Digital Commons Network^™

Remote Display Spatial Pointing Using Processed Inertial Sensor Data From A Mobile Device, Chien-Feng Yu, Pei-Yu Chen, Eusden Lin, Shang Wei Lin, Dewita Sonya

Defensive Publications Series

A mobile computing device (e.g., a smartphone, smart watch, wearable device, augmented reality glasses, etc.) may function as a spatial pointer for a remote display by processing data from an on-board inertial measurement unit. An on-device spatial engine can translate the device's physical orientation and movement into two-dimensional screen coordinates. This translation process may, for example, involve techniques such as isotropic aspect ratio correction and a dynamic motion amplification layer that adjusts sensitivity based on angular velocity. The processed coordinates can then be streamed to the remote display over a low-latency network protocol. This approach may provide improved cursor control …

Fully Isolated Floating Nut Terminal Block For 3-Phase High Voltage Systems

Defensive Publications Series

In electric vehicle (EV) powertrains, establishing robust electromechanical connections between the inverter and the electric motor's stator busbars (U, V, W phases) is critical. Traditional terminal blocks utilize a fixed-type geometry that cannot account for manufacturing and assembly tolerance variations. This rigidity introduces severe mechanical stress into the busbars, potentially leading to material fatigue, weld failures, and fluid leakage at the inverter’s overmolded housing seals. This proposed solution discloses an innovative, fully isolated floating nut terminal block. By integrating floating threaded subassemblies within a polyphenylene sulfide (PPS) overmolded bracket containing specific hexagonal grooves, the system allows multi-axis movement to absorb …

Macroscopic Momentum-Space Tomography: Utilizing High-Z Cryogenic Target Arrays As Resonant Phase-Retrieval Lenses For Substrate Interferometry, Christopher L. Eckes

Defensive Publications Series

This paper introduces a formal engineering architecture to transition the Dimensionally Extended Holographic Projection (DEHP) model from numerical simulation to empirical instrumentation. Integrating the spatial phase-retrieval mechanics of 3D Photoemission Orbital Tomography (3D-POT) with the high-density containment engineering of deep-underground liquid xenon detectors, we outline a method for a macroscopic momentum-space microscope. Rather than treating the September 1, 2026 LUX-ZEPLIN 248 keV anomaly as an exogenous particle collision, we demonstrate that a high-Z condensed target array can function as an active, resonant phase-retrieval lens. We provide the complete mathematical tensor frameworks, specific material specifications, and structural engineering steps required to …

Detecting Scan Flop State Corruption During A Functional-To-Scandump Mode Transition Using Parallel Seed Initialization And Comparison, Sunder Garg, Prakash Narayanan, Krunal Siddhapathak, Shivam Sharma, Mayank Parasrampuria

Defensive Publications Series

During silicon debug, a system-on-chip (SoC) captures its internal sequential state through a scan-based extraction step, referred to as Scandump.  Moving the design from functional operation into Scandump mode is an asynchronous event, where a glitch on a reset or clock signal can toggle sequential elements and corrupt the captured state.  This document describes a verification method that freezes the design with a global clock-stop signal, writes a known random seed in parallel into the scannable flip-flops (scan flops) as value A, moves the design into Scandump mode, and samples the resulting flop state in parallel as value B.  Comparing …

Machine‑Learning Estimation Of Static Ir Drop In System‑On‑Chip Power Grids Using Gradient‑Boosted Regression And Image‑To‑Image Translation, Prateek Pendyala

Defensive Publications Series

Designing the power delivery network of a system‑on‑chip (SoC) involves repeated changes to the layout and to the power grid, and engineers conventionally re‑evaluate each change with a commercial static current‑resistance (IR) drop analysis.  These analyses can run from tens of minutes to several hours across many compute workers, which lengthens each design iteration.  This disclosure describes a machine‑learning approach that estimates per‑node static IR drop for multi‑million‑node power grids from electrical and spatial features of a design database.  The approach provides two complimentary techniques: a gradient‑boosted decision‑tree regression that predicts incremental IR drop from extracted power and resistance features, …

