Digital Commons Network^™

Elastomeric Cowling For Pcb Connectors, Robert Hrabchak, Alberto Cavallaro, Ethan Hoying

Defensive Publications Series

Traditional metal cowlings for board‑to‑board connectors in electronic devices may add mass and occupy internal volume. These assemblies often rely on foam compression and multiple screws, which may lead to unpredictable retention forces and increased assembly complexity. Elastomeric retention assembly hardware is disclosed to secure connectors between a flexible circuit and a printed circuit board. The assembly includes an elastomeric band anchored by rigid bars to retention brackets on the circuit board. A stiffener with a convex, parabolic profile is positioned between the elastomer and the connector. This curved geometry facilitates a uniform distribution of downward force across the connector …

System And Method For Multi-Parcel Hoa Covenant Violation Detection From Spherical Imagery, Brice Fenger

Defensive Publications Series

Disclosed is a system and method for automated detection of homeowner-association (HOA) covenant violations from spherical (360°) imagery captured during a single drivethrough of a planned community. The novel aspects of the disclosure are: (1) the treatment of a single spherical image as a multi-parcel artifact, with violations attributed across all parcels whose geocoded locations fall within a radius of the image’s capture coordinates; (2) the per-parcel retrieval and merging of covenant rule sets - keyed by the specific parcel and, where applicable, by development phase - into a single multimodal large language model (LLM) prompt that performs both spatial …

System And Method For End-To-End Agentic Log Analysis, Verification, And Automated Remediation In Content Serving, Indu Ramamurthi, Raghav Lagisetty, Ajay Joshi, Srinath Narayanan, Sarvjeet Singh, Pradyumna Narayana

Defensive Publications Series

The present disclosure relates to an end-to-end agentic artificial intelligence system capable of autonomously ingesting live serving logs, isolating performance issues, mathematically verifying hypotheses using deterministic tool-calls, and deploying safe, low-latency fixes to a serving stack. The system chunks data into semantic problem slices and generates natural-language hypotheses. To prevent hallucination, the system executes deterministic queries against live data to verify its own hypotheses. Verified insights are translated into simple, non-machine-learning programmable rules that execute rapidly in production. These rules are pushed to a limited fraction of live traffic, where a real-time monitor compares performance against a baseline, automatically shutting …

Brand-Specific Conversational Agent With Lead Qualification, Balaji Pattabhiraman, Vijay Garg, Derrick Isoka, Deepak Yadav, Paneendra Ba, Teresa Batten, Teresa Chen, Lohitaksh Trehan, Shen Huang, Shruti Bhutada, Rina Jensen, Sudheer Sahu, John Amir-Abbassi, Ujjwal Gupta, Maneesha Nanda, Swati Mohanty

Defensive Publications Series

Keywords: conversational agent, brand-specific agent, lead qualification, search results integration, user intent, advertiser data aggregation, personalized user experience, dynamic call to action, AI agent training, lead prioritization

Abstract

Generating qualified sales leads for complex user journeys can be inefficient, often resulting in user drop-off and providing advertisers with little insight into user intent. This technique addresses these issues by integrating a brand-specific conversational agent directly into a content provider’s owned and operated surfaces, starting with the search results page. Trained on comprehensive advertiser data such as websites, business profiles, and user reviews, the agent provides detailed, real-time information, allowing users …

Dynamic Context-Aware And Personalized Insertion Of Sponsored Elements Into Llm-Generated Lists, Tim Whalin, Gagan Goel, Chris Monkman, Shrey Gupta, Hanny Kamal, Jason Galep, Shreya Kothaneth

Defensive Publications Series

Generative artificial intelligence (AI) systems frequently produce structured lists by synthesizing web data. Inserting ads into such lists can lead to jarring disruptions or redundant entries when integrated into these dynamic outputs. This creates a challenge in incorporating sponsored content without compromising user experience or trust, particularly when a relevant advertisement duplicates an organically generated item. The technology introduces a system that dynamically integrates sponsored elements into AI-generated lists by first employing a large language model to reverse-engineer the list’s context and derive one or more granular synthetic queries. This allows for the selection of sponsored candidates based on an …

