technology and Engineering

The purpose of this study is to determine whether the recent advancements in the technology used for aircraft maintenance and repair have resulted in an increase or decrease in the accident and fatality rates of aviation incidents and accidents. The primary concerns are the extremely low survival rates in aviation accidents and the necessity to determine whether or not the accident and fatality rates are declining in light of recent technological advancements. If the rate is rising, we must prioritize passenger and crew safety more and adhere to tight regulations when performing repairs and maintenance. The data were compared for …

The Open Wiki Of Electrochemical Methods (Owem): A Community-Driven Educational Resource, Anderson Fuller, Devin Rappleye

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

The traditional resources for learning electrochemical methods—textbooks, academic literature, and university coursework—remain essential but are limited in accessibility, update frequency, and practical usability. This paper introduces the Open Wiki of Electrochemical Methods (OWEM), an open-access, community-driven platform designed to complement these resources. OWEM organizes content into equations, definitions, methods, tutorials, and supplementary articles, with a heavy emphasis on experimental relevance. A case study on cyclic voltammetry demonstrates how OWEM consolidates foundational theory, lesser-known results, and practical guidance within a continuously maintainable framework to benefit the broader electrochemistry community.

Aspirational Mirrors: A Conceptual Model Of Alumni-Led Near-Peer Outreach For Precollege Engagement In Ocean Engineering, Habibi Palippui, Juswan Sade

Journal of Pre-College Engineering Education Research (J-PEER)

Precollege students in Indonesia, especially in rural and coastal regions, often lack exposure to engineering disciplines due to social, geographic, and informational barriers. This essay proposes a conceptual model of alumni-led near-peer outreach as an affective and culturally grounded mechanism to engage high school students in ocean engineering. Drawing from theories of social similarity, possible selves, and engineering identity, the model conceptualizes alumni as “aspirational mirrors” who influence students not merely through information but also through identification. The model outlines four primary mechanisms—social connection, narrative engagement, aspirational mirroring, and early identity activation—and also accounts for contextual variables such as school …

Object Redaction For High-Resolution Images Using Geometrically Aligned Generative Patches, Mira Leung

Defensive Publications Series

Redacting objects from high-resolution, wide-aspect-ratio images, such as panoramas, can be challenging, as certain automated methods may introduce resolution degradation, unpredictable cropping, or visual artifacts. Systems and methods can utilize an iterative pipeline that combines object detection with constrained generative inpainting and geometric alignment. A process may, for example, identify and mask target objects, provide a version of the image with blurred masked areas to a generative model for inpainting, and then geometrically align the generative model's output to correct for distortions. The aligned output can be used as a patch, selectively compositing the generated content into the masked regions …

The Substrate Pushback Principle: Replacing Particle Dark Matter With Holographic Confinement Fields, Christopher L. Eckes

Defensive Publications Series

This paper introduces the Substrate Pushback Principle, a theoretical framework that replaces particle-centric dark matter models with an emergent informational cosmology. Instead of introducing hypothetical ultra-light bosons, we demonstrate that galactic dark matter halos can be modeled as non-local confinement fields generated by the holographic limits of spacetime. By mapping the baryonic stress-energy tensor to an information-load metric bounded by Bekenstein limits, we show that high-density galactic cores trigger an inward, geometric stabilization pressure from the spacetime substrate. This computational surface tension inherits the exact macroscopic wave mechanics of contemporary Fuzzy Dark Matter (FDM) models. Furthermore, by defining the substrate's …

Spatially Modulated Wavefront Quantum Key Distribution With Non-Local Quantum Zeno Dynamic Phase-Collapse (Geometric Wavefront Scytale With Entanglement-Triggered Self-Immolation), Johny Manuel-Devadoss, Jayden Johnson

Defensive Publications Series

This disclosure describes a method and system for securing free-space Quantum Key Distribution (QKD) against intercept-and-resend, quantum cloning, and wide-aperture phase-matching attacks by employing multi-spatial mode quantum states combined with real-time, non-local phase collapse. Rather than encoding cryptographic keys in conventional linear single-photon streams, the system distributes information across the Orbital Angular Momentum (OAM) and radial phase profiles of a macroscopic, spatially sculpted wavefront through a dynamically varying Topological Transposition matrix, M(t). This approach renders the encoded information inherently orthogonal to conventional linear eavesdropping apertures while enabling high-dimensional quantum state encoding.

