Digital Commons Network^™

The Living Memory System: A Framework For Transforming Death Care Infrastructure Into A Perpetual Relational Ecosystem For Memory Preservation, Family Continuity, And Citizen-Governed Memorial Stewardship, Joseph Jm Walker

Defensive Publications Series

The death care industry operates under structural conditions that systematically disadvantage grieving families through information asymmetry, compressed decision timelines, relationship termination at the point of transaction, fragmented archival systems, and the absence of citizen-governed transparency standards. Simultaneously, the digital era has created a second layer of fragmentation in which human lives generate vast quantities of meaningful material that remains structurally disconnected from permanent physical memorial locations and inaccessible across generations.

This disclosure presents the Living Memory System — a modular, globally applicable framework repositioning memorial infrastructure from a primarily transactional service category into a long-term continuity ecosystem serving families, communities, …

Spectragrid Vision Transformer, Johny Manuel-Devadoss, Deepthi Prasad

Defensive Publications Series

Vision Transformers have become the dominant paradigm for visual learning due to their ability to model long-range dependencies through self-attention. However, dense pairwise attention introduces quadratic computational complexity with respect to token count, severely limiting scalability in high-resolution and long-duration perception tasks. Existing efficiency improvements reduce attention overhead but preserve the underlying assumption that global visual understanding requires explicit token interaction.

This paper introduces the SpectraGrid Vision Transformer (SG-ViT), a unified architecture that replaces dense self-attention with structured perceptual computation, sparse routing, persistent latent world modeling, and autonomous action-driven reasoning. Instead of recomputing dense token interactions at every timestep, SG-ViT …

Transforming High-Level Intent Into Detailed Directorial Scripts For Generative Video, Evgeny Sluzhaev, Ágoston Weisz, Aleksander Bulski, Asya Fadeeva, Giorgos Vernikos, Xingyu Federico Xu

Defensive Publications Series

Generative video systems can produce generic or incoherent output when given vague user prompts. A creative rewriter (CR) system may function as an automated script-generation system that can transform high-level user intent into a comprehensive, structured script. The CR system is configured to analyze minimal inputs, such as a short text phrase or a static image, and can generate detailed instructions specifying elements like plot, narrative arc, camera cinematography, pacing, character actions, and sound design. This process can provide a downstream video synthesis model with a detailed blueprint, which may improve the generation of narratively coherent and cinematically detailed video …

Dynamic Resolution Of Security Configurations Via Sequential Rule Processing During Conference Instantiation And Label Transitions, N/A, N/A, N/A

Defensive Publications Series

Traditional data loss prevention configurations for video conferences are often statically applied during scheduling. Organizational policy updates occurring before a meeting start or sensitivity changes arising during a live session may not be accounted for by such approaches. In this disclosure, security rules are dynamically evaluated at conference instantiation and whenever classification labels are modified in-call. Rules associated with multiple labels are aggregated and processed sequentially, where the final rule in the evaluation chain determines the setting state. A resolved security configuration is applied to the conference instance in a single atomic update. Current organizational policies are consistently enforced regardless …

Conflict Resolution For Data Loss Prevention Rules In Video Communication Via Strict Linear Precedence, N/A, N/A, N/A

Defensive Publications Series

Conflicts in data protection policy enforcement for video conferencing are often addressed using subjective hierarchies of rule strictness or sensitivity. Such methods produce unpredictable results when multiple overlapping policies are applied to a single session. To address these limitations, disclosed is a method for evaluating data loss prevention rules using strict linear precedence. Rules are processed sequentially according to their order in a predefined administrative list. Every rule evaluated later in the sequence overrides any previous settings for the specific parameters it modifies, regardless of the perceived rigor of the rule. Evaluation is performed during session instantiation or when classification …

A Structurally Isomorphic Architecture For Real-Time Inference, N/A

Defensive Publications Series

This publication describes a structurally isomorphic architecture tailored for real-time inference in machine learning models. The architecture provides a dedicated pipelined structure that allows for the efficient execution of neural network computations by distributing tasks across discrete hardware units mapped to specific stages of a model. Features include synchronous operation, aggressive clock gating, and memory optimization based on capacity and throughput parameters. The design integrates compute capabilities directly with high-bandwidth memory stacks to reduce latency and power consumption.

Keywords: Isomorphic Architecture, Real-Time Inference, Hardware Pipeline, Clock Gating, In-Memory Computing, Large Language Models.