Early Prediction Of Design‑Rule‑Check Violation Hotspots From Placement‑Stage Congestion Feature Maps Using A Fully Convolutional Network, Prateek Pendyala

Defensive Publications Series

In the physical design of a system‑on‑chip (SoC) layout, design‑rule‑check (DRC) violations often appear late, during detailed routing (a stage that can take days to complete and that may trigger repeated placement adjustments).  This document describes a method that estimates where DRC violation hotspots may gather earlier in the process, working from feature maps that become available after placement and global routing.  The method arranges these maps (macro regions, cell and pin densities, rectangular uniform wire density (RUDY) maps, and routing congestion) as multi‑channel two‑dimensional inputs to a fully convolutional network (FCN) built as a multi‑scale encoder‑decoder with skip connections …

Predictive, Time‑Scaled Scheduling Of Concurrent Workloads For Power And Thermal Management In A System On A Chip, Mohsen Heidarinejad, Farid Kenarangi, Arpit Mittal, Amin Khajeh

Defensive Publications Series

A system on a chip (SoC) that runs several workloads at the same time can experience uneven power draw, localized heating, and reduced responsiveness when it relies on a fixed policy that treats the die as uniform.  This document describes a closed‑loop framework that observes on‑die temperature and power, estimates power for subsystems without direct sensors, and predicts near‑term spikes and longer‑term demand from queued work.  Using these estimates, the framework stretches or compresses task timelines and recommends per‑subsystem power caps, which a control layer applies through operating‑point adjustment, clock and power gating, and task migration.  A supervisory layer then …

When The Protocol Decides - Replay-Ready Infrastructure For Programmable Financial Institutions, Deepak Aggarwal

Defensive Publications Series

The rails are becoming intelligent. The governance frameworks developed to manage them remain as before. In the ASEAN+3 group, the financial infrastructure stack is undergoing redesign, starting from the message layer upward. Project Nexus connects national payment systems at near-real-time speeds. ISO 20022 incorporates compliance controls within the financial messages themselves. Project Agorá brings programmable settlement to a distributed ledger. AI is parsing liquidity, fraud, identity, and credit information even before humans can see the information.

This paper presents a simple yet powerful illustration of its main thesis: One decision, three jurisdictions, seven seconds. Decision chains start unfolding themselves at …

The Irrecoverable Institution - Why Replayability - Not Explainability - Is The Governance Standard For Agentic Banking, Deepak Aggarwal

Defensive Publications Series

Financial institutions have accelerated the deployment of Agentic AI systems. These systems have the capabilities to make decisions and are operating faster than any governance mechanism can respond. However, when such decisions go wrong, the biggest cost incurred is not due to their very first mistake, but because the financial institution lacks the capability of replaying and governing the decision path until other costs increase significantly.

The objective of this paper is to propose Decision Replay as the base governance framework for agentic financial institutions, which would be the capability to replay and govern decisions at any moment, via any …

Banking Rewired - Reimagining The Future Of Banking In A Protocol-Driven World, Deepak Aggarwal

Defensive Publications Series

The World is Changed. Has Your Bank?  

A fintech executive in New York, USA. An AI researcher in Amsterdam, Netherlands. An MSME owner in Bengaluru, India. Each of them interacts with money not by logging in but living. Money flows, credit adjusts, identity streams, and ethics calculate, all ambiently, intelligently, and consent driven. Not science fiction. This is the shape of banking in a  programmable world. Banks are at a crossroads. The question is no longer: "How digital are we?" It is: "How programmable, ethical, and modular is our institution?"