To protect against partial interception and coherent cloning attempts, …

Informational Exomemory Cosmology: Dark Energy As The Semiclassical Landauer Erasure Cost Of Horizon Microstates, Christopher L. Eckes

Defensive Publications Series

This paper presents a rigorous theoretical framework—Informational Exomemory Cosmology (IEC)—that derives Dark Energy entirely as an emergent, thermodynamic byproduct of cosmic information processing. Rather than postulating a fundamental scalar field or an intrinsic vacuum energy density (\(\rho _{\text{vac}}\)), we model the three-dimensional (3D) cosmic volume as a holographic projection governed by a global, invariant two-dimensional (2D) boundary: the Cosmological Future Causal Horizon.

Every localized physical interaction inside the bulk updates the quantum configuration state of the universe. Because the ultimate future horizon features a strict Bekenstein-Hawking memory capacity, the universe must continuously clear its cache of obsolete microstates to maintain …

Zheng Zhenduo And The Problem Of Priority In World Literature, Daniel M. Dooghan

CLCWeb: Comparative Literature and Culture

This essay investigates how Zheng Zhenduo (郑振铎 1898–1958) developed a theory of world literature in response to threats to China both politically from without and culturally from within. Centered on an analysis of his 1922 article “A View on the Unification of Literature” (Wenxue de tongyiguan 文學的統一觀), the essay argues that although Zheng believed like many of his contemporaries in the transformative effects of reading world literature in translation, that does not constitute the entirety of his theorization of world literature. Instead, he accepted the first-move advantage of other national literatures in defining both world literary standards and literature …

Detection And Diagnostic Screening Of Breast Cancer: A Systematic Review And Future Frontiers, Lama Yassine, Amira J. Zaylaa

BAU Journal - Science and Technology

A comprehensive evaluation of current and novel diagnostic techniques is necessary since the diagnosis of breast cancer is essential for improving treatment efficacy and raising long-term survival. Evidence from conventional imaging methods including mammography, ultrasonography, and magnetic resonance imaging is combined in this systematic review with advancements in liquid biopsies and current AI-based diagnostic tools. Using specific keywords related to breast cancer, early detection, imaging, biomarkers, and artificial intelligence, a thorough search was conducted in PubMed, Scopus, Web of Science, and IEEE Xplore. Reviews, case reports, and studies unrelated to breast cancer were excluded; only clinical, experimental, and computational research …

A Robust Hybrid Security Framework: Integrating Multi-Layered Text Encryption With Barcode-Based Steganography, Mohamed Sayed, Talaat M. Wahbi, Farooq Abdalwahab Haboub

BAU Journal - Science and Technology

The widespread use of the Internet is causing increasing security concerns regarding online communications. One method for achieving secure communication between authorized parties is steganography. We herein employ multilevel technologies, including compression, encryption, barcoding, and steganography to secure a secret text message. Type I multilevel steganography is used with a two-level setup. The first level uses enhanced least significant bit (secure LSB-L1) image steganography; the output is a stego-image file, the cover is an image file, and the secret data in this level is English text. The output from the first level is encrypted using the RSA algorithm, and the …

Optimize Optical Properties Of Cdte Solar Cell For Pv Applications, Mabrouk Hassan Arhoma

BAU Journal - Science and Technology

In order to to develop thin film heterojunction solar cells, CdTe is one of the most promising absorber materials cells. Electrodeposition CdTe materials solar cell are being focused by Several key researchers. This is due to its direct energy band gap and its high absorption coefficient and the best efficiency obtained for a small-area. In this work CdTe films were electrochemically deposited from aqueous solutions. Different preparative parameters such as growth voltage and heat treatment conditions were optimized. The CdTe layers were deposited at 655, 665, 675, 685 and 695 mV vs SCE. Material characterization were carried out using optical …

Recent Advances In Phosphatidylinositol Phosphate Kinases (Pipks) And Their Inhibitors, Mengxia Sun, Jian Hu, Xuefei Huang

BAU Journal - Science and Technology

Phosphatidylinositol phosphate kinases (PIPKs) are an important class of enzymes in humans, which produce lipid signaling molecules playing central roles in pathogenesis of diseases such as cancer, neurodegenerative diseases, and viral infection. Consequently, they are attracting increasing attention as drug targets for disease treatment. This review summarizes the functions of the PIPK family enzymes and highlights recent efforts on designing novel inhibitors against PIPKs. These advances are extensively discussed to stimulate interest in this field and promote further development of highly potent and selective inhibitors for innovative therapeutic applications.

