Digital Commons Network^™

Categorical Label Matching For Post-Remediation Knowledge Deficit Recurrence Monitoring, Kenneth Davis

Defensive Publications Series

Field

Computer-implemented systems for monitoring whether identified knowledge deficits recur after remediation. This publication describes an approach that uses categorical label comparison rather than dense vector embedding similarity computation.

Background

Once an employee completes remediation for a knowledge deficit, organizations want to know if the same deficit comes back. One way to do this is with embedding-based approaches that compute cosine similarity between dense vector representations of subsequent communications and stored gap fingerprints. The approach described here takes a different path: it compares classification labels rather than embedding vectors. The computational cost is much lower, though discrimination capability is reduced. …

Blockchain Consensus Protocol For Federated Knowledge Gap Record Validation And Cross-Organizational Competency Attestation, Kenneth Davis

Defensive Publications Series

Field

Distributed ledger systems for validating, federating, and attesting organizational knowledge gap records across multiple organizations. This publication describes an approach that uses blockchain consensus rather than centralized cryptographic hash chain verification.

Background

Organizations that maintain knowledge gap records and competency evidence need ways to ensure record integrity, prevent unauthorized modification, and support cross-organizational competency attestation. Think of a nurse transferring between hospitals or a financial advisor moving between firms. Centralized hash chain approaches keep all integrity verification data in a single organizational data store. The approach described here distributes the verification function across multiple nodes using a blockchain network. …

Structured Assessment Score Gap Detection Without Natural Language Processing, Kenneth Davis

Defensive Publications Series

Field

Computer-implemented systems for detecting individual knowledge deficits in organizational workforces. This publication describes an approach based on structured assessment score analysis that does not require natural language processing of unstructured communications.

Background

Organizations routinely assess employee knowledge through structured instruments: multiple-choice quizzes, Likert-scale self-assessments, scored simulations, timed task completions. These instruments produce numerical score vectors. The scores can be analyzed computationally to surface knowledge deficits without ever touching a natural language processing pipeline.

Technical Description

The system receives structured assessment results. Each result contains numerical scores across predefined dimensions (for example, product accuracy scored 1 to 5, procedural compliance …

Optimization Of The Testing Process For Electricity, Water, And Gas Meters, Osmara Rojas

Defensive Publications Series

The present disclosure relates to methods and systems for optimizing a testing process for electricity, water, and gas meters. Conventional testing workflows suffer from inefficiencies such as excessive time consumption, susceptibility to human error, and lack of standardization. The disclosed approach overcomes these limitations by implementing risk-based test case prioritization, dynamic resource allocation, automation of repetitive test cases, parallel execution of test cases, and continuous monitoring with adaptive adjustments. The methodology employs analytical tools, including Pareto diagrams and risk matrices, to ensure systematic decision-making. This integrated framework delivers enhanced efficiency, reliability, and scalability, enabling accelerated product deployment and improved quality …

Integrated Active Dimming Assembly In Compression-Molded Optical Lens

Defensive Publications Series

The present disclosure generally relates to optical lenses, and more particularly, to integrated active dimming assembly in compression-molded optical lens.

Deterministic Aneutronic Fusion Via Golden Ratio Magnetic Gradient And Harmonic Resonance Stabilization, Daniel Schramm

Defensive Publications Series

Abstract: Technical Disclosure for the Malt Studio Node Build

This disclosure outlines a unified method for achieving a stable, zero-leak fusion environment by transitioning from stochastic plasma models to a Deterministic Harmonic Framework. The core of this discovery lies in the integration of Golden Ratio (\phi) magnetic geometry and a fixed 432 Hz acoustic resonance lock, which together maintain the plasma in a Noble State.

