Digital Commons Network^™

Low-Latency Pointwise Language Model Ranker With Token-Probability Normalization And Coordinated Batch Inference For Online Content Ranking, Anonymous

Defensive Publications Series

Techniques are described for low-latency pointwise content ranking using a fine-tuned student language model. A ranking service constructs per-candidate language-model inputs that include user-context signals and candidate item context, and sends the inputs to an inference server in coordinated batches. The inference server returns output values for designated positive and negative label tokens, reducing accelerator-to-host transfer. A continuous relevance score is computed using token-probability normalization, score = P(pos)/(P(pos)+P(neg)), yielding a calibrated value in [0,1] for thresholding and ranking. Batch processing may include reuse of cached key/value states for shared user-context prefixes. The techniques enable scoring hundreds of candidates within tight …

Multi-Organ Living Donor Matching System Using Social Graph Embedding With Donation-Aware Bias And Heuristic Medical Compatibility Scoring, Anonymous

Defensive Publications Series

A computer-implemented platform matches living organ donors with recipients using self-reported profile data and social-network data. A request is routed by organ type to kidney, liver, or bone marrow logic. A Friend2Vec graph embedding model constructs a weighted social graph, performs biased random walks, and trains a Skip-Gram network to produce user embeddings. Friend2Vec adds a donation-aware bias parameter that preferentially traverses edges associated with successful donation events. Embeddings are fused with medical and geographic attribute vectors using a learned fusion layer with layer normalization. A multi-layer perceptron predicts P(Donation | Donor, Recipient) from concatenated donor and recipient embeddings, their …

Dual-Mode Adaptive Cache Management For Storage-Backed Embedding Systems, Anonymous

Defensive Publications Series

Techniques are described for adaptive cache management in SSD-backed embedding table systems that serve both training and inference. A mode detection engine monitors access pattern features including access multiplicity, write frequency, batch sequentiality, and request concurrency, and classifies operation as training, inference, or hybrid. Based on the classification, a cache manager switches among mode-specific policies for locking, prefetch, eviction, and write-back. Training mode may use generation-based locking, DataLoader lookahead prefetch, distance-based eviction, and write-back of dirty entries on eviction. Inference mode may use reference-count locking to block eviction during active requests, request coalescing with index deduplication for prefetch, and frequency-weighted …

Gpu-Storage I/O Isolation For Distributed Embedding Training Systems, Anonymous

Defensive Publications Series

A GPU-storage I/O isolation architecture is described for distributed embedding training with SSD-backed embedding tables. Storage-related callbacks are registered using a host function launch mechanism that holds a GPU driver mutex only during enqueue, allowing blocking key-value store reads to execute on a CPU thread without stalling other CUDA streams. SSD read completions are delivered through a condition-variable-backed fill queue that wakes a filler thread without polling. Cache eviction is overlapped with prefetch using a double-buffer eviction manager that alternates buffers across training steps while a background thread writes dirty entries back to SSD. A stream isolation scheduler assigns dedicated …

Distributed Cache Coherence Protocol For Tiered Embedding Storage Across Multi-Node Training Systems, Anonymous

Defensive Publications Series

A multi-node training system uses tiered embedding storage with a high-bandwidth memory cache and local persistent storage on each node. Each node maintains a probabilistic cache directory, such as a Bloom filter, that encodes identifiers of cached embedding rows and periodically exchanges the directory with peer nodes, optionally using delta updates. Upon a local cache miss, a fetch decision engine consults received directories to identify candidate peers and selects between a one-sided RDMA read from a peer’s cache and a local persistent-store read based on estimated costs and load limits. Remotely retrieved embeddings are accepted subject to a staleness threshold …

Pipelined Double-Buffer Eviction Scheduling With Gpudirect Storage For Zero-Copy Tiered Embedding Management, Anonymous