Real-Time Context Engine For Dynamic Content Generation And Interface Adaptation, Tim Whalin, Otty Soemitro

Defensive Publications Series

A Real-Time Context Engine (RTCE) dynamically generates and adapts conversational content based on a user’s interactions with a webpage. The RTCE monitors client-side telemetry, such as scroll velocity and cursor position, and feeds these behavioral signals into a large language model (LLM) that functions as a real-time semantic orchestrator. For sponsored items, the system generates both an impartial “Objective Explainer” and a distinct “Advertiser Voice” through dual-voice orchestration, synchronizing them with the user’s expectations to maintain transparency. The technology also performs predictive mode-shifting by analyzing micro-interactions to infer shifts in user intent, automatically altering the user interface from one modality …

Objective Evaluation Synthesis For Personalized Sponsored Content In Generative Search, Tim Whalin, Grant Noskey, Gagan Goel, Omkar Muralidharan, Shrey Gupta, Grace Oh, Chris Monkman, Noor Rostoum, Hanny Kamal, Chen Liu

Defensive Publications Series

A system and method for synthesizing objective evaluations for personalized sponsored content in generative search environments is described. The technology utilizes a multi-voice generation pipeline to mediate between structured advertiser payloads and dynamic organic responses. An explainer model dynamically generates a neutral, objective summary of an advertisement that matches the style of an organic conversational flow. The system may classify advertiser data into factual, descriptive, and subjective claims, applying different grounding and attribution techniques to each category. Furthermore, a post-auction quality gate may dynamically suppress advertisements if the generated objective explanation falls below a helpfulness threshold. Keywords: generative artificial intelligence, …

Agent-Orchestrated Apparel Curation With Generative Ai-Based Visual Assessment, Sneha Kudli, Lakshmi Kumar Dabbiru

Defensive Publications Series

Some online fashion commerce experiences can be fragmented and labor-intensive, while certain human-led stylist services may lack scalability and real-time adaptability. A system and method are described for a personal shopper agent that uses artificial intelligence (AI) to automate apparel curation. The agent can synthesize a user's explicit preferences and implicit behavioral data to create a style blueprint. It may then query one or more product inventories for candidate items and use generative AI to produce virtual try-on images of these items on a user's three-dimensional body model. The agent can programmatically assess these images for fit and style to …

Addressable User Interface Via Natural Language Mapping Of Graphical Elements, N/A, N/A

Defensive Publications Series

Traditional graphical user interfaces are characterized by complex navigation paths that require users to traverse multiple menus and elements to complete tasks. The implementation of natural language control for such interfaces typically requires the development of dedicated application programming interface (API) layers for every supported function. These layers are resource-intensive to build and maintain. This disclosure describes a method for enabling natural language control of existing web-based interfaces without new API development. A mapping of user interface journeys is first generated in a codified language that describes specific document object model (DOM) interactions. This mapping is provided to a large …

Explainable Tree-Based Ensemble Models For Diabetes Prediction Using Shap, Maan Y Anad Alsaleem, Omar Shakir Hasan, Yahya Albugg

AUIQ Technical Engineering Science

Due to the generally unqualified nature of prediction data and the difficulty of interpreting predictions, predicting diabetes remains a significant hurdle in the adoption of machine learning within the medical domain. In this study, several tree-based machine learning techniques (LightGBM, XGBoost, CatBoost, and Gradient Boosting) were applied to predict diabetes using the 2015 BRFSS dataset, while two ensemble methods (soft voting and stacking) were employed to improve predictive accuracy. The performance analysis of the individual models and ensemble approaches indicates that CatBoost achieved the highest accuracy among the single classifiers (0.871), with an F1-score of 0.871 and a ROC–AUC of …

Chronotropic Response To Intratracheal Versus Intravenous Atropine In Anesthetized Adult Patients: A Randomized Controlled Trial, Ammar H. Mahdi, Majid Alhamaidah, Myasar J. Mohammed, Hussein Ali Hussein, Hussein Alkhfaji