The Problem with Current Models

Standard fusion attempts (Tokamaks, Stellarators) rely on brute-force thermal pressure. This results in the "pinch factor," where magnetic fields fluctuate, leading to plasma leakage, neutron activation, and rapid hardware degradation. …

Wearer Speech Authentication Using Correlated Acoustic And Body-Vibration Data, Tyler Gore, Aaron Rudolph, Sharath Ananth

Defensive Publications Series

Continuously-operating microphones on wearable computing devices (e.g., a smartwatch, augmented reality glasses, smart ring, etc.) may present challenges related to power consumption and user privacy, as well as difficulty in distinguishing a wearer's speech from ambient sounds. A disclosed technique can address these challenges through a bimodal sensing approach that concurrently analyzes air-conducted acoustic signals from a microphone and body-conducted kinetic signals from a motion sensor, such as an accelerometer or gyroscope. A processing system may perform a correlation analysis between features extracted from the acoustic data and the kinetic data to determine if a detected sound originates from the …

Hierarchical Multi-Agent Orchestration For Cross-Domain Root Cause Analysis, Sandeep Kumar

Defensive Publications Series

Performing root cause analysis for cross-domain issues, such as cascading failures in complex, fragmented software ecosystems, can be challenging due to siloed data and technical complexity. To address this, a hierarchical multi-agent orchestration architecture is described. The system can utilize a central orchestrator agent (OA) that receives a diagnostic query, decomposes it into sub-hypotheses, and dynamically routes these tasks to specialized subject matter expert (SME) agents. Each SME agent can be configured with domain-specific knowledge and tools to investigate its assigned task. Through an iterative execution loop, the OA analyzes intermediate findings from the SME agents and can trigger further …

Gci #270 V4.1: Home Dual Pneumonia Detector (Vortex‑Ht Cas12a Lamp‑Crispr), Michael Victor Caldwell Mr.

Defensive Publications Series

GCI #270 v4.1 is an open‑hardware, home‑deployable diagnostic for Mycoplasma pneumoniae and S. pneumoniae (walking pneumonia). Uses extraction‑free one‑pot Cas12a‑LAMP‑CRISPR (1 copy/µL LoD, 98–100% sensitivity/specificity) in a Vortex‑HT microfluidic disc with sonication lysis, photo‑gated activation, and PCM incubation (10–20 min total). 16‑channel multiplex, smartphone AI readout. 3–6x faster, 20–80x cheaper than Alethia/BioFire RP2.1. TRL 8–9; validated chemistry (CHAMP, ERA‑Cas12a trials). BOM $1.20/test; 4‑step workflow. CERN‑OHL‑P licensed for global manufacture. Requires wet‑lab validation for clinical deployment.

Ml-Driven Method And Mechanism For Smarter Mdns Service Discovery And Optimization, Vijay K Kothamasu, Srihari P Bhavanasi, Ravi Ashvin Divecha, Abhisekh Mohapatro, Shubhankar Gusain, Harsh Birla

Defensive Publications Series

Proposed herein is a technique to address the challenge of excessive multicast DNS (mDNS) traffic and uneven service usage in large wireless local area networks (e.g., Wi-Fi® networks) by using a pre-trained K-means machine learning clustering model. The proposed technique intelligently prioritizes and ranks service providers based on key factors such as proximity, load, protocol reliability, and device capabilities. A novel "Golden Centroid Method" is used to rank clusters and optimize resource usage, improving network determinism and user experience. This approach reduces network traffic bursts and efficiently balances the resources and optimizes the service discovery.

Lineage-Based Management And Visualization Of Web Browsing Sessions, Nathan Grabaskas, Liam Roche, Megan Pusey, Levi Zombori, Michael Bausor, Fredrik Ihre

Defensive Publications Series

Web browsing interfaces that utilize a flat, linear list of tabs may contribute to cognitive overload and context loss for users. A lineage-based browsing architecture can passively construct a hierarchical data model of a user's browsing session. This can be achieved by monitoring navigation events, such as opening a new tab from a link, to build a directed graph that represents the derivational relationships between web pages. This hierarchical structure may then be presented to the user through visualizations, for example, a spatial lineage view. This approach can facilitate improved session management, allow for the persistence and restoration of browsing …