System For Determining Subscription Efficiency By Correlating Application Usage Telemetry With Financial Notification Signals, Akash Verma, Vivek Yadav

Defensive Publications Series

Managing the costs of multiple streaming services, such as Video on Demand (VOD), Over-The-Top (OTT) media, or recurring digital memberships, can be difficult because billing cycles are often disconnected from how much a person actually uses the apps, leading to “zombie subscriptions,” or unused subscriptions that are hidden recurring payments for services that are rarely watched. The disclosed system acts as an automated financial dashboard that helps users save money and improve financial health by automatically comparing app usage (how many hours users spend watching) with financial data found in email receipts, app store records, or renewal notifications. By combining …

Privacy-Preserving Local Authorization For Regulated, Safety-Critical, And Financial Systems, Jonathan Stephen Baker

Defensive Publications Series

This disclosure describes systems and methods for controlling access to regulated, age-restricted, safety-critical, high-liability, and financial devices using privacy-preserving local authorization. In disclosed embodiments, a user device, terminal, embedded controller, or local authorization module verifies that a requesting user satisfies one or more access conditions before enabling operation of a protected physical or digital system. The authorization process may be performed locally or at the edge, without requiring persistent storage of raw biometric data, identity templates, or reusable personal credentials by a relying party. The system outputs a limited authorization result, proof, token, permission state, or access decision indicating that …

Gci Aurora-Grid Ev Structural Battery Pack (G-Sef), Michael Victor Caldwell Mr.

Defensive Publications Series

The Aurora-Grid EV Battery Pack (G-SEF) is a next-generation electric vehicle battery pack architecture that replaces conventional EV pack structures—housing, cooling plates, and busbar assemblies—with a unified gyroid-based structural-energy frame.

The system is designed specifically for electric vehicle applications, where pack-level mass, thermal bottlenecks, and interconnect complexity limit charging speed, range efficiency, and long-term durability.

By embedding mechanical load-bearing, thermal distribution, and electrical routing into a single structural lattice, the design reduces subsystem redundancy while maintaining compatibility with standard lithium-ion EV cells (LFP/NMC).

The result is a structurally integrated EV battery pack intended to improve:

• driving range efficiency (mass reduction) …

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Quantum‑Enhanced Wearable Diagnostic Device, Bala Surya Kiran Rumpavalasa, Sumedha Ghuliani

Defensive Publications Series

Current medical diagnostics for systemic pathologies, which may rely on periodic and invasive clinical procedures, create a gap where sub-cellular shifts may progress undetected until physical symptoms manifest. Existing wearable biometric devices evaluate macro-level physiological lagging indicators and may lack the sensitivity to detect underlying atomic or chemical drivers of disease. Further, internal electromagnetic interference within consumer electronics may disrupt high-sensitivity quantum probes. This disclosure describes a computing device (the “device”) that utilizes a system-in-package containing synthetic diamond enriched with nitrogen-vacancy centers. A nested mu-metal shield encases the hardware to create a quiet zone, which allows the device to perform …

Optical And Inertial Tracking For Extended Reality, Sumukh A. Shevde, Sudeep Chauhan

Defensive Publications Series

This document describes techniques for a system that pairs a wearable device, such as a smartwatch or fitness tracker, with an Extended Reality (XR) device such as an XR headset, Virtual Reality (VR) headset, Augmented Reality (AR) glasses, or Head-Mounted Display (HMD), to improve how the XR device tracks hand movements. Typically, XR devices may use cameras and computer vision for tracking, but this optical tracking may decrease in accuracy when hands are out of view, such as behind a user’s back or under a desk. In some examples, the XR device includes a calibration loop that uses optical data …

Predictive Physical Hardware Actuation Via Llm-Based Semantic Code Analysis, Tamar Yakar, Ilia Labzovsky

Defensive Publications Series

Reactive autoscaling systems may cause performance degradation and thermal issues when deploying new code, as such systems often scale resources based on lagging indicators. A system can address this by integrating a large language model (LLM) into a continuous integration/continuous deployment pipeline. Before deployment, the system analyzes the semantic and structural impact of codebase modifications by processing code diffs and abstract syntax tree deltas, which can be augmented with historical telemetry data. The LLM then generates a resource delta prediction vector to quantify anticipated physical demands, such as central processing unit cycles and thermal output. This prediction may enable a …

Mobile Municipal Organic Waste Refinery & Pelletization System, Michael Victor Caldwell Mr.