AUIQ Complementary Biological System

Atropine is a commonly used anticholinergic agent in anesthetic practice, administered primarily to counteract bradycardia. Rapid treatment of intraoperative bradycardia is clinically critical, as delays may lead to hemodynamic compromise. This study aimed to compare the onset, magnitude, and duration of the chronotropic response to atropine administered via the intravenous (IV) versus intratracheal (IT) route in anesthetized adult patients. A prospective, single-blind, randomized controlled study was conducted on 60 adult patients classified as American Society of Anesthesiologists (ASA) physical status I-II, scheduled for elective peripheral surgery under general anesthesia. Patients were randomly allocated into three equal groups (n = 20 …

Assessing Media Literacy Competence In Secondary Education: Towards A Rubric Based On A Systematic Review, Steijn Jan Van Der Craats, Jason Simon, Romy Andrieu, Bo Sichterman, Stan Van Ginkel

Journal of Media Literacy Education Pre-Prints

Developing media literacy competence is an essential objective in secondary education. However, a validated instrument aimed to encourage the development of media literacy amongst students formatively is lacking hitherto. This review aims to identify relevant studies on media literacy competence or components thereof and their assessment strategies. Further, this study synthesizes these findings into a set of principles for constructing a formative assessment instrument fostering media literacy competence. Seventeen publications from the last 15 years were selected through a systematic search in scientific databases. All studies were categorized concerning crucial characteristics of assessment instruments. Furthermore, the synthesis of this study …

Self-Verifying Single-File Cryptographic Documents With Dual-Passphrase Architecture For Offline Recipient-Mediated Access Control, Michael Benaudis

Defensive Publications Series

This disclosure describes two cryptographic constructions complementary to the architecture previously published by the present inventor on Technical Disclosure Commons (TDCommons publication 10079, 12 May 2026). The first construction is a self-verifying single-file document scheme, where a document embeds the SHA-256 hash of its own canonicalized form within a reserved placeholder zone, allowing the document to verify its own integrity at load time, in any standards-compliant browser, without any external trust anchor, certificate authority, server, or registry. The verification fails closed: on mismatch, the document irreversibly disables its decryption controls and exposes a tamper warning to the recipient. The second …

Intent Gravity Engines, Johny Manuel-Devadoss, Joanna Johnson, Jayden Jack Johnson

Defensive Publications Series

Contemporary recommendation architectures optimize short-horizon behavioral objectives such as click-through rate, retention, conversion probability, watch-time maximization, and engagement persistence. While these systems achieve high efficiency in immediate interaction optimization, they systematically fail to model longitudinal human development, identity continuity, aspiration stabilization, and temporally coherent cognitive evolution. Existing recommender systems operate under an implicit assumption that preferences are stationary or slowly drifting latent variables inferable from interaction sequences. This assumption becomes increasingly invalid in high-dimensional socio-cognitive environments where users are not static consumers but dynamically evolving agents whose identities emerge through recursive interactions between cognition, social exposure, emotional state transitions, epistemic …

Statistical Assessment Of Groundwater Quality In Selected Areas Of Samarra District: Effects Of Land Use And Geological Setting, Ahmed K. Ibrahim

Engineering and Technology Journal

In this study, 25 newly drilled wells were selected in the Samarra district, which has an estimated area of about 350 km², and included rural and urban areas with various agricultural, industrial, and residential activities. Water samples were taken from the wells every two months starting in November 2023 and continuing until September 2024. Physical tests were conducted, including total dissolved solids and electrical conductivity, as well as chemical tests that included pH, total hardness (TH), calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), sulfates (SO₄^–2), nitrates (NO₃^–), and chlorides (Cl). Concentrations …

Experimental And Numerical Analysis Of Mechanical Properties Of Uhmwpe Nanocomposite Reinforced With Nano-Hydroxyapatite, Heshw A. Hassan, Diyar O. Kaka

