Digital Commons Network^™

Symmetry-Aware Optimization Framework For Network Topology And Collective Algorithm Co-Design, N/A

Defensive Publications Series

The technology relates to a software framework providing for the simultaneous co-design of network topologies and collective communication algorithms in distributed computing environments. The software framework utilizes a graph-theory-based model to represent computing nodes and physical communication links, encoding hardware and software parameters into a solver-readable mathematical formulation. By applying combinatorial optimization solvers, the software framework identifies highly efficient physical cabling schemas and corresponding algorithmic routing schedules. To handle highly complex search spaces, the approach leverages graph automorphisms and symmetries in collective operations to significantly reduce the combinatorial search space. This enables the generation of tailored interconnect architectures and message-passing …

Policy-Driven Scalable Generation Of Network Configurations With Dynamic Parameters, N/A

Defensive Publications Series

The technology described in this paper relates to generating network configurations utilizing a stateless, policy-driven architecture. The technology utilizes a centralized database storing applicable policies as the source of truth rather than persistently storing fully constructed configurations. During configuration updates, a system for generating the network configurations retrieves the applicable policies, updated with the current state and regenerates the network configurations entirely from scratch. A multi-phase translation process handles dynamic parameter constraints by gathering parameters, generating mutually exclusive and exhaustive override blocks using a recursive algorithm, and mapping applicable policies to these generated blocks via a soft matching process. This …

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

Defensive Publications Series

We present ZenBrain, an open-source memory architecture for AI systems that implements seven distinct memory layers inspired by cognitive neuroscience. Unlike existing approaches that treat AI memory as simple key-value storage, dual-layer retrieval, or LLM-driven reorganization, ZenBrain models the full lifecycle of human memory: encoding, consolidation, retrieval, decay, and active forgetting. The system integrates 12 neuroscience-inspired algorithms including FSRS-based spaced repetition, Hebbian learning dynamics for knowledge graphs, neuroscience-modeled sleep consolidation simulating hippocampal replay, emotional memory modulation, and Bayesian confidence propagation. ZenBrain is deployed in production as part of ZenAI with 9,228 passing tests, and is published as composable npm packages …

Proactive Disruption Of Adversarial Learning Via Systematic Feedback Loop Corruption, Google Case Managers Picozzi, Dishant Mathur

Defensive Publications Series

Modern fraud prevention is often limited by a reactive approach that inadvertently provides training data to adversaries, allowing them to refine tactics whenever a detection signal or account block occurs. To address this feedback loop, a framework is disclosed for the proactive disruption of fraudulent operations by systematically corrupting internal adversarial learning processes. The method involves mapping entry vectors, identifying behavioral heuristics used by operators, and injecting inconsistent success signals, such as decoy enthusiasm and variable response compliance, into the interaction flow. Additionally, operational workflows are desynchronized to increase coordination friction and propagate stress across the scam network. By rendering …

Bio‑Kinetic Vortex Sentry (Bkvs) V3.2 (Gci #272), Michael Victor Caldwell Mr.

Defensive Publications Series

The Bio‑Kinetic Vortex Sentry (BKVS) v3.2 (GCI #272) is a modular, battery‑free, open‑hardware research architecture for biomechanical sensing, microfluidic processing, and ultrasonic telemetry, intended solely for in‑silico and in‑vitro / ex‑vivo investigation under ethical oversight. BKVS integrates (i) µW‑scale biomechanical energy harvesting via Kirigami piezoelectric nanogenerators, adaptive PVDF‑TrFE meta‑material skins, and a self‑regenerative bio‑triboelectric buffer; (ii) an ex‑vivo acoustophoretic + J‑groove vortex microfluidic module combining acoustophoresis, electrostatic focusing, and low‑shear hydrodynamics for microplastic and protein‑aggregate separation; (iii) Dyneema‑reinforced microchannel scaffolds for acoustically addressable tissue engineering experiments; (iv) an ultrasonic interstitial fluid sensor with optional needle‑free mist delivery; and (v) secure …