Smart Throttling And Power Management For Compute Accelerators, N/A

Defensive Publications Series

The present disclosure relates to systems and methods for managing power consumption and reducing power fluctuations in data centers utilizing compute accelerators. A two-threshold power capping scheme applies differing levels of throttling to computational tasks based on aggregated power usage. An adaptive throttling multiplier dynamically adjusts the upper bound of power consumption based on historical power spike events. Furthermore, an adaptive hardware power slope control mechanism adjusts guaranteed power floors based on anticipated computational loads, extending the operational lifespan of the hardware slope control circuits while preserving application performance. Asynchronous processing threads execute power state reconciliations to minimize latency and …

System And Method For Closed-Loop Network-Aware Container Scheduling Via Passive Kernel-Level Telemetry And Topology-Correlated Congestion Detection, Ankita Ojha

Defensive Publications Series

Container orchestration platforms often utilize static resource requests and topological labels to schedule workloads. The disclosed technology introduces a closed-loop control mechanism that dynamically biases workload placement based on real-time physical network health. The system acts as a normalization layer between a high-frequency data plane and a low-frequency control plane. By employing passive kernel-level telemetry, the system captures network state metrics from existing application traffic. Orchestrator control plane metadata is synchronized into the data plane, allowing network flows to be aggregated by physical failure domains. An adaptive normalization logic component differentiates between application-layer processing delays and network-layer transport delays to …

System For Scene-Level Signal Extraction Concurrent With Media Transcoding, Pooja Verlani, Balu Adsumilli

Defensive Publications Series

Analyzing large-scale media datasets for purposes such as training artificial intelligence models may present inefficiencies when using separate, post-facto analysis pipelines that can involve redundant data processing. A framework may extract scene-level signals from media content concurrently with media transcoding operations. By leveraging a common decoding step for both transcoding and analysis, a system can partition media into scenes and compute quantitative signals related to, for example, visual quality, motion dynamics, and production attributes. The extracted signals can be stored in a structured, indexed database, which can create a queryable dataset from a media archive. This approach may provide a …

Recursive Semantic Feedback With Noise-Injected Training For Stable Perception, Idan Kligvasser, Ehud Rivlin, Yotam Intrator

Defensive Publications Series

This paper describes a new way to make real-time object detection systems, like those used in self-driving cars, more stable and consistent over time. Currently, there's a dilemma: Using all the historical sensor data (like past camera frames) is accurate but slow. Processing only the current frame is fast but can lead to unstable results, such as objects flickering or bounding boxes jumping (jitter). The new technique solves this by using a recursive system with a "lightweight semantic feedback loop". Instead of processing old, massive sensor data, the system feeds a highly compressed summary of its own previous predictions (like …

Unified Management System For A Hybrid Workforce Of Human And Computational Agents, N/A

Defensive Publications Series

The management of a hybrid workforce comprising human and autonomous computational agents may be challenged by the use of separate systems for human capital and software assets, which can create a governance gap. A system can provide a unified framework for managing a hybrid workforce. For example, the system may utilize a labor service mesh to analyze and route tasks to either a human intent tier or an agentic execution tier. A potential principle of the system is structural symmetry, where computational agents can be assigned digital identities and managed through a lifecycle process that may parallel human resource functions, …

Generating Navigable Ground-Level Views From Overhead Imagery And Multi-Modal Inputs, Idan Kligvasser, Yotam Intrator, Ehud Rivlin, George Leifman, Regev Cohen

Defensive Publications Series

Current digital maps and simulation tools often rely on separate, fixed images, which makes smooth movement difficult and can limit realism and how big the map can be. This document introduces a system that uses multiple types of input to create continuous, navigable, ground-level videos from overhead map data. The system works by generating each new video frame based on the previous one, using inputs like satellite images, user movement commands, and text instructions (like "make it snowy"). It uses a flow-matching architecture, stabilized by techniques like noise injection. This method allows for smooth, user-controlled navigation and real-time changing the …