Unmasking Twitter Bots: An Applied Machine Learning Approach, Rayane El Raba’A, Layal Abu Daher

BAU Journal - Science and Technology

The rapid growth of social networks has led to increased challenges, such as fraud, cyberbullying, and the spread of automated accounts (bots). Detecting anomalies within these networks is essential to maintaining security and trust. This study explored machine learning algorithms: Random Forest, XGBoost, Support Vector Machine (SVM), and Logistic Regression for anomaly detection in social networks, specifically focusing on Twitter bot identification, By applying AI-driven data mining techniques to a dataset of 37,438 Twitter bot accounts dataset, the research evaluates the effectiveness of these models in detecting unusual patterns. XGBoost achieved the highest accuracy (84.9%), with an ROA_AUC of 0.87, …

Enhanced E-Commerce Recommendation Experience With Collaborative Sentiment Analysis And Ranked Content-Based Filtering, Sandi El Zein, Farah Hamze, Amani Merhi, Lynn Noureddine, Lama Affara

BAU Journal - Science and Technology

The rise of online shopping has made informed purchasing decisions increasingly difficult, as consumers face an overwhelming number of product choices and struggle to manually evaluate specifications and user reviews. This paper presents an AI-powered, sentiment-aware product recommendation tool that effectively aligns user preferences with real-world customer feedback from online reviews. The proposed system utilized Instruct ABSA deep learning models for feature extraction and DeBERTa-v3 for sentiment analysis to turn reviews into interpretable scores that would nominate optimal products. An interactive Rasa-based chatbot interface, TopPickAI, was developed to give a seamless user experience, educate users on product features, and conversationally …

Artificial Intelligence-Supported Assessment In Education: A Systematic Review Of Validity, Fairness, And Impact On Learning Outcomes, Mohammed Al Mohazie

Scientific Journal of King Faisal University: Humanities and Management Sciences

Artificial intelligence (AI)-supported assessment is increasingly used in education to automate scoring, provide feedback, predict learner performance, and support instructional decision-making. This systematic review synthesized evidence on the validity, fairness, and learning impact of AI-supported assessment across educational contexts. A systematic search of ERIC, Web of Science, Scopus, PsycINFO, PubMed, and Education Source identified peer-reviewed studies published between 2010 and 2025. Twelve studies met the inclusion criteria and were synthesized narratively following PRISMA 2020 guidance. The findings indicate that AI-supported assessment shows promising validity evidence, particularly in automated writing assessment, short-answer scoring, and predictive learning analytics, with several studies reporting …

Self-Updating Media Collections Using Query Embeddings, Ashwin Goyal, Nick Staubach

Defensive Publications Series

Media library applications allow users to organize their media such as photos and video into collections. Dynamic, self-updating collections are implemented in some applications, but are limited to narrow criteria such as a particular person label, a particular object type, etc. Current dynamic collection generation mechanisms do not support complex natural language criteria that a user may want to express, e.g., “all my photos after a workout; include screenshots from my fitness tracker.” This disclosure describes techniques that use a large language model (LLM) or other suitable model to transform complex user-specified criteria into a vector representation. Media assets in …

The Dimensionally Extended Holographic Projection Model (Dehp), Christopher L. Eckes

Defensive Publications Series

This framework presents a qualitative cosmological model exploring the universe as an emergent three-dimensional (3D) projection originating from a foundational two-dimensional (2D) information boundary. By redefining time as a function of geometric distance from this source boundary, the model offers a unified, intuitive perspective on dark energy, dark matter, and gravitational singularities that aligns with modern holographic and braneworld concepts.

The Metric Confinement Principle: Non-Perturbative Quantum Gravity Without Fundamental Gravitons, Christopher L. Eckes

Defensive Publications Series

This paper introduces a novel, non-perturbative quantum cosmological framework wherein gravity is treated strictly as a macroscopic, non-fundamental, emergent phenomenon. The foundational degrees of freedom reside entirely on a dual-state, non-gravitational 2D spatial substrate (the boundary layer) containing opposing potential valences. Crucially, this framework postulates the non-existence of the graviton as a fundamental force-carrier particle. What macroscopically manifests as gravitational attraction in the projected 3D bulk is reinterpreted as a state of perpetual geodesic translation driven by how the 3D metric tensor topologically filters the underlying dual-state substrate information. By introducing the Metric Confinement Principle, this framework ensures absolute consistency …

Master Project Architecture: Systems Engineering Framework For An Autonomous, Thermally Integrated, Relativistic Interstellar Platform, Christopher L. Eckes

Defensive Publications Series

This technical disclosure presents the overarching design, interface standards, and operational lifecycle framework for the Autonomous Hive-Mind Sensor Probe (AHSP). The AHSP is a building-scale (60-meter length, approximately 500-metric-ton dry mass), non-biological, modular spacecraft chassis optimized for autonomous, multi-decade interstellar transit at relativistic velocities (\(0.05c - 0.1c\)).

