Digital Commons Network^™

Vabr‑V2.0 — Vortex–Acoustic Bio‑Refinery, Michael Victor Caldwell Mr.

Defensive Publications Series

The Vortex–Acoustic Bio‑Refinery (VABR‑v2.0) is a conceptual modular system designed to convert municipal sewage sludge into biodiesel using vortex‑based solids concentration, tri‑band acoustic cavitation, dual‑stage heterogeneous catalysis, and high‑G centripetal coalescence separation. The system operates at near‑ambient pressure and is intended for decentralized deployment at wastewater treatment facilities. VABR‑v2.0 includes enhanced safety systems, catalyst‑recovery mechanisms, closed‑loop water reuse, and modular snap‑in

The Metric Field And Its Primitives, Steven Kirkland

Defensive Publications Series

The Metric Field and Its Primitives is the formal-mathematics layer of a research project whose popular-science companion, Inners Guide to the Hyper Loop, ships the story. This volume ships the mathematics: definitions, theorems, proofs, falsifier ladders, and the algebra the framework reads across substrates from atomic spectra to slime moulds to the cosmic substrate.

The framework. A candidate fundamental framing under Metric Field Ontology (MFO) commitments. The conventional readings of physics — general relativity, quantum field theory, the Standard Model, ΛCDM cosmology, M-theory's eleven-dimensional supergravity — are preserved at the mathematical level. What is shifted is the ontological framing: …

Computer Aided Field Investigation (Cafi): A Provenance-First Architecture For Real-Time Msme Credit Decisioning In India, Murali Krishnan

Defensive Publications Series

Computer Aided Field Investigation (CAFI) is a provenance-first architecture for real-time MSME credit decisioning in India, replacing the photographs-and-narrative output of conventional field visits with a hash-chained, tablet-captured, audit-defensible evidence graph. The five-layer architecture combines geo-fenced tablet field capture, DPDP-compliant consent-bound media acquisition, an append-only provenance data model in which every credit-decision fact links to immutable source artifacts, a deterministic real-time triangulation engine cross-validating borrower declarations against Goods and Services Tax (GST) returns and Account Aggregator (AA) bank statement data, a quality-assurance anomaly layer detecting photo perceptual hash collisions, GPS clustering, visit duration outliers, and field-officer response patterns, and a …

Offline‑First Transaction Buffering With Merkle‑Root Synchronization For Mobile Api Requests, Harshwardhan Tripathi

Defensive Publications Series

The present disclosure relates to a method and a system for synchronizing offline-generated Application Programming Interface (API) requests using Merkle roots between a client device and a server. The present disclosure suggests buffering one or more API requests in a persistent local storage queue responsive to unavailability of network connectivity. Thereafter, the present disclosure suggests generating, for each buffered API request, a cryptographic leaf hash based on a canonical representation of the corresponding API request. Upon generating the cryptographic leaf hash, the present disclosure suggests constructing, by the client device, a Merkle tree including the cryptographic leaf hashes as leaf …

Water System #30 Solar‑Thermal, Vortex‑Enhanced Desalination System, Michael Victor Caldwell Mr.

Defensive Publications Series

Water System #30 solar‑thermal, vortex‑enhanced desalination system designed for off‑grid, humanitarian, and disaster‑response water purification. The system uses concentrated solar heat, a cyclonic evaporation chamber, and a multi‑stage contaminant separation process to convert seawater or high‑TDS brackish water into potable water without membranes, high‑pressure pumps, or consumables.

To ensure stable operation under variable sunlight and high‑salinity conditions, the system integrates:

• A phase‑change thermal flywheel to buffer solar fluctuations

• A passive ultrasonic scale‑prevention ring to eliminate mineral buildup

• A hydrophobic gyroid demister to prevent salt‑mist carryover

• A high‑conductivity polymer condenser wrap to increase distillate yield

This disclosure provides a complete, manufacturable, …

Ocular Neuro‑Restoration System (Onrs): A Non‑Invasive Ultrasound‑Driven Drug Delivery & Biomarker Platform, Michael Victor Caldwell Mr.

Defensive Publications Series

The Ocular Neuro‑Restoration System (ONRS) is a non‑invasive, wearable ultrasound platform designed to deliver neuroprotective and vascular‑restorative therapeutics to the retina, optic nerve head, and posterior eye without injections. The system uses low‑intensity focused ultrasound (LIFU), vortex‑phase acoustic fields, microbubble‑enhanced sonoporation, and microfluidic tear‑exchange diagnostics to overcome the anatomical barriers that normally block ocular drug delivery.

