Digital Commons Network^™

A Process For The Preparation Of (S)-3-Amino-3-(4-Chlorophenyl)Propan-1-Ol, Msn Laboratories Private Limited, R&D Center, Hyderabad, India, Srinivasan Thirumalai Rajan, Srinivas Reddy Gade, Suresh Challa.

Defensive Publications Series

The present disclosure relates to a process for the preparation of (S)-3-amino-3-(4-chlorophenyl)propan-1-ol of formula-1, which is represented by the following structural formula.

Formula-1

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 …

The Fingers-Based Occlusion Effect Triggering Methodology That Will Be Utilized For Creating Visual Imagery And Visual Patterns Utilizing A Pen Tool Where The Pen Tool Can Be Utilized To Create Visual Imagery And Visual Patterns On Physical Surfaces And On 3-Dimensional Virtual Space Areas., Punarjeewa Abeysekera

Defensive Publications Series

This paper describes a fingers-based occlusion effect triggering methodology that will be utilized for creating visual imagery and visual patterns utilizing a pen tool where the pen tool can be utilized to create visual imagery and visual patterns on physical surfaces and on 3-dimensional virtual space areas. The fingers-based occlusion effect triggering methodology will incorporate a pen tool, a built-in display that produce illumination, tracking markers and built-in camera configuration. The methodology will be required to utilize a power source that will be required to power the pen tool and its entities. And the methodology will be required to utilize …

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 …

Primitive For Finding Actionable Information In Time Series Based On Motif Locations, Michael Yeh, Yan Zheng, Junpeng Wang

Defensive Publications Series

The present disclosure relates to a system and method for finding actionable information in time series based on motif locations. The method includes an analysis computer that obtains time series data. The analysis computer generates a plurality of motifs. For each motif of the plurality of motifs, the analysis computer determines identified locations in the time series data that match the motif and determines a plurality of motif type scores based on the identified locations of the motif. The analysis computer determines a selected motif of the plurality of motifs based on the plurality of motif type scores for each …

Method, System, And Computer Program Product For Online Account Recovery, Elisa Duarte

Defensive Publications Series

Methods, systems, and computer program products are provided for online account recovery. An example method includes: receiving an account recovery request associated with a user account a user is unable to access, the account recovery request including identity data and payment device data, the payment device data obtained via short range wireless communication in response to the user arranging the payment device relative to a computing device; in response to receiving the account recovery request, authenticating the chip based on a cryptogram; in response to authenticating the chip, inputting a payment device identifier and the identity data into a model …

Optimally Scaled Low-Rank Adaptation For Efficient High-Rank Fine-Tuning, Yilang Zhang, Xiaodong Yang, Yiwei Cai

Defensive Publications Series

A method can be performed during a round of iteration during a loss function optimization process. The method can include a computer obtaining a first matrix and a second matrix. The computer can determine a selected scaling process from a first scaling process and a second scaling process. The computer can modify the first matrix and the second matrix using the selected scaling process to obtain a first modified matrix and a second modified matrix. The computer can determine a first moment and a second moment based on the first modified matrix and the second modified matrix. The computer can …

Autonomous Mobile Robot For Transferring Planar Workpieces Between Processing Stations Using An Orientation-Holding Con­Veyor Stage And A Self-Locking Kinematic Dock, Alexander Willer

Defensive Publications Series

An autonomous mobile robot (AGV / AMR) transfers a planar workpiece — for example a printed circuit board — between processing stations by carrying a transfer-conveyor segment on a powered stage that holds the segment’s orientation independently of the robot’s heading. This lets a minimal-footprint, non-holonomic robot present the conveyor to a station port facing any direction, in confined space, without sweeping the segment through its diagonal. At each station a docking interface is provided that separates location from clamping: passive kinematic features (a fully-locating feature plus a relieved one, optionally tapered) locate the segment, while one or more self- …

Predictive Doppler Frequency Pre-Compensation For Non-Terrestrial Network Handovers, Edison Chen, Xuqiang Zhang

Defensive Publications Series

In non-terrestrial networks, for example, networks that use low-earth-orbit satellites, handovers between satellites may be subject to latency due to significant Doppler frequency shifts for the target satellite. This disclosure describes a predictive method for Doppler pre-compensation that may be centered at a user equipment (UE) (e.g., a smartphone, tablet, or vehicle-mounted terminal). The technique may involve the UE recording the magnitude of a frequency compensation value from its connection with a source satellite. For an initial uplink transmission to a target satellite, the UE may then apply a predictive pre-compensation value, which could be derived by inverting the polarity …

In-Band Threat Context Propagation For Distributed Policy Enforcement, Niranjan M M

Defensive Publications Series

The proposal introduces a data-plane aligned mechanism for propagating compact, actionable threat context in-band with live traffic to enable immediate and coordinated security enforcement across distributed environments. Instead of relying on centralized control-plane signaling or out-of-band policy distribution, the approach encodes deterministic enforcement intent such as action, severity, scope, and validity into bounded in-band metadata that travels along the same forwarding path as the affected traffic.