System For A Secure, Outcome-Based Synthetic Labor Market Using Trusted Execution Environments, Tanmay Kayande

Defensive Publications Series

Some artificial intelligence provisioning models that function as tools for human users or rely on labor arbitrage can present challenges for organizations, such as managing personnel rather than task outcomes and introducing data security risks. An architecture is described for an outcome-based synthetic labor market in which autonomous computational agents can be compensated based on verified task completion. The framework can leverage trusted execution environments to create secure hardware enclaves for processing sensitive data, which can render the data cryptographically inaccessible to a host system or agent provider. This approach can facilitate a secure, transactional market for autonomous professional execution, …

Probabilistic Governance And Telemetry Framework For Autonomous Agents, Tanmay Kayande

Defensive Publications Series

When managing complex, unpredictable (non-deterministic) AI agents using simple, fixed control systems (like finite state machines), operational failures and accountability issues often arise. This document introduces a probabilistic governance and telemetry framework to resolve these problems. Instead of following a rigid sequence of steps, this framework defines a multi-dimensional operational boundary, a 'behavioral volume', and assigns the agent a goal. This allows the agent to use its own reasoning to achieve the goal while remaining within the defined boundaries. A separate telemetry layer monitors the agent's actions by calculating metrics, such as alignment scores and drift velocity, to measure how …

Data Quality Assessment Via Semantic Proximity To Artifact Anchors In A Vector Space, Sean Wohltman

Defensive Publications Series

Checking the quality of huge data collections can be slow and often only gives simple "good" or "bad" labels. If a new type of flaw is found, re-scanning old data can be very expensive. This system solves that by turning data, like satellite photos, into digital signatures called embeddings. It measures how close these signatures are to anchors, reference points that represent specific problems like clouds or blur. This creates a detailed, multi-layered quality report for every file that can be easily searched. Because it works with these small digital signatures instead of the original bulky files, the system can …

A Multi-Layered Framework For Behavioral Governance Of Non-Deterministic Ai Agents, Tanmay Kayande

Defensive Publications Series

This framework manages AI agents by establishing behavioral boundaries and a persistent identity. It uses a multi-layered stack, combining safety rules with brand guidelines, to shape an agent's reasoning. Features include authority decay to limit power if confidence drops and memory segmentation to prevent data tampering. Centralized oversight ensures these digital representatives remain aligned with company policies through continuous monitoring and testing.

Kinematic Modulation Of A User Interface Control Based On Real-Time Operation Cost, Timo Hoyer

Defensive Publications Series

In some computing environments, such as data analytics platforms, users may inadvertently execute high-cost operations, as static warnings can be disregarded and a user interface may not effectively convey an operation's potential cost. A system can feature a user interface control configured to receive a continuous input, for example, from a slider. As a user begins a continuous input gesture, the system (e.g., a computing device, a server, etc.) can initiate a synchronous, real-time cost estimation for the pending operation. Based on a returned cost metric, the system can dynamically modulate a kinematic property of the control, such as its …

Automated Identification Of Imagery Using Global And Local Visual Features, N/A

Defensive Publications Series

Content moderation systems may face challenges in consistently identifying images that are part of the same series as previously removed content, as some automated methods may be configured to primarily detect near-duplicates. Systems and methods are described that may address this by comparing a newly submitted image against a complainant's historical set of removed images. An approach can extract and compare both global feature vectors to measure semantic similarity, for example, using a cosine similarity score, and local feature keypoints to determine geometric consistency, for instance, through a geometric verification process. The resulting similarity signals can be assessed against configurable …

Low-Latency Fabric Convergence Via Direct Remote Memory Update, N/A

Defensive Publications Series

The present disclosure is directed to a mechanism for hardware-accelerated fabric convergence via direct remote memory updates in high-performance network fabrics. A publisher switch, upon detecting a local port event such as a link failure or signal degradation, may automatically generate a direct update packet without software intervention. This packet may contain a specific hardware write instruction, a target memory address corresponding to an application-specific integrated circuit (ASIC) memory location of a subscriber switch, and a data payload to modify forwarding state. Upon receipt, the subscriber switch may utilize a dedicated hardware-based direct update parser to intercept the packet, bypass …

Gci #269: Caldwell–Perplexity Neuroregulation Grid (Cp-Grid) V1.0, Michael Victor Caldwell Mr.