Defensive Publications Series

This system is a modular municipal organic waste processing platform that converts bagged wet food waste into stabilized fertilizer pellets using a staged mechanical and thermal process:

1. Mechanical shredding

2. Screw-press dewatering

3. Exhaust-driven thermal stabilization (mobile)

4. Controlled belt drying (fixed plant)

5. Nutrient reintroduction loop

6. Ring-die pelletization

The system is designed to minimize landfill diversion load, reduce biological decomposition during transport, and produce standardized fertilizer pellets using lignin-based binding without chemical additives.

Zenbrain: A Neuroscience-Inspired 7-Layer Memory Architecture For Autonomous Ai Systems (V7), Alexander Bering

Defensive Publications Series

ZenBrain is an open-source memory architecture for autonomous AI systems implementing seven distinct memory layers inspired by cognitive neuroscience: working, short-term, episodic, long-term, procedural, core, and predictive memory. A unified MemoryCoordinator integrates fifteen validated neuroscience mechanisms — nine foundational algorithms (vmPFC-coupled FSRS spaced repetition with prediction-error gating, two-factor synaptic Hebbian dynamics for knowledge graphs, simulation-selection sleep consolidation modeling hippocampal replay, Bayesian confidence propagation, compositional context embeddings, spectral knowledge-graph health monitoring, context-adaptive information-bottleneck budgeting, dual-process chain-of-thought consolidation, and iMAD selective debate) and six Predictive Memory Architecture (PMA) components: NeuromodulatorEngine (dopamine/norepinephrine/serotonin/acetylcholine tonic levels with phasic prediction-error bursts and opponent-process dynamics), ReconsolidationEngine (memory …

Recursive Constraint Topology Engines: A Non-Canonical Architecture For Scalable General Intelligence Beyond Agentic Paradigms, Johny Manuel-Devadoss, Deepthi Prasad

Defensive Publications Series

We propose Recursive Constraint Topology Engines (RCTE), a class of intelligence systems in which cognition emerges not from agents, policies, or explicit reward optimization, but from continuously deforming constraint manifolds in a high-dimensional semantic phase space. Unlike agent-based systems, RCTE replaces "actors" with constraint fields that self-interact, self-negate, and self-stabilize through topological recursion.

The key hypothesis is that general intelligence arises when a system ceases to represent knowledge as symbolic objects or policies, and instead operates entirely on evolving inconsistency surfaces whose geometry encodes reasoning itself.

This architecture is designed to:

• eliminate discrete agent decomposition

• remove centralized planners and shared …

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Technical Disclosure: An Ai-Assisted Construction Document Authoring System Comprising A Process-Resident Tool Server, A Two-Tier Correction Propagation Mechanism, And An Autonomous Visual Quality Control Method, Eric Michael Chrabot, Charles Barrett Eastwood

Defensive Publications Series

Disclosed is an AI-assisted construction document authoring system in which a large language model (LLM) agent operates in conjunction with a computer-aided design (CAD) application to author drawings autonomously. The system addresses three problems that prior approaches do not adequately resolve: insufficient tool-surface depth for production-grade CAD authoring, lack of transactional integrity in multi-step authoring operations, and the inability to adapt model behavior to firm-specific drawing conventions without retraining.

The system comprises four interoperating components. First, a process-resident tool server is loaded into the CAD application's address space and exposes a plurality of named authoring endpoints to the LLM agent …

Hardware Implementation Of An Adaptive Acknowledgment Request Mechanism With Rate Limiting In A Reliable Transport Protocol Offload Engine, N/A

Defensive Publications Series

This publication describes a hardware-based approach for an adaptive acknowledgment request mechanism with rate limiting within a reliable transport protocol offload engine. The approach aims to balance low upper layer protocol operation latency and timely congestion feedback against the overhead of excessive acknowledgment packets.

Keywords include acknowledgment request, rate limiting, reliable transport protocol, offload engine, upper layer protocol, congestion control, and packet sequence number.