Four Strategic Shifts Redefining the Future Bank

1. From Platform …

System And Method For Elemental Decomposition-Based Provenance Attribution Of Ai-Generated Audio, Eric Zavesky

Defensive Publications Series

A system and method determine whether a candidate audio catalog contributed to the training of a generative audio model. An elemental encoder decomposes generated audio and catalog items into elemental embeddings corresponding to aesthetic elements including melodic contour, harmonic progression, rhythmic pattern, and timbral palette. A segmentation engine defines regions of the generated output for scoped analysis. Within each element independently, instance-level scores compare output regions against catalog items while distribution-level alignment compares the catalog's element distributions against distributions over model-generated outputs relative to a reference set. A multi-order analyzer scores recurrence patterns, including motif persistence. A provenance scorer combines …

Localized Generation Of Privacy-Preserving Ambient Chronicles, Karl Tao, Gaurav Arora

Defensive Publications Series

A system is disclosed for generating a localized activity chronicle within a private environment. Local cameras capture sparse static snapshots of room environments over a local network. A local smart hub platform receives each snapshot directly into an ephemeral, volatile memory buffer. An on-device vision model, such as a quantized vision-language model executed by a local hardware neural processing unit or other local processing resource, processes the snapshot to generate a time-stamped natural-language description of activities within the private environment. Immediately following text generation, the raw snapshot is purged from the volatile memory, preventing raw image data from being stored …

Wearable Apparatus Configured For Ambient Marker Sensing And Application Actions, Carlos Henrique Esteves Mendonca, Joost Korngold

Defensive Publications Series

Transactions involving physical objects often require manual interaction with a mobile device, such as opening a camera application to scan a visual marker, resulting in an interruptive and multi-step process. A wearable extended reality apparatus or device (e.g., smart glasses) is described that may be configured for hands-free processing of digital transactions. The device can use an ambient camera to sense visual markers in an environment. To establish user intent, a dwell mechanism may evaluate gaze duration before triggering a secondary image capture. The device is configured to decode a uniform resource identifier from the visual marker and link to …

Ai-Driven Browser Automation System For Attribute-Based Resource Access, Benjamin Albert Azose, Akancha Murlidhar Gupta, Theodore Thomas Olsauskas-Warren

Defensive Publications Series

An AI-driven browser agent framework is disclosed to facilitate attribute-based access to resources by enabling resource access decisions based on user or account characteristics rather than transferable authorization mechanisms. With user permission, the framework allows a browser agent to communicate user credentials, selected eligibility-related information requested by a resource provider for evaluating predefined eligibility criteria associated with a requested resource. Based on the evaluation, the browser agent may be granted immediate access to a resource acquisition workflow, assigned access at a future date or time, placed into a waiting queue, or denied access. By supporting multiple communication mechanisms, coordinated admission …

Cross-Surface Ad Narrative Orchestration Using Llm Sequential Reasoning With Engagement-Responsive Story Branching, Tamar Yakar, Ilia Labzovsky, N/A

Defensive Publications Series

A system orchestrates stateful, multi-chapter advertising narratives across different digital platforms within real-time bidding environments. The system separates the ad-serving process into an asynchronous control plane for computationally intensive planning and a synchronous data plane for low-latency auction execution. The asynchronous control plane uses a large language model (LLM) to generate a narrative directed acyclic graph (NDAG) that defines a story arc with branching logic based on potential user engagement. The system then compiles this narrative graph into a deterministic state transition matrix for execution at the network edge. To track user progression, the synchronous data plane uses a compact …

Deterministic Multi-Domain Computational Framework For Bi-Ionic Propulsion And Thermoelectric Resonance (Stalwart V18.1), Daniel Schramm

Defensive Publications Series

This paper details the mathematical and computational architecture of a multi-domain physics engine designed to validate interrelated aerospace systems, specifically bi-ionic vector thrust and solid-state thermoelectric energy recycling. To eliminate computational hallucination and enforce strict physical boundaries, the engine is constructed utilizing highly deterministic Python libraries: SciPy for immutable, universally accepted physical constants; SymPy for strict, symbolic equation rendering and mathematical proofs; and NumPy for continuous spatial array generation. This framework interlinks discrete physical phenomena (magnetic containment, plasma gyration, kinetic wave damping, and thermal energy harvesting) into a singular, codependent mathematical ecosystem. The novel contribution is the Master Resonance Equation …