A CMUT phased array generates controlled acoustic streaming and reversible tight‑junction modulation, enabling 10–50× enhanced penetration of small molecules and biologics, consistent with published evidence that ultrasound increases ocular permeability and drug transport .

A PDMS microfluidic gel‑refresh system maintains uniform coupling and eliminates …

Agentic System For Real-Time Social Media Intelligence Synthesis And Strategic Briefing Generation, Kevin Babu

Defensive Publications Series

A technique is proposed for real-time social media intelligence synthesis and strategic briefing generation. Engagement metrics associated with social media content associated with a user are obtained. An artificial intelligence (AI) agent configured to derive data for a social media briefing based on the engagement metrics is instantiated. The AI agent is caused to calculate an engagement velocity of the social media content based on a rate of change of the engagement metrics over a time period. The AI agent is caused to to determine a brand sentiment forecast and a viral breakout point based on the engagement velocity and …

System And Method For Automated Testing Gap Categorization And Codebase Vulnerability Localization, Aman Singh

Defensive Publications Series

A system related to automated testing gap categorization and codebase vulnerability localization in large-scale distributed computing environments. The system may receive an incident record containing unstructured text and identifiers pointing to external systems, obtain content from the external systems based on the identifiers, and aggregate the content into a unified context payload. The system may generate a fingerprint data structure based on the unified context payload and a versioned analysis prompt to determine whether AI model analysis is needed. The system may perform multi-stage AI analysis including identifying where a supervised analysis system indicated a testing gap, classifying the type …

Virtual/Augmented Reality Paired Driving Using Digital Key Enabled Device For Pairing/Authentication, Nick Miller, Emelie Jess Ashdown

Defensive Publications Series

This disclosure describes a system for safely driving a vehicle from a remote location using an extended reality (XR) headset, virtual reality (VR) goggles, augmented reality (AR) glasses, or a hardware simulator. Existing remote driving, tele-operation, or remote vehicle control methods often rely on simple passwords, which can be less secure. This new technique uses a high-security digital car key stored on a physical device—such as a smartphone, an object tracking tag, or a small hardware “puck”—that should be placed inside the vehicle before it can be operated remotely. This creates a physical requirement that ensures only someone with authorized …

Graph Similarity-Based Selection Of Long Chain-Of-Thought Trajectories For Model Training, Ali Payani, Ramana Kompella

Defensive Publications Series

Recent research has demonstrated that selecting a carefully curated subset of long chain-of-thought (COT) trajectories can significantly improve the performance of reasoning large language models (LLMs) in mathematical question and answer tasks.  Proposed herein are techniques to extract long COT reasoning traces, which can be useful for fine-tuning artificial intelligence (AI) models, such as LLMs.

Gaussian-Weighted K-Nearest Distribution Point Mapping For Smooth Probability Estimation, Ania Kacewicz, Jud Dagnall

Defensive Publications Series

Proposed herein is a method to map compressed data representations to smooth probability distributions by distributing each data point's weight across its k-nearest distribution bins using Gaussian decay, creating a natural exponential falloff where closer bins receive exponentially more weight than distant bins. Unlike traditional methods that either create spiky distributions (nearest-neighbor-only) or over-smooth local features (global kernel density estimation), a bounded Gaussian approach, as proposed herein, confines smoothing to local neighborhoods while maintaining smoothness within those regions. The algorithm includes circular distance support for temporal data (ensuring hour 23 is treated as 1 hour from hour 0, not 23 …

Dynamic, Secure, And Device Identity-Based Dynamic Host Configuration Protocol (Dhcp) Fixed Internet Protocol (Ip) Assignment For Clients, Sajid Sayedrasul Inamdar, Sarat C Pollakattu, Marc Faggion

Defensive Publications Series

Dynamic Host Configuration Protocol (DHCP) reservations are essential for ensuring consistent Internet Protocol (IP) addressing for critical devices, but conventional IP assignment approaches rely on manual mappings that are complex, error-prone, and difficult to scale.  Moreover, conventional IP assignment approaches introduce management overhead, risk of IP conflicts, and lack a mechanism for dynamically and securely assigning fixed IP addresses to DHCP clients.  To address these limitations, the techniques presented herein implement a dynamic, secure, and centralized DHCP reservation solution using a Network Access Control (NAC) platform.  The techniques presented herein enhance the Remote Authentication Dial-In User Service (RADIUS) protocol to …

