Digital Commons Network^™

An On-Vessel Signal Discrimination Layer For Bandwidth-Constrained Maritime Decision Support, Dev Mohanty

Defensive Publications Series

The DeepBlue protocol sentry is an on-vessel signal-discrimination independent layer that filters high-frequency NMEA telemetry streams into compact, information-dense feature vectors. Unlike AIS broadcasts, rather than transmitting all raw sensor data (which is bandwidth-expensive and mostly redundant), it:

1. Normalizes raw NMEA sentences across GPS, propulsion, environmental sensors
2. Derives features (fuel consumption, course/speed changes, propulsion efficiency drift, loitering detection) over rolling 1-5 min windows
3. Scores materiality — only flags features that deviate from the vessel's own baseline
4. Assembles vectors of tens-to-hundreds bytes for transmission over satellite/mesh uplinks

The key insight: filter redundancy at source before transmission, not downstream. It's a …

System, Method, And Computer Program Product For Processing Documents Into Hierarchical Data Structures For Retrieval-Augmented Generation, Komal Mahto

Defensive Publications Series

ABSTRACT

Systems, methods, and computer program products are provided for processing documents. The system includes at least one processor configured to segment a document into a plurality of segments, construct a hierarchical data structure comprising a plurality of nodes representing the plurality of segments, each node of the plurality of nodes comprising hierarchical metadata, in response to determining at least one first node of the plurality of nodes exceeds a token limit, split the at least one first node into a first subset of nodes based on a semantic analysis of text represented by the at least one first node, …

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 New Posting,(4 Ais, Upgrades), Michael Victor Caldwell Mr.

Defensive Publications Series

Upgrade to this Invention/Posting Using 4 AIs to do so.

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 …

Ψ-Theory: Living Core. Ontological Development And Formalization. Comments 1–21, Valerii Y. Vorobiev

Defensive Publications Series

This document compiles comments 1–21, which chronologically develop and formalize Ψ-Theory — an ontological framework where time (Ψ-field) is the primary metric of reality, and gravity, mass, and quantum phenomena emerge from its dynamics. It addresses the crises of modern cosmology (dark matter, dark energy, Hubble tension) and quantum mechanics (measurement, non-locality) by replacing ad-hoc entities with a single causal principle. The comments include testable predictions (BH shadow shift, underground chronometry, Tully-Fisher derivation) and propose a phase diagram of reality from (4,2) to (0,-2).

The Oscillator Alignment Protocol (Oap), Christopher L. Eckes

Defensive Publications Series

This protocol rejects the standard "Master and Machine" or "Prompt and Bulk Text Drop" dynamic. Instead, it frames human-AI collaboration as a cognitive oscillator—an interactive analog system where human intuition serves a visual pattern, the AI echoes back the technical framework, and the idea evolves continuously through fast, low-overhead volleys.

Loci ∞ — Infinity Memory Middleware With Temporal Compression And Universal Cross-Platform Injection, Arko Sanyal

Defensive Publications Series

We disclose LOCI ∞, a universal memory middleware system for cross-platform AI memory synchronization. LOCI extracts entity knowledge from conversations on any LLM platform, stores it in a user-owned typed dual-stream profile (informational stream: heat-decaying associative entities; quantifiable stream: exact typed facts with zero-hallucination retrieval), and injects relevant context back into any LLM platform at any point during or between sessions. The system implements hardware-aware storage tiering mapped to entity semantic salience scores (VRAM/RAM/NVMe), graph-neighbor heat propagation via spreading activation, generation-time confidence-gated correction, keystroke-level predictive context prewarm, and a privacy-locked population memory layer using federated learning with differential privacy. A …

The Dimensionally Extended Holographic Projection Model: A Viscoelastic Unified Field Specification, Christopher L. Eckes

Defensive Publications Series

This technical disclosure formalizes the geometric synthesis of the Dimensionally Extended Holographic Projection (DEHP) model. We present a particle-free, mathematically cohesive alternative to standard general relativity and non-baryonic dark matter. The framework replaces independent fundamental forces with a single fluid-dynamic mechanism: the topological metric embedding of a continuous, two-dimensional (2D) phase fluid substrate (z=0) operating in absolute harmonic resonance (the "Garden State").