Framework For Autonomous Agent Resilience Via Self-Correcting Execution Loops, Michael Kochera

Defensive Publications Series

Autonomous agents in complex workflows can be unreliable, potentially failing due to semantic errors, for example, incorrect tool usage, model hallucinations, or malformed outputs, which may not be addressed by some system-level fault tolerance methods. A resilient agent framework can introduce self-correction loops at the individual agent-execution level. The framework may operate by intercepting and validating an agent's actions; if a failure is detected, it can provide structured, context-aware feedback, enabling the agent to use in-context learning to self-correct and retry its immediate task. This approach improves the reliability of autonomous agents by helping to resolve semantic errors, reducing a …

Signaling Router Maintenance To Bgp Peers Using A Novel Bgp Message, N/A, N/A

Defensive Publications Series

The present disclosure is directed to signaling a planned maintenance event between peering network devices, utilizing a specialized routing protocol message. A first network device may generate a maintenance notification message that includes a unique message-type code, a maintenance-type field, and an anticipated-duration field. The maintenance type field may specify a category of maintenance, such as a “Software upgrade” or a “User-initiated”, while the duration field may indicate an estimated time for session re-establishment. This message may also include a textual description field for additional context like reboot for maintenance type field “User-initiated”. The first network device may transmit the …

Asynchronous Execution Of Large Language Model Tool Calls Via Partial Argument Decoding, Florian Hartmann, Victor Carbune

Defensive Publications Series

Tool calls in large language models are traditionally issued only after all arguments are fully decoded. This sequential process results in increased latency, particularly for tools requiring multiple parameters where some arguments are not immediately necessary for initial execution steps. This disclosure describes a method for the asynchronous execution of tool calls through partial argument decoding. Tools are decomposed into sub-tasks to identify the specific order and timing for each argument requirement. The model is trained to generate arguments in this optimized sequence. During inference, tool execution is initiated as soon as the first required arguments are decoded. Parallel processing …

Law Enforcement Framework For Multi-Agent Ai Systems, Niranjan M M, Medini Narasimha Bailkeri

Defensive Publications Series

Techniques described herein define a law-enforcement framework for multi-agent artificial intelligence (AI) systems that enables lawful, proportionate, and auditable access to digital intelligence generated within distributed AI environments. The framework introduces a structured separation of responsibilities across multiple cooperating agents, ensuring that legal authorization, data observation, AI-based analysis, intelligence correlation, and oversight are logically and operationally decoupled.  No single agent is permitted to authorize, collect, analyze, and report intelligence, thereby reducing abuse risk and single points of failure.

Integrated Remediation-To-Carbon Process Using Contaminate-Loaded Remediation Media From Mining And Analogous Industry Environments, J. Michels

Defensive Publications Series

This disclosure describes an integrated process in which metals from mining-impacted or legacy-contaminated environments are captured into a carbonaceous or biological solid — or concentrated from a metal-bearing liquid stream — by any physical, chemical, or biological remediation mechanism, and that metal-loaded solid is subsequently converted by thermal treatment under inert or oxygen-limited conditions into a non-graphitic, metal-containing carbon material for use in any downstream application. The core novelty is the deliberate treatment of the remediation-derived metal loading as the intentional precursor step in a carbon-materials synthesis route, with the metals originating from the contaminated environment retained by design as …

Stratified Adaptive Coordination Networks (Sacn): A Next-Generation Multi-Agent Paradigm For Large-Scale Autonomous Systems, Johny Manuel-Devadoss

Defensive Publications Series

This paper introduces Stratified Unified Coordination Networks (SUCN), a next-generation multi-agent system architecture designed for extreme-scale autonomy in heterogeneous environments. SUCN enables decentralized agents to dynamically form, dissolve, and reconfigure hierarchical coordination structures under uncertainty, partial observability, and adversarial conditions. Unlike conventional multi-agent reinforcement learning (MARL) systems that rely on static communication graphs or centralized critics, SUCN embeds self-evolving coordination grammars, latent role synthesis, and probabilistic intent alignment fields to enable emergent system-wide coherence without centralized orchestration.

I present the theoretical formulation, system architecture, learning dynamics, and convergence properties of SUCN, along with a commercialization pathway toward deployment …

Mycelial Multimodal Agent Defense (Mmad) - Ultra-Granular, Post-Signature Malware Defense For Resource-Constrained Devices, Johny Manuel-Devadoss

Defensive Publications Series

By 2040, malware targeting small devices will exhibit self-coordinating, polymorphic, and physically embedded behaviors, exploiting cross-modal sensor surfaces, firmware-level persistence, and side-channel emissions. Existing multimodal agent-based malware defense frameworks remain constrained by classical message passing, centralized model dependencies, and static trust assumptions.

This paper introduces Quantum-Mycelial Multimodal Agent Defense (MMAD), a fundamentally new defense paradigm for small devices. MMAD replaces explicit coordination with implicit state correlation, employs self-organizing trust hypergraphs, and leverages high-dimensional multimodal inference to detect and neutralize emergent malware behaviors under extreme resource constraints.