Defensive Publications Series

Techniques are described for tiered embedding management in which embedding rows are evicted from GPU memory to NVMe SSDs and prefetched from SSDs into GPU memory using GPU-direct storage DMA that bypasses CPU memory. Two page-aligned GPU-resident buffers are registered with a GPU-direct storage interface and are alternated by a double-buffer scheduler such that one buffer serves embedding access for model computation while the other buffer performs I/O. Eviction uses GPU-direct writes from GPU memory to SSD, and prefetch uses GPU-direct reads into a GPU-resident buffer followed by scatter to target GPU addresses. A batch coalescing layer groups small per-row …

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 …

Ai-Driven Runtime Software Adaptation With Ai Judge Validation And Sandboxing, Mira Leung

Defensive Publications Series

Static, pre-compiled software applications can be rigid, limiting their ability to provide dynamic, personalized user experiences and often requiring slow, resource-intensive update cycles. A system is described that can enable software to adapt its functionality or user interface at runtime. The system may utilize an architecture of artificial intelligence (AI) agents to generate code or configuration modifications based on high-level goals. A feature of this system can be an automated validation loop where an AI-based judge evaluates these modifications against a governance corpus of rules for security and correctness. Approved modifications can then be executed within a sandboxed environment in …

Multi-Agent Ai System For Human-In-The-Loop Document Packet Verification, Bhavani Sankar Sikakolli, Kalyan Konidala, Pinkesh Badjatiya, Yogesh Indoria, Gourabdip Ghosh, Siddhant Kurmi, Aryan Singh, Tilottama Basu, Farhan Rawani, Sangram Mohite

Defensive Publications Series

Verification of document packets for regulatory compliance may rely on manual review, which can be inefficient and susceptible to error. Some automated tools may not adequately compare data across diverse structured forms and unstructured evidence within a packet. A multi-agent artificial intelligence system can use specialized agents, which may leverage large language models, to automate processes such as the ingestion, classification, extraction, and validation of information. The system can employ a configurable source-of-truth hierarchy and multi-tiered matching logic to validate data. A human-in-the-loop mechanism can present flagged discrepancies or unverified fields to a human specialist for review and adjudication. This …

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 …

Global Research Institutions Most Likely To Build & Test The Caldwell Open‑Hardware Portfolio (2026 Edition) A Cross‑Domain, Field‑Indexed, Search‑Optimized Directory For Universities, Engineering Labs, Medical Centers, Atmospheric Networks, Space Agencies, And Applied‑Physics Research Groups, Michael Victor Caldwell Mr.

Defensive Publications Series

The Caldwell Open‑Hardware Portfolio contains more than 300 publicly available, builder‑ready inventions across energy harvesting, water systems, food resilience, medical bio‑acoustics, atmospheric science, space systems, materials engineering, compute infrastructure, and disaster‑resilience technologies. All inventions listed in this directory are open‑hardware, non‑patented, and publicly accessible on the Technical Disclosure Commons (TDC) under the author name “Michael Victor Caldwell.”

This disclosure is designed to maximize global discoverability, increase institutional downloads, improve AI‑driven indexing and recommendation, enhance search‑engine visibility, support prototype development and laboratory testing, and connect inventions to research programs across multiple domains. The directory uses semantic indexing, cross‑domain keyword clustering, and …

Automated Service Case Triage Using Real-Time Sentiment And Sensitivity Analysis, Parnika Singhal, Deep Raithatha

Defensive Publications Series

Systems and methods are described to address potential challenges in enterprise service management that can arise from delayed feedback and manual case routing. A described technology can utilize a processing pipeline to perform near real-time analysis of service interactions. This pipeline can ingest text-based communication data, sanitize it to remove personal information, and apply a computational linguistic model to classify user sentiment and identify predefined sensitive topics. Based on this analysis, a system may enable automated workflows, for example, the intelligent routing or escalation of cases that meet certain sentiment or sensitivity criteria. The system can also provide real-time sentiment …

