On-Chip Thermal Monitoring and Mitigation for Semiconductor Design-for-Test

During semiconductor design-for-test operations, the application of high-activity test patterns can generate localized heat as functional-mode thermal management systems may be inactive. A hardware-based architecture can integrate localized monitoring modules near potential thermal hotspots. A module can operate synchronously with test patterns to capture peak temperature values and their corresponding test pattern counts. The system may also include a mitigation circuit that compares real-time temperature against a configurable threshold and can throttle system clocks if the threshold is exceeded to reduce heat generation. This approach can provide thermal observability and control in a test environment, enabling the creation of thermal profiles for test program optimization and providing a mechanism to mitigate thermal runaway

System and Method for Autonomous Cross-Domain Collaborative Artificial Intelligence–Driven Discovery and Innovation

The presented proposal discloses a system and method for autonomous, collaborative artificial intelligence–driven discovery and innovation. The techniques presented herein enables structured interaction among multiple specialized AI software agents, each possessing domain-specific expertise, to perform real-time cross-domain reasoning without continuous human intervention. An interaction controller governs communication, reasoning exchange, and collaboration rules among the agents, while an evaluation module assesses novelty, feasibility, and domain validity of generated outputs. Through iterative feedback and refinement, the proposed system synthesizes knowledge across disciplines to generate robust, non-obvious solutions and inventive outcomes. The proposed architecture overcomes limitations of conventional single-domain and task-parallel AI systems by enabling genuine intellectual collaboration, scalable integration of new domains, and autonomous discovery applicable to scientific research, engineering, healthcare, and other high-complexity use cases

Dynamic AI Agent Orchestration for NL-to-SQL Query Generation

Reliably generating accurate structured query language (SQL) queries from natural language (NL) inputs is a difficult task due to challenges such as schema ambiguity, uncertainty regarding table relationships, complex business logic makes, etc. LLM-based solutions are often unable to operate reliably within complex, real-world enterprise environments with complex datasets. This disclosure describes the use of agentic artificial intelligence (AI) for NL-to-SQL query transformations. A semantic data layer leverages a three-tiered model - attributes, entities and cubes. Attributes define dimensions within a table, entities represent a logical view of data, and cubes act as business objects that abstract the complexity of identifying a source of truth and model domain-specific datasets. An agentic workflow with an orchestration agent and sub-agents dedicated to individual data cubes is used. A predefined cube configuration is passed to a large language model (LLM) to enable accurate identification of relevant data entities and consistent application of business logic. The namespace of the semantic model is extended to capture agentic guardrails with predefined metadata or prompts, and to control agent behavior and scope, providing context-sensitive information while actively preventing LLM hallucination

The PHYRFLY Opus: A Unified Standard for Hyperdimensional Time Vectors, Spectrally Isolated Coordination, Neural Hierarchies, and Distributed Proprioception

This monograph establishes 264 prior art claims for a decentralized, connectionless timing and positioning architecture comprising the UTLP, RFIP, and SMSP protocol triad. It formalizes the PHYRFLY nomenclature to distinguish low-level, hardware-scheduled Physical-Layer synchronization primitives from higher-level application orchestration. The core novelty centers on a Vector Time Representation, encoding temporal state as 8 phase values (ticks modulo coprime integers 211–251) transmitted in 8 bytes, then expanded locally into ~10,000-dimensional hyperdimensional chord vectors for similarity computation and drift estimation. This cyclic encoding enables automatic phase-lock convergence within 5–10 beacon exchanges regardless of initial offset, with the Chinese Remainder Theorem guaranteeing unique tick recovery across a 261,000-year horizon. A complementary Spectral Isolation Model maps transport-agnostic architecture to biological firefly wavelength differentiation, enabling swarm-level isolation through physics (e.g., 802.11 vs. 802.15.4) rather than protocol-layer logic—independent swarms occupying the same physical space remain blind to one another at the RF front-end. Key technical advancements established as prior art include: Hyperdimensional Phase Encoding: Basis vectors derived from prime-indexed dimensions enable cosine similarity metrics for graceful synchronization degradation, Kalman filtering for sub-tick drift estimation, and Byzantine fault detection through cross-phase consistency analysis. An optional fine-resolution segment concatenates 4 smaller primes (~4,000 additional dimensions) for nanosecond precision. Phase-Indexed Score Execution (SMSP): Coordinated actuation patterns compiled from human-readable timing specifications into phase-space representations; synchronized devices independently derive identical outputs by evaluating current phases against compiled scores—no start now signal or runtime coordination required. The Neural Hierarchy (Neuron → Ganglion → Plexus → Cortex): A hierarchical orchestration model that separates flat, peer-to-peer timing infrastructure from application-layer data aggregation and command distribution. Regional Stability Digests (Ganglion Privacy): A method for masking individual node technosignatures by aggregating raw vitals into anonymous regional summaries, providing physical-layer privacy while maintaining global sensor utility. Council of Oracles: A multi-oracle time consensus mechanism where nodes with external time sources (GPS/NTP) peer-review each other to identify and demote deviant God nodes. Dormancy Lifecycle with Phantom Arbor Defense: A protocol for secure swarm re-entry after sleep, utilizing N-beacon verification and temporary authority penalties to prevent synchronization hijacking. Metabolic Stealth: A defensive behavior for sparse clusters that automatically reduces broadcast frequency to minimize RF footprint when solitary. This document provides physics foundations, mathematical proofs of convergence properties, and reference implementations across heterogeneous silicon (ESP32-C6, MG24, nRF52840), establishing these methods as a Public Utility to preclude the patent enclosure of distributed beamforming, autonomous swarm coordination, bilateral therapeutic stimulation, emergency vehicle lighting synchronization, and continental-scale geophysical sensing