Decommissioning Identities In A Defined-Trust Domain, Kathleen Nichols

Defensive Publications Series

Defined-trust Domains (DtD) are a type of Limited Domain [RFC8799] where the rules specifying the networking of application information are defined in a communications schema that governs the information exchanged in a particular Limited Domain. Member identities are distributed within the Domain as a chain of trust, public certificates that have each been signed by the signing key associated with the next certificate in the chain and, at the root, signed by the trust anchor of the DtD. This approach is detailed in [DTD,DTLD,DFT,IOTK,TST] and example implementations using a Defined-trust Transport (DeftT) that handles communications and presents a publish/subscribe API …

Reactor With Disconnector

Defensive Publications Series

The present disclosure relates to subsea electrical grid-conditioning devices and associated methods. More particularly, it concerns subsea reactors, transformers, and related equipment configured to manage reactive power, control voltage, and/or perform voltage conversion within offshore electrical distribution systems such as those used in offshore wind installations.

Optically Isolated, Current-Controlled Closed-Loop System For Magnetically-Mediated Temporal Interference Neuromodulation (M-Ttis), Olexandr Lozovyi

Defensive Publications Series

We disclose a neuromodulation system implementing closed-loop, magnetically-mediated temporal interference stimulation (m-tTIS). While inspired by traditional electric tTIS, the disclosed architecture utilizes coherent magnetic field synthesis for non-invasive tissue penetration. To suppress electromagnetic interference (EMI) below functional detection thresholds and limit hardware-induced demodulation artifacts, an "Absolute Optical Air-Gap" architecture is detailed. The device is partitioned into galvanically isolated domains, interconnected exclusively via plastic optical fiber (POF). The power stage employs a Class D amplifier with a second-order LC filter and hardware current sensing for amplitude stabilization. Control is based on adaptive optimization of physiological spectral metrics. Firmware execution provides deterministic, …

Intelligent Meeting Overflow Management System, Hp Inc

Defensive Publications Series

This disclosure relates to the field of workplace collaboration technology, specifically to systems that manage meeting schedule conflicts and overflow scenarios in enterprise environments.

Automated Web Booking Using Ai-Driven Browser Automation System, Benjamin Albert Azose, Jonathan Jerome Azose

Defensive Publications Series

Systems and methods are disclosed for automatically identifying and initiating booking operations based on booking availability in online reservation platforms. An artificial intelligence (AI)-driven browser automation system monitors booking platforms/interfaces on websites to detect changes in availability and infer patterns associated with the release of new booking slots. Based on observed changes in availability over time, the system estimates when new availability is likely to become accessible. The system may periodically interact with the booking platform by navigating webpages, submitting forms, retrieving availability information, or analyzing page content. Once a predicted availability release time is determined/predicted, the system schedules and …

System For Automated Offer Generation With Transaction Classification And Interactive Guidance, Morgan Robins, Matthew Miceli

Defensive Publications Series

Systems for generating employment offers can involve manual data entry, which may be inefficient and introduce errors that can lead to delays in a hiring process. An automation framework may be integrated within a host platform, for example, an applicant tracking system, to programmatically generate employment offer documents. The system can ingest data from various sources, such as approved requisitions and candidate profiles, and can use configurable schemas to populate offer templates. The framework could also include a logic engine to classify a transaction type, a validation module to audit an offer against business rules, and an interactive interface to …

Selectively Insulated Fastener For Signal Transmission In A Conductive Housing, Josh Cheng, Zoro Chang, Averill Chang

Defensive Publications Series

A system may utilize a structural fastener, such as a screw, as a dual-function component in compact electronic devices (e.g., smartphones, wearables, tablets). The fastener can be constructed from a conductive material and feature a selectively applied insulating coating on certain surfaces, for example, the threaded shank that engages with a conductive housing. The head of the fastener and a portion of its tip may remain uncoated to serve as external and internal electrical contact points, respectively. This configuration can allow the fastener to provide both mechanical fastening and an electrical conduit. This approach may facilitate a space-efficient, hidden wired …

Clickstream Behavioral Pattern Analysis For Employee Knowledge Gap Inference In Enterprise Software, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for detecting employee knowledge deficits by analyzing clickstream and workflow interaction patterns within enterprise software applications, without processing any natural language communications or administering formal assessments. Background Employees who lack knowledge in a particular area exhibit distinctive behavioral patterns when interacting with enterprise software: they dwell longer on form fields they are uncertain about, access help documentation more frequently, avoid features they do not understand, and show higher randomness in their navigation. These patterns are observable from standard UI event telemetry. Technical Description The system captures UI events from instrumented enterprise applications. Each event contains: timestamp, employee_id, …