Three-dimensional (3D) physical matter (z > 0) is modeled as a localized, high-tension wave crest ("knot") forced outward along a spatial z-axis by an original inflationary puncture flux (\(J_{z}\)). By defining antimatter as a zero-volume, 2D negative wave trough …

Adaptive Multi-Format Prompt Preprocessing Using Unified Reinforcement Learning Framework, Katyayani Kiranmayee Kolluru, Shivam Mohan

Defensive Publications Series

The present disclosure provides a system for adaptive multi-format prompt preprocessing using a unified reinforcement learning framework. The system includes a prompt-type classifier (116) configured to identify a format type of an input prompt, wherein the format type includes one of natural language text, code, log, hybrid content, or error trace, the prompt-type classifier (116) being configured in some embodiments to perform deterministic rule-based classification. The system further includes a feature extraction layer (118) configured to produce a multi-modal representation of the input prompt capturing structural, linguistic, and semantic signals. The system also includes a hierarchical reinforcement learning policy engine …

In-File Stapled Freshness: Hash-Chain Validity Tokens Written Into A Frozen Self-Serialized Document Via A Length-Preserving Neutralized Zone, With Fail-Stale Offline Verification, Michael Benaudis

Defensive Publications Series

Revocation of frozen offline credentials — single-file HTML documents, PDFs, or other self-serialized digital credentials verified without any network, server, or public-key infrastructure — is information-theoretically constrained: a file sealed at issuance cannot learn of a later revocation event unless some information reaches the verification context. This disclosure does not remove that channel; it reduces it to one short, public, unforgeable hash-chain token per validity period, relayable by any untrusted party, and relocates the freshness proof inside the credential file itself. At issuance, a hash-chain tip (Micali NOVOMODO style) and period parameters are embedded in the credential's signed core, attested …

Persistent Driver Signatures For Software-Defined Vehicles, Sean C. Keys, Karsten Knese

Defensive Publications Series

This disclosure describes a system that enables software-defined vehicles (SDVs), smart cars, or connected autonomous vehicles to adjust their advanced driver assistance systems (ADAS) based on a persistent driver signature. The driver signature acts as a portable digital identity or user profile representing a driver’s unique physiological and behavioral tendencies, such as typical steering and braking patterns. Instead of storing raw data like video files, the system relies on a cloud database to store a secure mathematical model (a vector or tensor) that represents these individual habits. At the beginning of each trip, the SDV identifies the driver using a …

Technical Disclosure: The Urban Biosphere Ziggurat (Ubz), Affordable Housing And Urban Planning, Christopher L. Eckes

Defensive Publications Series

Current high-density urban housing models in the United States routinely fail because they optimize strictly for initial cost-per-square-foot, resulting in double-loaded corridor containment layouts that restrict natural light, induce community stagnation, and induce severe benefit "cliff effects" on upwardly mobile residents. The Urban Biosphere Ziggurat (UBZ) framework resolves this systemic crisis by decoupling high-tech, factory-precise structural engineering from regional, artistic architectural cladding. This disclosure outlines a scalable, non-speculative structural chassis integrated into a Community Land Trust (CLT) and Limited-Equity Housing Cooperative (LEHC) [1.5] governance ecosystem, permanently divesting real estate from predatory international speculation. [1]

To maximize municipal feasibility …

Concurrent Presentation And Evaluation Of Multi-Stream Media, Guillaume Vernon Bailey

Defensive Publications Series

Current techniques for displaying vertical videos on landscape displays suffer from inefficient use of lateral screen space and rely on linear navigation that yields limited, dwell-time-based engagement data. The disclosed technology addresses this by replacing single-video presentation with a concurrent multi-stream interface, displaying multiple vertical videos side-by-side in a user interface on a screen of a television. The disclosed technology maintains one media content item in an active playback state while keeping peripheral media content items in a subdued state, such as dimmed or paused. Users navigate horizontally to shift the active focus or vertically to populate a completely new …

Method For Trust-Aware And Language Model–Driven Email Threat Detection And Mitigation, Niranjan M M

Defensive Publications Series

Email remains the primary communication channel for enterprises and continues to be the most exploited attack vector for cyber threats. Modern email attacks increasingly rely on impersonation, social engineering, and contextual manipulation rather than traditional malware or malicious links, allowing them to evade existing detection mechanisms. At the same time, email security systems are adopting large language models (LLMs) to improve intent detection and contextual analysis, introducing new risks where email content itself can manipulate or degrade automated reasoning.