Physical Oracles And The Instrumental Status Of The Terrestrial Biosphere, Volodymyr Kotegov

Defensive Publications Series

This document develops a general instrumental framework for evaluating physical systems that function as oracles — systems capable of generating high-dimensional observations on the actual physics of the universe, exhibiting substantial computational irreducibility, and producing data in measurement bases not yet fully formalized by the agent. Within this framework the terrestrial biosphere is analysed as the strongest currently known Slow Oracle.

Humanistic, ethical, and sentimental considerations are excluded. Evaluation proceeds solely in terms of expected utility, option value under residual uncertainty, basis diversity rent, thermodynamic opportunity cost, and resistance to model collapse. The central claim is that, while residual uncertainty …

Caldwell Hermes‑Awh V1.0 High‑Flux Enthalpy‑Recycling Modular Extraction System Open-Hardware, Build-And-Test Atmospheric Water Harvester For Low-Humidity Environments, Michael Victor Caldwell Mr.

Defensive Publications Series

Caldwell HERMES‑AWH is a modular, solar-regenerated atmospheric-water-harvesting system designed for low-to-moderate relative humidity, nominally 15–35% RH. The design addresses the major practical bottlenecks of conventional sorption-based atmospheric water harvesting: slow water-vapor diffusion into thick sorbent beds, adsorption heat that reduces uptake, poor thermal uniformity during regeneration, loss of desorbed vapor, incomplete condensation recovery, and low daily cycle count.

The system uses multiple thin structured sorbent cassettes, each carrying a 0.5–2.0 mm active sorbent layer on a thermally conductive backplane. Cassettes operate in sequential modes: ambient-air adsorption, thermal preconditioning, closed solar-thermal regeneration, vapor recovery and condensation, and cooling/reset. The system maintains …

System And Method For Statistical Modeling And Automated Lifecycle Refresh Detection Of Digital Media Assets, Manisha Arora, Yassine Idrissi, Bruno Caforio

Defensive Publications Series

A data-driven, statistically rigorous analytical framework is disclosed for determining performance decay and optimizing the replacement timing of digital media assets (such as images and videos) in digital media campaigns. The system ingests campaign-level and asset-level metrics on a daily basis and extracts high-dimensional visual and semantic embedding vectors from the media assets using a deep neural network feature extractor. A visual taxonomy is constructed by clustering similar assets into visual archetypes using K-Means clustering, allowing for aggregate fatigue analysis within specific thematic content clusters. The statistical decay engine fits a non-linear saturation model (e.g., a Hill function S-curve) to …

C++ Iterator Hardening Via Restriction Of Scripting Engine And Inter-Process Communication Execution, Kentaro Hara

Defensive Publications Series

Memory safety flaws, such as use-after-free vulnerabilities, are caused when collection structures are modified during active iteration loops. Modifications to an active collection structure are sometimes induced by unexpected execution of a scripting language engine or an inter-process communication mechanism, whereby dangling iterators are produced. To mitigate these flaws, a thread-local counter mechanism is disclosed. A counter within thread-local storage is modified across iterator lifecycle operations, including construction, copy construction, move construction, assignment, and destruction. Within a rendering process, execution of a scripting language engine is blocked via a process termination if a non-zero value is held within the counter. …

Caldwell W2g‑Vt V2.1 — Continuous Waste‑To‑Gasoline Refinery Using Molten‑Salt Cavitation Depolymerization, Halogen Scrubbing, Dual‑Bed Zsm‑5 Swing Catalysis, Venturi Ultra‑Fast Spray Quench, Ultrasonic Anti‑Fouling, Steam‑Stripped Heavy Bottoms, Optical Cavitation Feedback & Vortex‑Tube Instrument Cooling, Michael Victor Caldwell Mr.