The Protocol For Just-In-Time Adoption Of Auto-Provisioned Singleton Resources, Utkarsh Bhardwaj, Shivank Awasthi

Defensive Publications Series

In declarative infrastructure-as-code (IaC) systems, a challenge can arise when the creation of a parent resource also provisions a child resource having a runtime-generated identifier. This scenario may cause IaC tools to register a conflict error when attempting to manage the pre-existing child resource. A protocol is described to programmatically adopt these auto-provisioned singleton resources. The protocol can involve querying a cloud provider’s application programming interface to discover the child resource’s runtime identifier and then using that identifier in a just-in-time import process. This operation can map the existing resource to its declarative configuration block and inject it into the …

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 …

Reverse Hook Slackline Anchor, John Riley Mr

Defensive Publications Series

Slackline anchor with reverse hook design which increases power to depth ratio. This means the anchor performs at a shallower depth and is easier to install and extract to use again repeatedly.

The Cyclical Composite Virtual Projection System That Will Effectively Increase The Perceived Resolution Of The Cyclically Projected Virtual Projections Where The Effective Resolution Increasing Effect Will Be Achieved By Effectively Positioning The Cyclical Virtual Projections At A Greater Distance Away From The Eye., Punarjeewa Abeysekera

Defensive Publications Series

This paper describes a cyclical composite virtual projection system that will effectively increase the perceived resolution of the cyclically projected virtual projections where the effective resolution increasing effect will be achieved by effectively positioning the cyclical virtual projections at a greater distance away from the eye. The entire cyclical composite virtual projection system will consist of a cyclical projection directing system and 4 identical cyclically configured composite projection systems. And the cyclical projection directing system will contain 4 cyclically configured convex lens stack sections, 4 cyclically configured reflectors and 4 cyclically configured beam splitter configurations. In addition to that, each …

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 …

Progressive Contextual Augmentation Of Digital Media Using Implicit Prompts, Ashwin Goyal, Nick Staubach

Defensive Publications Series

Automatically surfacing content from media libraries can be highly useful, enabling users to effortlessly discover relevant contextual information and related data without having to perform manual searches. However, current methods usually require users to manually search for information, or rely on rigid rules that fail to capture the user's specific, current context. This disclosure describes techniques that automatically provide contextual information about media in a user’s library without requiring explicit prompts from the user. Media content items in a user’s gallery are weighted for their importance to the user. The metadata and content of an image (or other content item) …

Enhancing User Engagement During Call Initiation Latency, Aanya Mehta

Defensive Publications Series

This disclosure describes techniques, implemented with user permission, to enhance user engagement during the idle time between call initiation and connection. Contextually relevant, personalized content is displayed while a call is being connected. Such content can include, for example, photos, interaction metrics for the call recipient, event-specific information such as birthdays. For calls to a business, information about the business can be displayed. Display of useful information can improve the user experience of placing calls.

Gci‑Universal Resonant Energy Stack (Ures/Mmra/Grhn V1.0) A Three‑System Open‑Hardware Architecture For Replacing Conventional Solar Panels With Multi‑Modal Resonant Energy Harvesting License: Cern‑Ohl‑P (Permissive) No Patents. No Secrets. No Photos. Builder‑Ready., Michael Victor Caldwell Mr.

Defensive Publications Series

This unified disclosure presents three interoperable energy systems designed to evolve and replace conventional solar panels:

URES v1.0 — Universal Resonant Energy Skid  

1. A retrofit system that upgrades existing solar panels using Arachne Smart‑Skin, TEHL, vortex cooling, and APR AI.

MMRA v2.0 — Multi‑Modal Resonant Array  

1. A next‑generation resonant panel built on Arachne Gyroid Lattices, multi‑spectrum capture, and integrated vortex cooling.