Agentic Framework Integrating RAG for Policy Queries and Autonomous Trend Analysis

Tools that just pull up whole, complicated company policy documents often don\u27t help people find the specific answers they need. This new technology is a system for understanding and analyzing policies that works in two ways. A Reactive Mode acts like a Q&A tool. It uses advanced technology (retrieval-augmented generation) to break down policies into small, searchable pieces. This allows the system to give direct answers with citations and even run simulations to show what happens in different situations based on the rules. A Proactive Mode is an automated agent that constantly checks support data to spot trends and see how quickly certain issues are growing. Based on what it finds, this agent can take action, such as pointing out missing information in the knowledge base or flagging ongoing, serious problems. Overall, this system provides personalized answers and helps the company improve its internal knowledge, which means employees won\u27t have to rely as much on human support teams

SELF-LEARNING, LLM-DRIVEN, EXPLAINABLE, PRIVACY-AWARE, LEARNING AGENT FOR INTELLIGENT MODEL RECOMMENDATIONS (SELF-LLM-XPLAINER)

The present disclosure relates to a system and method for model recommendation, more particularly, a self-learning, LLM-driven, explainable, privacy-aware, learning agent for intelligent model recommendations (SELF-LLM-XPLAINER). The present disclosure suggests ingesting a dataset provided by a user via an online interface. Thereafter, the present disclosure suggests profiling the ingested dataset to generate standardized metadata. Subsequently, assessing the standardized metadata and sampled data values to detect Personally Identifiable Information (PII) and to generate a privacy risk map. Upon generating the privacy risk map, the present disclosure suggests identifying a machine learning task corresponding to the dataset based on the standardized metadata and one or more sample values. Further, the present disclosure suggests analyzing the standardized metadata and identifying task metadata to generate a recommendation model. As a result, the present disclosure provides a self-learning, agentic system for intelligent recommendation of machine learning models and pipelines

SYSTEM FOR EPISTEMOLOGICALLY-INFORMED TEXT GENERATION WITH LANGUAGE MODELS

Proposed herein is a system that enables Large Language Models (LLMs) to automatically generate linguistically appropriate hedging language that accurately reflects the reliability of underlying information sources. By extracting multi-dimensional epistemological metadata (source authority, temporal relevance, evidential support) from knowledge base documents and integrating this metadata directly into LLM generation processes through augmented attention mechanisms, the system produces responses where confidence expressions match actual source reliability. The approach addresses the confidently incorrect problem in high-stakes applications (medical, legal, financial) by ensuring LLMs communicate uncertainty appropriately, using domain-specific hedging conventions and continuous feedback-driven refinement

A Method for Dynamic Web Image Modification via User-Specified Heuristics and Generative Models

Web content is often not tailored to individual user needs, such as accessibility requirements or content preferences. A method is disclosed for automatically modifying web images based on user-defined heuristics. Within a browser setting, a user can specify rules in natural language for how certain image content should be altered. When a web page is rendered, images are analyzed to determine if they match any user-specified rule. If a match is identified, a generative model is used to modify the image according to the corresponding rule. The modified image is then displayed in place of the original. This allows for a customized browsing experience, enabling automatic image adjustments for accessibility, content filtering, and localization

Method and System for Distributed Timekeeping and Synchronization Using Coprime Cyclic Hyperdimensional Vectors

Disclosed is a protocol and architecture for distributed timekeeping that replaces scalar binary counters (e.g., Unix timestamps) with Hyperdimensional (HD) State Vectors. The system, termed the Universal Time-Locked Protocol (UTLP) Vector Time, generates a global time state via the superposition of multiple coprime cyclic attractors (virtual oscillators), creating a high-dimensional temporal texture that evolves deterministically. Unlike scalar clocks which require absolute synchronization, this vector-based approach enables Fuzzy Synchronization, where distributed nodes correct drift via similarity-based gradient descent rather than hard resets. To accommodate low-bandwidth networks (e.g., BLE, 802.15.4), the system utilizes Generative Compression, transmitting only the phase indices (a Harmonic Chord of approx. 8-14 bytes) which allows receivers to regenerate the full 10,000+ bit hypervector locally. The disclosure includes a reference implementation for Elastic Coherency, a method for drift correction that averages vector states across a swarm, and a hardware architecture definition using parallel circular shift registers or compute-in-memory (CIM) arrays for micro-watt power operation. This technology is applicable to swarm robotics, neuromorphic computing, and haptic coordination where atomic-level coherency is required without a central master clock

Device for taking images of an aircraft engine

A device for taking images of an aircraft engine, comprising a. a frame (1), in particular a mobile frame (2); b. a rotatable beam (2), in particular rotatably mounted to the frame, comprising i. a plurality of attachment elements, each attachment element configured to allow for a camera module (3) to be releasably mounted thereto