Defensive Publications Series

This research project develops and validates a continuous‑flow waste‑to‑gasoline refinery capable of converting mixed waste plastics and organics into high‑octane gasoline (C₅–C₈, 91–95 RON) at 1.0 kg/s throughput.

The system integrates:

• Molten‑salt depolymerization (NaNO₃/KNO₃ at 450°C)

• Phoenix‑Cracker hydrodynamic cavitation (from your TDCommons inventions)

• Arachne‑NTC optical cavitation sensors (TDCommons)

• CaO/MgO halogen scrubbing

• Dual‑bed ZSM‑5 swing catalytic reactor

• Venturi direct‑contact spray quench (0.12 s)

• 28 kHz ultrasonic anti‑fouling

• Steam‑stripped heavy bottoms

• Vortex‑tube instrument cooling

• Light‑gas oxygen purge

• Fractionation and internal energy recovery

This document provides the full research theory, experimental plan, system diagrams, operating parameters, integration notes, and validation methodology required to …

Aquila-X 3.0: Modular High-Throughput Mobile Potable-Water Factory With Adaptive Pretreatment, Parallel Production Trains, Seawater Energy Recovery, Multi-Grade Outputs, And Concentrate-First Residual Management Research Conceptual Invention, Michael Victor Caldwell Mr.

Defensive Publications Series

AQUILA-X 3.0 is a transportable, modular, multi-barrier water-production platform designed to produce more independently verified potable water per deployable system than conventional mobile RO plants while maintaining safe operation, source-specific treatment, practical energy demand, maintainability, redundancy, and complete residual accountability.

The system does not depend on one miracle component. Its capacity comes from:

• Selecting the shortest safe treatment route for each characterized source.

• Removing grit, solids, oil, algae, and foulants before fine membranes.

• Using multiple independently isolatable production trains.

• Avoiding high-pressure RO when freshwater does not need desalination.

• Using dedicated high-pressure SWRO equipment and energy recovery when seawater does need …

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Notification String Optimization Using Reinforcement Learning And Llms, Sumit Kumar Jha, Ishan Gambhir, Shubham Kumawat

Defensive Publications Series

Current approaches to avoid the drop in engagement with notifications have a high overhead, are slow to roll out, and lack content personalization. This disclosure describes techniques, implemented with user permission, to automatically select and manage content for push notifications with an automated closed-loop self-healing personalized architecture. The approach can be implemented with a Contextual Multi-Armed Bandit (CMAB) Reinforcement Learning (RL) model with reward signals configured to trigger a Large Language Model (LLM) to generate, validate, and inject fresh personalized notification strings in the content pool. The pipeline to generate structured content to replace previously pushed notification content can be …

Vt‑Tce V1.0 — Standalone Buildable Disclosure Vortex‑Tube Thermal Conditioning Engine A Passive Hot/Cold Separation Thermal‑Conditioning System For Remote Energy Installations, Michael Victor Caldwell Mr.

Defensive Publications Series

VT‑TCE v1.0 is a builder‑ready, open‑hardware, standalone thermal‑conditioning engine based on:

• vortex‑tube hot/cold separation

• passive thermal routing

• synthetic‑coolant compatibility

• hot‑stream buffering

• cold‑stream electronics/sensor cooling

It is designed for remote energy installations, providing:

• cold‑stream electronics cooling

• hot‑stream thermal buffering

• auxiliary heat routing

• passive thermal stabilization

This version contains no external invention references and is fully buildable and testable by engineering teams.