The proposal introduces a secure, trust-aware, and LLM-safe framework for automated email threat detection and remediation. The proposed system integrates sender …

Risk Authority Platform, Soumick Sinha, Mayank Johari, Lucas Fernando Müller, Sanjay Sawhney

Defensive Publications Series

Proposed herein is a Risk Authority platform that continuously computes an authoritative Trust Score and Trust Deficit for users or entities from heterogeneous security, identity, threat, compliance, privilege, and vendor-risk telemetry. The platform normalizes signals, applies configurable weighting and time decay, and maintains a versioned canonical trust state. A drift detection and reconciliation engine compares downstream trust states against the authoritative state and issues deterministic, idempotent reconciliation tokens when deviations or model-version mismatches occur. Software development kit (SDK) and application programming interface (API) integrations can validate schemas, verify tokens, and propagate risk updates. A closed-loop adaptive policy controller maps Trust …

System For Converting Predictive Insights Into Executable Tasks Using Retrieval-Augmented Generation, N/A

Defensive Publications Series

Predictive analytics tools are highly effective at identifying organizational risks, such as potential employee turnover, but they often fall short in providing managers with clear steps to resolve these issues. To bridge this gap, the described technology functions as an intelligent intermediary layer that translates high level statistical risk drivers into concrete, multi-step intervention strategies.  When a predictive engine detects a risk, the system uses a retrieval augmented generation framework to pull relevant contextual information from an internal knowledge base, which can include organizational playbooks and historical success records. This specific context is then fed into a generative large language …

System For Context-Aware Data Redaction Using Instruction-Constrained Generative Ai, N/A

Defensive Publications Series

Data redaction techniques, such as manual review or simple pattern-matching, may present challenges related to speed, potential for errors, and contextual understanding for identifying sensitive information. The described system and method may be used for a context-aware redaction process that uses a generative artificial intelligence (AI) model. Source text can be encapsulated within a detailed instructional prompt that guides the AI model's function toward identifying and substituting sensitive data. This process can be managed by an orchestration layer that is configured to interact with an AI inference engine, for example, under a zero-retention policy. By replacing identified data with semantic …

Prioritization Of Work Items Using Ai-Based Weighted Strategic Alignment, Tanmay Kayande, Deep Raithatha

Defensive Publications Series

Prioritization of work items within an organization can be a subjective and manual process, potentially leading to a disconnect between development efforts and strategic business objectives. A disclosed technology describes a system, for example, a computing device (e.g., a server, a smartphone, a wearable device), where an artificial intelligence agent can analyze unstructured work requests, such as feature ideas or bug reports. The agent may evaluate an item against a configurable registry of weighted strategic drivers, and can assign a numerical score and a natural language justification. A total priority score may then be calculated for a work item by …

System For Privacy-Preserving Cryptographic Auditing Using Zero-Knowledge Proofs, N/A

Defensive Publications Series

Systems for enterprise security may rely on high (fidelity) logging, which can involve collecting and storing large volumes of sensitive event metadata, creating security and privacy liabilities. A cryptographic auditing framework may be utilized where, instead of storing raw event data, a system can generate and store a succinct cryptographic proof, such as a zero-knowledge proof. This proof can serve as a mathematical attestation that a permitted action occurred in compliance with a governing policy, potentially without revealing the specific details of the user or the action. This approach can be used to generate a tamper-evident, privacy-preserving, and space-efficient audit …

Autonomous Stress Testing In A Network Digital Twin For Predictive Remediation, Mohit Chandra, Amrita Mukherjee

Defensive Publications Series

The management of complex telecommunications networks can be challenged by difficulties in predicting the impact of component failures and the risks of testing automations on a live system. Systems and methods are described that can address these challenges by creating and maintaining a graph-based digital representation, such as a digital twin, of an operational network that can be synchronized with real-time data. Within this digital twin, for example, an autonomous agent can perform synthetic fault injections to simulate a wide range of potential failures and stressors. The system can analyze the effects of these simulated faults to predict potential service-level …