Optimized, Context-Aware Large Language Model (Llm) Architecture For Artificial Intelligence (Ai)-Native Sixth-Generation (6g) Networks, Swapnil Barai, Ravi Shekhar, Dishant Parikh, Gaurav Kumar Rungta

Defensive Publications Series

The evolution toward sixth-generation (6G) networks introduces agentic communication, in which autonomous software agents interact and execute actions based on real-time environmental data. Large language models (LLMs) provide reasoning capability for such agents, but deploying an individual LLM for each agent can be operationally and economically infeasible. This disclosure presents a consolidated, context-aware LLM architecture that centralizes LLM resources within a 6G core and logically separates the resources into control plane (CP) and user plane (UP) instances. Using a shared resource model and a context-tagging mechanism based on device type, radio access technology (RAT), and function type, the architecture supports …

Edge Artificial Intelligence (Ai) Guardian: Ai-Powered Predictive And Self-Healing For Bidirectional Forwarding Detection (Bfd) And Internet Protocol Security (Ipsec) Tunnels In Software-Defined Wide Area Network (Sd-Wan), Krushnarajendra H R

Defensive Publications Series

Current Software-Defined Wide Area Network (SD-WAN) solutions are reactive and centralized, lacking the ability to predict and autonomously heal tunnel degradations before outages occur.  To address these limitations, the techniques presented herein implement Edge AI Guardian, a system configured to deploy a lightweight on-device Artificial Intelligence (AI) agent on edge routers to predict tunnel failures in real time, autonomously perform local self-healing actions, and generate natural-language Generative Artificial Intelligence (GenAI)-based root cause summaries without requiring centralized network management connectivity.

Energy-Efficient Artificial Intelligence Inference Through Task Decomposition And Heterogeneous Parallel Execution With Critical Path Trade-Off Analysis, Utkarsh Bhardwaj, Shivank Awasthi

Defensive Publications Series

A system performs task decomposition for the energy-aware parallel execution of Artificial Intelligence (AI) inference across heterogeneous computing resources. The technology decomposes a complex prompt into atomic sub-tasks and maps them into a Directed Acyclic Graph (DAG) to define dependencies. Each sub-task is then classified by its computational nature and routed to hardware, such as a local central processing unit (CPU), neural processing unit (NPU), or cloud server, based on physical energy and carbon cost models. The system analyzes the DAG to identify the critical path, routing these tasks to higher-performance resources to reduce latency while assigning non-critical tasks to …

Multi-Agent Safety Architecture Using Geometric Projections And Cryptographic Egress Control, Neel Mohbe

Defensive Publications Series

Decentralized, multi-agent artificial intelligence (AI) systems can introduce structural vulnerabilities, such as emergent toxicity and alignment erosion, that existing safety paradigms may not fully address. A multi-agent safety architecture is described that can treat safety as a geometric and cryptographic property of a network's communication and consensus fabric. A method can involve mathematically defining a safety concept as a subspace within a model’s activation manifold to create an orthogonal projection operator. This operator may filter agent states to help mitigate harmful emergent content, a cryptographic egress layer with low-rank proofs can be used to verify the filter's application before messages …

Integrated Passive Design Strategies For Enhancing Energy Performance Of Hotel Buildings In Hot-Arid Climates: A Simulation-Based Study, Esraa Ebrahiem Abu-Elenain

HBRC Journal

Sustainable architectural design strategies offer effective solutions for enhancing energy efficiency and reducing operational costs in energy-intensive buildings, such as hotels in hot-arid climates. However, limited research has addressed the integrated application of multiple passive design strategies within hotel buildings using a unified simulation-based framework. This study investigates the combined application of wind catchers (Malqaf), adaptive mashrabiya shading systems, and high-performance glazing on a proposed hotel floor in Ras Sedr, Egypt. The design was modeled in Autodesk Revit and analyzed through dynamic simulation using EnergyPlus. A comparative approach was adopted, including a baseline scenario and an improved design scenario. The …

Enhancing Social Activity Through Climate-Adaptive Design In Hot-Humid Campus Open-Spaces: A Case Study Of The University Of Basrah In Iraq, Noor A. Almansor, Farah Ahmed Thiab, Riyam Rajab Fenjan