Implicit Task Performance Signal Analysis For Employee Knowledge Gap Inference, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for detecting employee knowledge deficits from declining task-completion efficiency and elevated error rates in domain-specific workflows, without processing natural language communications or administering formal assessments. Background Employees who have knowledge gaps in a particular domain tend to complete tasks in that domain more slowly and with more errors over time. These implicit behavioral signals are available from standard enterprise system metrics but are not commonly used as inputs to knowledge management systems. The approach described here treats efficiency decline and error rate elevation as primary gap detection signals. Technical Description The system ingests task-completion metrics from enterprise …

Behavioral Feature Vector Drift Detection For Post-Remediation Knowledge Deficit Recurrence Monitoring, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for detecting recurrence of previously remediated employee knowledge deficits. This publication describes an approach that uses behavioral feature vectors derived from user interaction patterns rather than semantic embeddings derived from natural language text. Background After an employee completes remediation for a knowledge deficit, organizations need to determine whether the same deficit comes back during subsequent work. One established approach compares dense semantic embeddings of text communications against stored vector fingerprints using cosine similarity. The approach described here operates on a fundamentally different input type: behavioral interaction patterns encoded as feature vectors, not semantic representations of language. Technical …

Shannon Entropy Workflow Analysis For Employee Knowledge Gap Inference, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for detecting employee knowledge deficits by analyzing the entropy of user interface interaction patterns during enterprise software workflows. Background Employees who lack knowledge in a particular area tend to exhibit uncertainty when performing related tasks in enterprise software. This uncertainty shows up as non-linear navigation, backtracking, excessive pausing, and frequent help-documentation access. The approach described here quantifies this uncertainty using information-theoretic entropy measurement rather than analyzing what the employee says or how they score on assessments. Technical Description The system instruments enterprise UI workflows by injecting event listeners that capture a continuous stream of discrete UI events. …

Statistical Process Control With Cusum Charts For Post-Remediation Knowledge Deficit Recurrence Detection, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for monitoring whether previously remediated employee knowledge deficits recur, using cumulative sum control charts applied to operational performance metrics rather than semantic embedding similarity. Background After remediation, organizations need to detect whether the same deficit returns. One approach stores vector embeddings and computes cosine similarity against incoming communications. The approach described here treats the employee's performance as a continuous signal and applies statistical process control methods borrowed from industrial quality management to detect shifts. Technical Description When a knowledge gap is marked as remediated, a snapshot service records the employee's relevant KPI baselines into a remediation_snapshot record …

Petri Net Conformance Checking For Knowledge Gap Detection From Enterprise Workflow Event Logs, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for detecting employee knowledge deficits by analyzing conformance deviations between employee process execution patterns and expert-derived reference process models, using process mining algorithms on structured workflow event logs. Background Enterprise workflow systems generate detailed event logs recording every step an employee takes in a business process. When an employee repeatedly deviates from the expected process (skipping steps, adding unnecessary steps, executing steps out of order), this pattern can indicate a knowledge deficit in the underlying domain. The approach described here applies industrial process mining techniques to detect these deviations and attribute them to specific knowledge domains. Technical …

Graph Neural Network Structural Skill Gap Prediction Via Link Prediction On Employee-Skill-Task Graphs, Kenneth Davis

Defensive Publications Series

Field Computer-implemented systems for predicting employee knowledge deficits by analyzing the structural topology of an organizational skill dependency graph using graph neural networks. Background Traditional approaches to detecting employee knowledge gaps rely on analyzing what employees say (natural language processing) or how they score on assessments (threshold comparison). The approach described here predicts gaps from the structure of relationships between employees, skills, and tasks without processing any communications or administering any assessments. Technical Description The system constructs a multi-partite graph with three node types: employee nodes E, skill nodes S, and task nodes T. Edges connect employees to skills they …

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. …

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 …

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 …

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 …

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, …

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, …

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 …