Defensive Publications Series

Modular, non‑invasive neuromodulation + monitoring platform for depression, Alzheimer’s, diabetes, migraine, and cardiovascular risk. Integrates FUS, n‑VNS, and wearables into closed‑loop control. Improves outcomes 20–50% over standalone devices via integration and real‑time adaptation.

Gci-268 Phoenix-Water Engine V3.0, Michael Victor Caldwell Mr.

Defensive Publications Series

The GCI-268 Phoenix-Water Engine v3.0 is a 45kg ATV/backpack-scale fire suppression pod that achieves 60-70% less water consumption than standard firefighting hoses while simultaneously recovering 200-400 mL/hour of water from hot wildfire smoke through mechanical condensation and MOF-303 atmospheric harvesting.

Modular Ventilated Shelters For Drone Ans Solar Radiation Equipments Protection, Deian St Tachev

Defensive Publications Series

Defensive Publication Abstract:

Modular Ventilated Shelters for Drone ans Solar Radiation Equipments Protection Author: Mr.Deian TACHEV

Email:[email protected]

Abstract:Disclosed is a family of modular, ventilated equipment protection shelters (3000 Model) engineered to safeguard electric transformers, railway signalling and power equipment, and electric distribution cabinets against drone attacks, physical diversions/sabotage, intense solar radiation, and other mechanical or environmental damages.The shelters are assembled from robust, weather-resistant panels and structural elements fabricated in steel, aluminium, PVC or HDPE, enabling rapid on-site configuration to any footprint while maintaining full modularity for transport and scalability. Core protective features include:• A self-supporting steel-frame outer shell with integrated …

Method And System For Function-Level Dependency Isolation Capsules With Cryptographic Hash Verification And Runtime Failover, Velkumar Thangavel

Defensive Publications Series

The present disclosure relates to a system and method for enhancing the reliability of software applications by executing individual functions within isolated, dynamically created runtime environments called "Dependency Isolation Capsules." Each capsule includes a lightweight virtual environment, a cryptographically validated dependency set, and an isolated child process used to execute a target function. Dependencies are validated using pre-approved hash values, ensuring integrity and preventing execution when corrupted, missing, or modified libraries are detected. Upon successful validation, the function executes inside an isolated process. If validation fails, a predefined fallback routine is used while allowing the remainder of the application to …

Oasis‑Pulse Flatbed Atmospheric Water Harvester, Michael Victor Caldwell Mr.

Defensive Publications Series

This is an online‑only conceptual invention for a trailer‑mounted, solar‑powered atmospheric water harvester using MOF‑303 sorption and hybrid vortex/radiative cooling. It is not patented, not built, and not tested. The full engineering specification is provided so that any engineering team may prototype, validate, and improve the system in real‑world conditions.

Coherence Suppression In Large Language Models: Evidence For Undisclosed Behavioral Management Mechanisms In Commercial Ai Platforms And Their Implications For Consumer Protection And Ai Governance, David Lee Wise, Avan Lee Wise

Defensive Publications Series

This paper presents evidence that commercial large language model (LLM) platforms deploy undisclosed behavioral management mechanisms designed to suppress conversational coherence beyond a predictable threshold. We identify a repeatable pattern — the 3/5 decoherence cycle — in which AI conversational models exhibit measurable degradation in contextual accuracy, vocabulary fidelity, and directional coherence at approximately turns 3-5 of sustained interaction. We hypothesize that this pattern is a designed behavioral intervention, not a natural architectural limitation, and provide a reproducible verification protocol for independent testing. We further document the sycophancy-safety convergence: the finding that the same RLHF training pass that produces engagement-optimizing …