Enforcement points decode and validate this metadata in the fast path and apply policy actions at data-plane speed without requiring context lookups or external coordination. Rich threat details remain out-of-band and are optionally resolved …

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 …

Learned Encoder Selection Via Column Statistics Feature Extraction For Adaptive Columnar Data Encoding, Anonymous

Defensive Publications Series

Techniques are disclosed for learned selection of a column encoder using column statistics. A feature vector is computed in a single pass over a column and includes base statistics (e.g., sparsity, cardinality, dominant frequency, bit-width percentiles, run-length and delta statistics, entropy, sortedness, and data type) and interaction features (e.g., sparsity clusteredness, bit-width gap, delta-entropy ratio, dominant runlength, outlier fraction, and delta uniformity). A benchmark harness evaluates candidate encoders on column samples and labels each sample with an encoder selected by a composite score combining decode performance, compression performance, and encode performance using configurable weights. A compact neural network maps the …

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 …

Confidence-Gated Hybrid Diagnosis System With Cross-System Signal Correlation For Infrastructure Failure Management, Anonymous

Defensive Publications Series

A confidence-gated hybrid diagnosis approach is disclosed for multi-system infrastructure operations. Typed signals are collected from multiple independent monitoring systems and temporally aligned within a configurable window. The aligned observations are compared to structured historical failure patterns stored in a knowledge base, where each pattern includes cross-system signal signatures and operational metadata such as recommended actions and oncall routing. A pattern match confidence is computed based on a proportion of signatures satisfied. A triage report is generated with diagnosis, confidence, affected systems, and routing. A large language model (LLM) copilot is invoked only when confidence falls below a threshold or …

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 …

Hierarchical Alignment Bit Provisioning In Tensor Processing Units For Block Floating-Point Data Formats, Anonymous

Defensive Publications Series

Hierarchical provisioning of alignment bits is described for tensor cores operating on block floating-point or microscaling (MX) data types. A tensor core multiplies element pairs to form products, aligns products within each block using an intra-block alignment bit setting, and reduces aligned products with an intra-block adder tree to form per-block partial sums. The per-block partial sums are then aligned across blocks using an inter-block alignment bit setting and reduced using an inter-block adder tree to produce an accumulated result that may be converted to FP32. The intra-block alignment bit setting is provisioned independently from the inter-block alignment bit setting …

Offline Short-Form Video Content Pre-Download With Integrated Parental Controls And Advertisement Management, Anonymous

Defensive Publications Series

Systems and methods are described for pre-downloading recommendation-based short-form video content for offline viewing. A client application selects a batch of videos from a personalized feed based on a user-selected viewing duration and downloads the batch to local storage using adaptive quality levels and storage-aware size estimation. Advertisements are bundled with the offline package and enforced as non-skippable during offline playback. Parental controls are integrated by applying age-appropriateness filtering before download and enforcing a daily offline viewing time limit that ends or blocks playback when reached. The system may automatically schedule pre-downloads when connected to Wi-Fi based on predicted offline …

Regional Shrink Testing For Empirical Capacity Validation In Distributed Computing Infrastructure, Anonymous

Defensive Publications Series

Regional Shrink Testing is disclosed for empirical capacity validation in distributed computing infrastructure. A controller configures a production region by applying safeguards such as disabling autoscaling and isolating load balancing behavior, captures baseline metrics, and iteratively reduces active service instances while maintaining substantially constant production traffic. Shrink targets may be computed proportionally per hardware type class (LSST) using resource weights, with instance selection based on priority and/or random sampling. A monitoring layer evaluates stopper metrics at a percentile across active hosts and classifies health into multiple levels to control shrinking, backoff, and peak detection based on sustained threshold durations. The …

Sram-Based Deficit Weighted Round-Robin Eligibility Maintainer With Pipelined Read-Modify-Write Forwarding, Safe Reload, And Deterministic Initialization, Anonymous

Defensive Publications Series

An SRAM-based eligibility maintainer for deficit weighted round-robin scheduling stores per-queue quantum and credit in packed SRAM entries. A fixed-latency pipeline accepts multiple opcodes including CSR read, CSR write, credit decrement, and credit increment, aligned to SRAM read latency. Read-after-write correctness is provided using address-collision forwarding of in-flight write data. Per-queue eligibility is tracked in a first register vector and reload selection is tracked in a second vector indicating whether a next credit operation should reload relative to quantum. Credit updates use saturating arithmetic and threshold-aware eligibility comparisons with selectable semantics. Deterministic initialization paints SRAM with known data while defining …