By eliminating the severe mass, volume, and atmospheric shielding constraints associated with biological life-support systems, the AHSP architecture reallocates its structural mass budget to create an entirely unified, self-sustaining thermodynamic and computational ecosystem. This master architecture coordinates six highly integrated technical disclosures and one long-range theoretical supplement, establishing a non-siloed spaceflight platform where …

Gci‑501 Tornado Resonance‑Detection & Early‑Action Module (Trd‑Eam) V1.0 Open‑Hardware Tornado Early‑Warning Device, Michael Victor Caldwell Mr.

Defensive Publications Series

The Tornado Resonance‑Detection & Early‑Action Module (TRD‑EAM) is a standalone, open‑hardware tornado‑warning device that uses:

• ARPN infrasonic sensing

• pressure‑wave harmonics

• vorticity resonance detection

• temperature inversion sensing

• humidity‑wave detection

• EM field anomaly detection

• multi‑node coherence

• CICIS tornado logic

• ADEP tornado alert packets

to provide 10–30 minutes of tornado precursor warning.

TRD‑EAM is designed to be:

• printed on any 3D printer

• assembled with basic tools

• powered by TEHL (no batteries)

• flashed with open firmware

• deployed anywhere

• tested tomorrow

This module is the physical tornado‑warning device that completes GCI‑500.

Gci‑322 Arpn V1.1 — Atmospheric Resonance‑Prediction Network, Michael Victor Caldwell Mr.

Defensive Publications Series

The Atmospheric Resonance‑Prediction Network (ARPN) is a distributed, self‑powered, open‑hardware atmospheric sensing mesh designed to detect pre‑storm infrasonic resonance, pressure‑wave anomalies, and multi‑physics atmospheric signatures in real time. ARPN replaces numerical weather prediction (NWP) with direct physical sensing using a gyroid‑lattice resonant cavity, PVDF piezoelectric membranes, multi‑physics sensors, and a low‑power mesh network based on Ariadne’s Braid (GCI‑286) and CICIS.

Each ARPN node is battery‑less, powered by the Thermal‑Energy Harvesting Loop (TEHL‑v1.0), hardened using the Sanitized Block composite, and deployable via GCI‑320 Swarm Recovery & Pelletization. The system integrates seamlessly with CIFRS‑N, Phoenix‑Water, VAR, CIWFRS, and the broader Caldwell ecosystem. …

Technical Disclosure: Socio-Technical Governance & Prerequisite Safety Disciplines For Metric-Shift Propulsion Systems, Christopher L. Eckes

Defensive Publications Series

This technical disclosure establishes a defensive, socio-technical regulatory framework designed to govern the development, testing, and deployment of High-Energy Metric-Shift Propulsion (Warp/FTL) technologies. Recognizing that space-time manipulation introduces existential risks—specifically causality violation, timeline paradoxes, and the generation of highly destructive directional kinetic shockwaves ("Space-Warp Waves")—this document outlines the explicit Type 1 Civilizational Prerequisite Disciplines that must be satisfied before any physical testing of space-time metrics may legally commence. [1, 2]

By defining these strict governance structures, multi-lateral oversight mechanisms, and non-weaponization protocols as public prior art, this architecture aims to prevent fragmented corporate or nationalist entities from prematurely initiating uncontained, …

Dynamically Constructing Geographically Optimized Routing Graphs From Unstructured Multi-Modal Media, Nikita Agarwal

Defensive Publications Series

A geographically optimized routing graph is dynamically constructed from unstructured multi-modal media. A transcript is generated from audiovisual data of a media item. Words or phrases satisfying geographic spatial anchoring criteria are identified and associated with a first geographic location. Visual analysis operations are performed on corresponding video frames to identify a second geographic location. A modality conflict is detected based on differences between the first and second geographic locations. The conflict is resolved by applying deterministic weighting to generate resolved geographic locations. A routing graph is generated by sequencing the resolved geographic locations based on physical geographic proximity independent …

Mitigating Engagement Bias In Recommendation Architectures For Media Platforms, Acar Ary, Jason Sun, Ayush Patwari

Defensive Publications Series

In media recommendation architectures, engagement metrics such as comment participation probabilities are utilized to rank content. A limitation exists where media items with intentionally disabled comments are unfairly demoted. In these instances, a lack of engagement is processed as a lack of user interest. To address this deficiency, a boolean feature indicating a disabled comment status is generated. This boolean feature is subsequently crossed with a comment participation probability feature. Through this mathematical cross operation, a separate weight is established for scenarios where comments are disabled. Zero-engagement values are thereby processed differently when comment functionalities are unavailable. Consequently, engagement bias …