Engineering and Technology Journal

Recently the polymer nanocomposites have shown significant development, enabling substantial improvements in the performance of conventional polymers that reflect large influences on the products and industry. Ultra-high molecular weight polyethylene (UHMWPE) is widely employed in biomedical and structural applications, their mechanical properties can be tailored through the incorporation of nanoscale fillers. In this study, nano-hydroxyapatite (nHA) particles were incorporated into UHMWPE at reinforcement loadings of 0.5, 1.0, 3.0, and 5.0% content experimentally, and different volume fraction numerically to evaluate their effect on the material's mechanical behavior. A Representative Volume Element (RVE) based on finite element analysis (FEA) was developed to …

Enhanced No₂ Gas Sensing Using Silver-Doped Cadmium Telluride Nanocrystalline Thin Films, Tunis Balasim Hassan

Karbala International Journal of Modern Science

Nitrogen dioxide (NO₂) is a toxic pollutant that necessitates sensitive and reliable monitoring systems. Conventional gas sensors often lack adequate responsiveness and fast recovery under changing conditions and therefore create a need for semiconductors with enhanced performance, especially at high industrial temperatures (around 250 °C). The study therefore aims to synthesis and evaluate silver-doped cadmium telluride (Ag:CdTe) thin films as NO₂ gas sensors. Pure CdTe and Ag:CdTe with silver concentrations of 5, 10, and 15 wt% were prepared by a co-precipitation process. XRD verified cubic symmetry with a progressive fall in crystallite size (6.67 nm to 5.46 nm at 15 …

Exploring Resource-Efficient Deep Learning For Medical Image Segmentation, Pallabi Dutta

Doctoral Theses

Automated medical image segmentation improves diagnostic accuracy by au tomating the precise delineation of target anatomical structures in the input images. Artificial Intelligence (AI), and specifically, Deep Learning (DL), has emerged as a state-of-the-art approach for this task. However, the significant computational demands of DL approaches often hinders their deployment. Ad vanced models, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), require substantial processing power and a large memory footprint, limiting their use in resource-constrained settings. This thesis aims to address this challenge by developing a series of novel, resource-efficient DL models that achieve high segmentation accuracy with reduced …

May 2026 President's Corner, Jacqueline Brellenthin

NASIG Newsletter

No abstract provided.

Member Spotlight: Rebecca Bealer, Willa Liburd

NASIG Newsletter

In this member spotlight, Rebecca Bealer, Head of Serials and Systems Librarian at Louisiana State University Health Sciences Library, reflects on her experience as NASIG's representative to IFLA's Serials and Continuing Resources (SCORE) section. She shares the professional and personal rewards of engaging with library colleagues internationally, the challenges of an increasingly consolidated workload in technical services, and her advice on essential skills for middle managers. Rebecca encourages NASIG members to consider volunteering as IFLA SCORE representative when the next call goes out in mid-2027.

Awards And Recognition Mid-Year Report 2025-26, Jessie London

NASIG Newsletter

No abstract provided.

Awards And Recognition Annual Report 2025-26, Jessie London

NASIG Newsletter

No abstract provided.

Bylaws Committee Mid-Year Report 2025-26, Cecilia Genereux

NASIG Newsletter

No abstract provided.

Bylaws Committee Annual Report 2025-26, Cecilia Genereux

NASIG Newsletter

No abstract provided.

Communications Committee Midyear Report 2025-26, Betsey Appleton

NASIG Newsletter

No abstract provided.

Communications Committee Annual Report 2025-26, Betsey Appleton

NASIG Newsletter

No abstract provided.

Conference Planning Committee Mid-Year Report 2025-26, Amy Carlson

NASIG Newsletter

No abstract provided.

Conference Planning Committee Annual Report 2025-26, Amy Carlson

NASIG Newsletter

No abstract provided.

Conference Proceedings Mid-Year Report 2025-26, Marie Peeples

NASIG Newsletter

No abstract provided.

Conference Proceedings Mid-Year Report 2025-26, Marie Peeples

NASIG Newsletter

No abstract provided.