HBRC Journal

Outdoor open spaces between university buildings support students' community interactions and academic achievements. However, in hot-humid climate zones, some of these spaces lack activity and experience social withdrawal due to thermal discomfort. This is seen on the University of Basrah campus. To address this, the study aimed to identify the most suitable climate-adaptive design pattern to improve thermal comfort and, in turn, enhance students' social presence in the University of Basrah's neglected, peripheral outdoor campus spaces. A convergent mixed-method case study was applied. First, measurable environmental and social factors were identified from related studies. Next, two open spaces in the …

The Impact Of Climate Change On Glass Facades: A Bibliometric Analysis, Pelin Akın, Güneş Mutlu Avinç

HBRC Journal

Climate change has direct impacts on the design and performance of building envelopes, necessitating new approaches in the discipline of architecture. In this study, a bibliometric analysis was conducted to understand the effects of climate change on glass façade systems. The 612 academic publications obtained from the Web of Science database were analyzed through R Studio Biblioshiny. Within the scope of the study, publication trends, key themes, prominent authors, institutions and geographical distributions were evaluated in detail. According to the findings of the research, it was indicated that research has gained momentum especially after 2016, focusing on themes such as …

Advances In Kenaf Fibre Reinforced Biocomposites: Processing Techniques, Performance Optimisation, And Future Research Directions, Thomas Adedayo Ayorinde, Tamba Jamiru, Peet F Le Roux, Basiru Philip Aramide, Oluwafemi Emmanuel Ogundahunsi

Engineering and Technology Journal

Kenaf fibre-reinforced composites have attracted considerable interest lately as eco-friendly materials due to their light weight, renewability, degradability, and favourable specific mechanical properties. Despite the advances already achieved in natural fibre composites, the commercial-scale use of kenaf-based composites has been hindered by variations in raw material quality, moisture sensitivity, interphase degradation, thermal instability, and other processing issues. This review critically assesses the morphology, reinforcement behaviour, fibre extraction methods, surface treatments, manufacturing processes, and characterisation techniques employed for kenaf fibre-reinforced composites within the framework of performance and sustainability. The study shows that no extraction and manufacturing process simultaneously optimises fibre integrity, …

Study Of Compressive Strength Of Palm Kernel Shell Concrete Under Various Curing Methods And Predictive Modeling Using Machine Learning, Hyginus Obinna Ozioko, Emmanuel Ebube Eze, Edward Ingio Adah

Engineering and Technology Journal

This study evaluates the compressive strength of Palm Kernel Shell Concrete (PKSC) under different curing methods and develops machine learning models for strength prediction. Concrete mixes containing 0–100% PKS replacement of coarse aggregate were prepared at a constant water-cement ratio of 0.5 and cured by immersion, sprinkling, wet hessian, and open-air methods. Compressive strength was measured at 7, 14, 21, and 28 days. Increasing PKS content reduced slump from 82 mm to 18 mm, oven-dry density from 2390 kg/m³ to 1430 kg/m³, and initial setting time from 108 min to 76 min. Immersion curing produced the highest …

A Hybrid Deep Learning Framework For Multi-Class Retinal Disease Classification, Ali M. Duhaim, Abbas M. Al-Bakry

AUIQ Technical Engineering Science

Ocular diseases such as diabetic retinopathy, glaucoma, and cataract remain major causes of vision loss worldwide, creating an increasing demand for accurate and reliable automated diagnostic systems. Although deep learning techniques have demonstrated strong performance in retinal image analysis, their clinical adoption is still limited by challenges related to predictive reliability, robustness, and interpretability. This study presents HEFR-Net (Hybrid EfficientNet-B3 and ResNet-50 Feature-Fusion Network), a hybrid deep learning framework designed for multi-class classification of retinal fundus images. The proposed architecture integrates EfficientNet-B3 and ResNet-50 through feature-level fusion, enabling the model to capture both fine-grained texture patterns and high-level structural characteristics …

Generative Model-Based Object Detection Using Concurrent Candidate Generation And Consensus, Leonid Kuligin, Thomas Zettl

Defensive Publications Series

Conventional object detection techniques can require extensive, task (specific) retraining to adapt to new domains or evolving conditions, which may be inefficient for certain applications. A system and method are described that can utilize a generative model-based workflow to perform context-aware object detection. For a given input, such as an image, and a textual prompt, a generative model may be invoked multiple times concurrently to produce a diverse set of candidate detections. A consensus mechanism can then process this set of candidates, for example, by filtering for duplicates and synthesizing the varied information to create a consolidated set of results. …