Self-Exhausting Fleet-Level Failure Pattern Detection Via Persistent Graph Coloring And Human-In-The-Loop Validation, Nilay Gupta, Wayne W Chen

Defensive Publications Series

Techniques are proposed herein for detecting and validating recurring failure patterns across a fleet-scale corpus of causal event graphs. A pattern-discovery engine groups taxonomy-normalized node labels and categories, computes support as the number of distinct incident graphs containing a pattern, and classifies retained patterns into new taxonomy categories and known but unvalidated patterns. Engineers confirm or reject ranked patterns through a human-in-the-loop workflow. Confirmed patterns are recorded in a persistent validated-pattern registry that is structurally independent of the graph index and reapplied after index rebuilds. The registry acts as a partial graph coloring and active-learning oracle: future discovery operates on …

Context-Aware Multimodal Generative Copilot And Cross-Surface Discovery Engine For Automotive Passenger Displays, Richa Gupta

Defensive Publications Series

This disclosure describes an operating-system-level passenger copilot, also referred to as an in-car assistant, passenger companion, or media helper, for vehicles equipped with passenger displays, rear-seat entertainment screens, or secondary displays. The system coordinates video screen image capture (frame ingestion), voice isolation (seat-isolated routing), cross-device watch history syncing (watch graph synchronization), and on-screen landmark navigation (point of interest extraction) to enhance the in-vehicle entertainment experience without distracting the driver. When a user taps an on-screen icon or speaks into a dedicated microphone, the vehicle operating system captures a video frame, screenshot, or image from a streaming video application. A multimodal …

System For Providing Playback-Synchronized Contextual Content To A Secondary Device, Aritri Chakraborty, Himank Airon, Ayushi Goyal

Defensive Publications Series

Obtaining contextual information for content on a primary display can disrupt a viewing experience or involve fragmented manual searches on a separate device. Systems and methods are described that can address this by synchronizing a secondary computing device (e.g., a smartphone, tablet, or wearable device) with a primary display. The primary device may broadcast synchronization data, such as a content identifier and a playback timestamp, to a companion application on the secondary device. This application can then query a backend system to retrieve pre-processed, time-coded metadata corresponding to a specific moment in the media. This process can provide context-aware information …

Edge-Based Causal Analysis For Remediating Micro-Temporal Resource Congestion, Ajit Singh

Defensive Publications Series

Systems and methods are described for mitigating micro-temporal resource congestion in multi-tenant computing environments, where conventional schedulers may not effectively resolve sub-second interference. A decentralized control plane can operate at the node level, using local probabilistic profiling to generate compressed summaries of system behavior. A causal analysis engine can then calculate a correlation coefficient to attribute performance degradation in a affected workload to the resource consumption of a potential source workload. The system can handle analysis edge cases, such as resource saturation, and can employ a return-on-investment framework to select a remediation action, for example, throttling the source, boosting the …

Dynamic And Granular Source Attribution For Structured Content, Hugo Navarrete, David Fengyu Ke

Defensive Publications Series

Systems for presenting structured content, such as lists, can face challenges in providing clear source attribution. Placing a single citation at the end of a list may create a disconnect between a specific claim and its source, potentially making verification difficult for a user. To address this, techniques are described for a system that can dynamically place attribution markers within the content. This system can analyze properties, such as list length, nesting depth, and source mapping, to apply a rules-based strategy, for example, inserting citations on a per-item or sectional basis. The system can then modify the content to insert …

Mandate Lifecycle Extensions For Agentic Payment Credentials, Matthew T. Kirby

Defensive Publications Series

Autonomous AI agents, including large language model (LLM) agents, increasingly originate payment authorization requests under stored, cryptographically signed mandates derived from natural-language instructions. Existing frameworks verify machine-enforceable constraints — amount, payee, merchant — at transaction time; existing art separately teaches similarity-based transaction screening, single-use transaction-linked authorization credentials, decoupled out-of-band authentication, versioned credential supersession with freshness proofs, and attested display of transaction details. No reference teaches the lifecycle coupling specified here: (1) suspending a payment authorization request when a similarity score between a salted, committed embedding of the natural-language instruction — bound into the signed mandate with a pinned scoring stack …