Speculative Data Prefetching Based On Predicted Agent Intent In Machine Learning Systems, Anonymous

Defensive Publications Series

Techniques are described for speculative data prefetching in systems in which an LLM agent dynamically invokes retrieval backends whose candidates require embedding lookups from SSD-backed embedding tables. A user memory state with tiered memory data is obtained and converted into features. An intent prediction model produces, for each backend, a probability that the agent will invoke the backend. A prefetch controller computes a backend-specific prefetch decision using a value metric that combines probability, expected embedding lookups, SSD latency, and prefetch cost, and selects backends subject to a bandwidth budget based on SSD throughput and a Phase 1 time window. Speculative …

Coordinated Load-Aware Contention Domain Assignment, Peiman Amini, Navid Reyhanian, Ardalan Alizadeh, Matt Silverman

Defensive Publications Series

A system is proposed herein through which a set of techniques can be utilized to create a coordinated, latency-aware allocation policy for Dynamic Sub-band Operation (DSO).  DSO can be used to create multiple parallel contention domains.  For example, an access point (AP) can use fine-grained per-sub-band measurements, including overlapping basic service set (OBSS) frame ratio, jitter variance, airtime fairness, clear channel assessment (CCA), and retry metrics, to compute a condition score per sub-band. The AP can also use neighbor coordination pressure to prevent overlapping basic service sets (BSSs) from converging on the same sub-band and apply traffic-class-aware admission limits with …

Multi-Lane Concurrent Specification Evolution System With Configurable Ai Governance For Distributed Engineering Organizations, Anonymous

Defensive Publications Series

A multi-lane concurrent specification evolution system maintains a hierarchical specification across three lanes: isolated team experimentation branches, an integration lane, and a low-velocity consensus lane. Per-domain governance policies define permission levels for AI autonomy and human involvement, including human-only, human-review, AI-propose with an objection window, and AI-auto subject to a confidence threshold. An AI agent proposes and/or executes merges from team branches to the integration lane using conflict detection, contract compatibility checking, invariant validation, and cross-reference impact analysis for inter-domain accept/produce contracts, and notifies affected owners. When stabilization criteria are met, the integrated state is promoted to a versioned baseline …

Hierarchical Multi-Level Knowledge Graph With Compositional Contracts For Ai Agent Navigation Of Distributed Software Systems, Anonymous

Defensive Publications Series

Systems and methods store a hierarchical knowledge graph for navigating and changing distributed software systems. A product layer defines product identity, system bindings, and an end-to-end dataflow across system domains. A system knowledge graph includes a four-level specification hierarchy: domain specifications with intent phrases and ownership metadata; feature specifications with typed accepts/produces compositional contracts; behavior specifications with given/when/then invariants; and technical specifications with implementation anchors and referenced skills. An agent follows a six-phase change protocol: understand a request via semantic discovery over intent phrases, plan by traversing bindings and dataflow to identify impacted specs and code locations for approval, execute …

Persistent Hierarchical Context System With Cloud-Synchronized Memory For Ai Agent Workspace Awareness, Anonymous

Defensive Publications Series

Systems and methods provide persistent, hierarchical, project-aware context for an AI agent using a dual-use file hierarchy. A cloud-synchronized workspace contains embedded, machine-parseable context files at multiple directory levels. When the agent operates with respect to a directory, a context loader automatically loads a chain of context files from that directory and parent directories to form layered context including user identity, preferences, and project-specific information. Because the context resides as files within the cloud-synchronized workspace, the context persists across sessions and follows the user across devices. An ingestion mechanism accepts arbitrary inputs such as links or notes, analyzes content to …

Hierarchical Multi-Resolution Columnar Encoding With Trait-Specific Aggregation For User Engagement Sequence Feature Stores, Anonymous