Automatically Managing Ai Fatigue Through Performance Tracking And Memory Summaries, Deep Raithatha, Tanmay Kayande

Defensive Publications Series

Generative artificial intelligence agents engaged in long-duration tasks often suffer from "contextual fatigue," a noticeable decline in reasoning quality and focus over time. To resolve this issue, an automated monitoring system can track the AI's internal word-choice patterns to detect early statistical signs of performance decay. Once this fatigue is identified, the system triggers a recovery process that temporarily pauses the main AI for a "sleep cycle." During this brief rest, a secondary AI reviews and condenses the primary agent's cluttered memory into a clean, dense summary. By resuming its task with this newly compressed information, the primary AI regains …

High Temperature High Pressure Extraction Methods, Natalie M. Durdle Miss

Defensive Publications Series

A method is disclosed for accelerating the extraction of flavor volatiles, peptides, and gelatin from animal tissue using high-temperature, high-pressure, non-turbulent conditions to prevent emulsion. The disclosure further details a rapid clarification protocol using mechanically released intracellular proteins to form an aerated, buoyant filtration raft, as well as a cryo-filtration process leveraging a self-assembling gelatin polymer network to separate lipids and hazy proteins from an aqueous phase. These processes are specified for both artisanal culinary production and mass-scale commercial soup, pet food, and protein recovery manufacturing operations.

Accelerated Production Of Culinary Stocks, Natalie M. Durdle Miss

Defensive Publications Series

A method is disclosed for accelerating the extraction of flavor volatiles, peptides, and gelatin from animal tissue using high-temperature, high-pressure, non-turbulent conditions to prevent emulsion. The disclosure further details a rapid clarification protocol using mechanically released intracellular proteins to form an aerated, buoyant filtration raft, as well as a cryo-filtration process leveraging a self-assembling gelatin polymer network to separate lipids and hazy proteins from an aqueous phase.

Ambient Pre-Conscious Intelligence (Api), Johny Manuel-Devadoss, Deepthi Prasad, Jayden Jack Johnson

Defensive Publications Series

Current artificial intelligence systems are, in practice, still largely reactive in nature. Even the most advanced assistants typically require explicit user prompts, clearly observable interaction events, or high-confidence inference of user intent before they engage in meaningful computational support. As a result, there is an inherent delay between the moment a cognitive need begins to emerge and the moment a system is able to respond. This delay is not merely a technical limitation; it introduces measurable friction into everyday human–computer interaction. In complex, information-dense environments, this friction accumulates, contributing to increased task-switching costs, reduced continuity of thought, and elevated cognitive …

Secure Live Streaming Architecture With Continuous Visual Identity Verification And Avatar‑Based Subject Representation, Krzysztof P. Bednarz

Defensive Publications Series

This publication describes a secure live streaming software architecture in which a human subject is continuously recognised using computer vision, visually occluded, and replaced in real time with an avatar-based graphical representation. The system supports local, remote, and distributed processing across mobile devices, desktop systems, and network-connected services. Identity verification is enforced throughout the streaming session, and streaming output is automatically frozen, paused, or terminated if the recognised subject no longer matches an authorised identity profile. This version extends the disclosure to include explicit failure modes and attack scenarios, strengthening its value as defensive prior art.

Dynamic Input Layering To Animate A Virtual Avatar Over A Mobile Video Capture Using Concurrent Front-Camera Tracking, Audio, And Ui Commands, Krzysztof P. Bednarz

Defensive Publications Series

This publication describes a mobile software architecture and method for real-time animation of a virtual avatar over a live or recorded video stream captured from a mobile device. The system concurrently utilises a back-facing for environmental video capture, a front-facing camera for facial tracking, and an audio input for lip synchronisation. A synchronisation and buffering mechanism aligns video, audio, and animation data streams in near real time, ensuring temporally coherent avatar animation over live or recorded video. These heterogeneous inputs are dynamically layered and synchronised to drive a two-dimensional (2D) or three-dimensional (3D) avatar while supporting both local recording and …

Continuity Of Care For Alcohol Use Disorder Patients Using Telehealth During The Covid-19 Pandemic, Martine Beaubrun

Walden Dissertations and Doctoral Studies

No abstract provided.