GRHN v1.0 — Global Resonant Harvesting Network  

1. A frontier system using CMRS‑1, Ariadne’s Braid, Omni‑Vortex stacks, and environmental resonance harvesting.

All three systems include:

• BOMs

• ASCII diagrams

• safe build guidance

• prototype testing protocols

• viability percentages

• improvement estimates

• cross‑invention integration

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 …

System And Method For Interaction-Based Training Of Autonomous Agents, Eric Zavesky

Defensive Publications Series

A system and method for training autonomous agents through interaction-based validation is disclosed. The system includes a personality definition component that ingests behavioral specifications to synthesize personality parameters, and a training orchestration agent that conducts structured adversarial interactions with a trainee agent to validate behavioral alignment. An evaluation component detects systematic deviations through semantic analysis and pattern recognition across the interactions, distinguishing between isolated incidents and systematic misalignments. An interaction recording system captures the training exchanges for analysis, while a parameter refinement interface enables human oversight of behavioral modifications. The system addresses challenges in training agents to embody specific personality …

System And Method For Cryptographically Verifying Autonomous Agents In Merchant Transaction System, Sumit Kumar Roy, R V. Vighnesh, Apurba Pandey, Komaljot Kaur

Defensive Publications Series

ABSTRACT

A system for cryptographically verifying autonomous agents in merchant transaction systems includes a verification server configured to receive a transaction request from a terminal agent in a multi-agent delegation chain. The verification server parses a delegation chain manifest from the transaction request, wherein the delegation chain manifest comprises a linked list of signed hop records, each hop record capturing a delegation event from a delegator to a delegate. The verification server verifies, for each hop record in the delegation chain manifest, a delegator signature against a public key retrieved from an agent registry. The verification server verifies a hash …

Gci Universal Wildfire Conversion Skid (Uwcs‑1 / Uwsm‑1) An Open‑Hardware Retrofit Architecture For Converting Existing Water‑Carrying Fleets Into Wildfire Suppression Assets, Michael Victor Caldwell Mr.

Defensive Publications Series

This disclosure defines a builder‑ready, open‑hardware retrofit system that converts existing commercial, industrial, agricultural, mining, municipal, and military water‑carrying trucks into wildfire‑capable suppression units using a bolt‑on skid module.

The GCI Universal Wildfire Conversion Skid (UWCS‑1 / UWSM‑1) integrates:

• A vortex–thermoacoustic hybrid pump delivering 150–300 GPM at 250–400 PSI with pump‑and‑roll and dirty‑water drafting

• A VMR‑derived drafting and debris‑separation manifold for ponds, lakes, pools, canals, and reservoirs

• A fire‑rated discharge manifold with VETI‑3.0 vortex ejector nozzle integration for long‑range, coherent water jets

• Optional crew‑protection and monitoring modules based on CIWFRS, CORES, and GCI Vortex Sentinel (AV‑1)

• A power and control …

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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‑400 Arg‑Cm V1.0 — Atmospheric Resonance‑Guided Climate Modulation Network, Michael Victor Caldwell Mr.

Defensive Publications Series

The Atmospheric Resonance‑Guided Climate Modulation Network (ARG‑CM) is a fully open‑hardware, distributed system that uses real‑time atmospheric resonance sensing (ARPN) to predict moisture waves, trigger uplift, seed clouds, and coordinate atmospheric‑water harvesting in order to cool local and regional climates and reduce heat‑wave intensity.

ARG‑CM integrates:

• GCI‑322 ARPN v1.1 — Atmospheric Resonance‑Prediction Network

• Phoenix‑Water Engine (GCI‑268) — Atmospheric water harvester

• VAR (GCI‑280) — Vortex Atmospheric Reclamator

• CIFRS‑N v4.0 — Food‑Water‑Energy Nexus

• OSM v4.0 — Omni‑Sentinel Mesh

• TEHL‑v1.0 — Thermal‑Energy Harvesting Loop

• Sanitized Block — Structural housing

• CICIS — Compute and control backbone

This disclosure provides everything needed for engineers to …

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. …