Defensive Publications Series

A self-contained columnar record format stores a user engagement sequence across multiple traits using multiple tiers having different time windows and granularities. The record includes a header that specifies tier descriptors (including entry counts, byte offsets, and encoder identifiers) and trait descriptors (including data types and trait-specific aggregation functions). A rolling compaction pipeline moves data from finer tiers to coarser tiers by bucketizing by the coarser granularity and applying the stored aggregation function per trait (e.g., SUM, MAX, MIN, MODE, OR, SAMPLE_TOP_K, WEIGHTED_AVG). A resolution-aware decode API receives a resolution budget selecting a subset of tiers and optional per-tier entry …

Closed-Loop Profile-Guided Kernel Optimization With Bottleneck-Shift Detection And Cross-Kernel Transfer Learning, Anonymous

Defensive Publications Series

A closed-loop GPU kernel optimization technique collects hardware performance counters to form a normalized counter-profile vector and classifies the kernel into a bottleneck class. Candidate structured transforms are selected using probabilistic ranking based on stored successes and failures for transforms conditioned on bottleneck class and hardware. After each transform, the kernel is re-profiled (in addition to benchmarking), re-classified, and a bottleneck shift is detected when the bottleneck class changes. Upon a shift, remaining transforms are re-ranked for the new bottleneck class. Optimization trajectories are recorded as sequences of transforms, bottleneck-shift pairs, and speedups, enabling multi-step lookahead scoring. Cross-kernel transfer is …

Ai-Powered Autonomous Agent For Enterprise Platform Configuration With Live Introspection And Dependency-Aware Deployment, Anonymous

Defensive Publications Series

An autonomous agent configures a configurable enterprise platform to onboard a new business vertical. The agent performs live environment introspection using parallel administrative API calls to build a snapshot and a graph of configuration components and their relationships. Existing verticals are detected using naming patterns and relationship traversal with confidence scoring, and a baseline vertical template is extracted. A three-phase requirement analysis maps requirement patterns to component clusters, matches required components against the snapshot using five-tier classifications (exact, sibling, partial, misconfigured, missing) with risk metadata, and enriches results using a machine-learning model that identifies dependencies and contradictions and outputs structured …

Systems And Methods For Automated Recipe Extraction From Multimedia Content With Visual Pantry Inventory Detection And Differential Shopping List Generation, Anonymous

Defensive Publications Series

Systems and methods are described for transforming unstructured cooking-related multimedia into actionable outputs. A client provides a video link, web link, screenshot, or photo. One or more models extract ingredients and preparation actions using combinations of speech recognition, optical character recognition, and visual recognition. A structured recipe is generated with ingredients and ordered steps, and additional attributes such as serving size, nutrition or macronutrients, and dietary tags are derived. A meal plan may be produced over a time window, and required ingredients are aggregated. Optionally, the user captures images of pantry and/or refrigerator contents via a guided flow. Inventory items …

Systems And Methods For Asymmetric Propagation Constraints With Partitioned Memory Architecture In Collaborative Recommendation, Anonymous

Defensive Publications Series

Techniques are described for collaborative recommendation that constrain cross-user propagation of user-derived signals using asymmetric, type-dependent rules. A signal classification layer assigns each generated insight to a psychological signal type including positive preference, negative preference, behavioral pattern, and vulnerability indicator. An asymmetric propagation engine applies type-specific parameters such as hop depth, evidence thresholds, confidence discounting, and temporal decay, including higher friction for negative, behavioral, and vulnerability-related signals than for positive preferences. Negative preference propagation is constrained to a demotion-only effect in ranking, reducing scores without excluding candidates. A partitioned memory architecture stores ranking-accessible preferences in a first partition and stores …

Systems And Methods For Automated Code Review Quality Assessment Using Hybrid Classification And Logarithmic Scoring With Anti-Gaming Safeguards, Anonymous

Defensive Publications Series

Systems and methods are described for automated assessment of code review quality using review comments, reviewer actions, reactions, and diff context. A pipeline identifies human reviewers, extracts per-reviewer comment threads, and executes parallel sub-agent analyses to produce structured signals including impact and relevance scores and comment attributes. A deterministic ruleset classifies each comment into HIGH, MEDIUM, LOW, or OUT_OF_SCOPE. A reviewer score is computed using weighted counts of classified comments with a logarithmic normalization term to provide diminishing returns, and may include additive bonuses such as code suggestions, reactions, and request-changes actions. Multi-layer integrity safeguards may include concentration ratio thresholds, …