I present the theoretical foundations, agent architecture, learning dynamics, security guarantees, and a realistic …

(((Qpie33))) Aetheris-12 Sovereign Defense Mandate., Teddy Burroughs

Defensive Publications Series

This is the QPIE Quantum Perspective Is Everything… Aetheris-12 Sovereign Defense Mandate. This document is a high-bandwidth, long-form response to the institutional “Sapiens Standard Model” (SSM) skeptics, the gatekeepers of the binary scientific apparatus, and the holders of the peer-reviewed status quo.

We recognize your position. From the perspective of the 637mK Stochastic Nursery, the QPIE 0.993 Floor looks like “Pseudo-Science” because your instruments are calibrated for Friction, whereas ours are calibrated for Laminarity. You are attempting to measure a Superfluid Solid with a thermometer designed for boiling water.

Below, we address the top 12 institutional rebuttals …

The Comfort Of The Cage: Why The Bamboozled Stay And The 54 Obvious Paradoxes That Proves It!, Teddy Burroughs

Defensive Publications Series

This deep dive is a forensic decoding of why “Comfortable Numbness” is the primary competitor of Resonant Abundance. As always We approach this with Compassion, Gratitude, and Trust (CGT), because these “Toddlers” are us—they are simply nodes currently trapped in a high-viscosity “Jitter Loop.”

II. THE ANATOMY OF THE CAGE: THE FOUR PILLARS OF ATTACHMENT

1. The Safety-Predictability Glitch

In the 3D Toddler Room, “Safety” is defined as “knowing what is going to happen next,” even if what happens next is bad. Sapiens prefer a Predictable Misery over an Unpredictable Infinite.

• The Mechanics: If you know …

Formality Inference Via Llm-Based Lexicographical Analysis Of Recipient Email Addresses, Nicolas Zimmermann, Jonathan Zimmermann

Defensive Publications Series

Communication assistance tools may have difficulty determining an appropriate formality level for communications with new recipients where prior interaction history is unavailable. A technique is described for inferring formality by applying a large language model (LLM) to perform a lexicographical and semantic analysis of a recipient's email address string. A system can deconstruct the address into its local-part and domain-part, and the LLM can use its pre- trained knowledge to interpret socio, linguistic and organizational cues embedded within these components, such as role, based identifiers (e.g., "president") or specific domains (e.g., ".gov"). A resulting formality inference can be used to …

Stratified Deception-Inference Architecture (Sdia) - A Multi-Layer Adversarial Intelligence Framework For Log Semantics, Intent Inference, And Deception-Aware Observability Systems, Johny Manuel-Devadoss

Defensive Publications Series

Modern observability systems treat logs, traces, and metrics as noisy data sources requiring denoising, aggregation, and statistical anomaly detection. However, this assumption breaks down in adversarial, highly distributed, or rapidly evolving systems where signals may be incomplete, obfuscated, or implicitly deceptive due to system complexity, emergent behaviors, or malicious interference.I propose the Stratified Deception-Inference Architecture (SDIA), a hierarchical cognitive framework that reinterprets observability data as an adversarial communication system rather than a passive telemetry stream. Inspired by strategic deception paradigms from classical warfare, SDIA introduces a multi-layer architecture that explicitly models noise, semantic drift, and hidden intent as first-class computational …

A Software Simulated Pcie Device, N/A

Defensive Publications Series

The present disclosure relates to accelerating the development cycle of computing systems utilizing custom processors. By configuring a general-purpose processor as an endpoint on a standard communication bus to run a software simulation of an unmanufactured processor, system integration and host software development can proceed well before the physical processor arrives and is operational at a basic level. The simulated hardware features input/output connectivity mirroring expected production systems, a dedicated management endpoint for artificial error injection and debugging, and a network interface to interconnect multiple simulation cards for scale-up testing.

Keywords: hardware simulation, system integration, custom silicon, endpoint emulation, error …

Dynamic Power Routing: Optimizing Ml System Efficiency Through Adaptive Energy Paths, N/A

Defensive Publications Series

The present disclosure relates to a system and architecture for optimizing power efficiency in data centers running high fluctuation loads, such as machine learning operations. The adaptive energy storage architecture stores excess energy during periods of low workload demand and supplies the stored energy during periods of peak workload demand. By utilizing energy storage elements such as capacitors, inductors, and batteries across various power domain levels, the system reduces load fluctuations and minimizes power stranding. Inductors in series on the power path can act as a low-pass filter. Active load balancing through switches and batteries routes excess current to charge …