Digital Commons Network^™

The Shorthorn: October 3, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 27, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 26, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 19, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 14, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 18, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 13, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

The Shorthorn: September 12, 1984

The Shorthorn Newspaper Collection: 1980s

No abstract provided.

Expanding The Cognitive Attentional Standards Platform Through Artificial Influence Assessment (Aia): Rationale, Development, And Measurement Design, Delante Clark

Graduate Scholarship and Creative Works

Artificial intelligence is increasingly shaping how individuals access information, make decisions, and interact with digital environments. The Cognitive Attentional Standards Platform (C.A.S.) was developed to assess attention related harms, cognitive safety, digital autonomy, and platform influence across digital systems (Clark, 2026). However, the growth of generative AI, conversational agents, and algorithmic decision support technologies has introduced new forms of influence that may not be fully captured by existing assessment domains. This paper proposes the Artificial Influence Assessment (AIA) as an expansion of the C.A.S. framework designed to measure AI mediated influence on cognition, behavior, autonomy, and information processing. Drawing on …

Governing Algorithmic Attention: Attention Safeguard Models And The Cognitive Attentional Standard As System Level Interventions In Human Computer Interaction, Behavioral Economics, And Artificial Intelligence, Delante Clark

Graduate Scholarship and Creative Works

Algorithmic recommendation systems and interface designs shape attention by combining visually salient cues with uncertain reward timing and low friction interaction. These conditions can sustain anticipatory checking, extend time on task, and reduce natural disengagement points through patterns such as infinite scrolling and autoplay. This paper synthesizes research across neuroscience, human computer interaction, behavioral economics, and artificial intelligence to argue that attention capture is a predictable outcome of incentive driven design rather than an individual failure of self regulation. It advances the Attention Safeguard Models and the Cognitive Attentional Standard as system level interventions that regulate exposure conditions, pacing, and …

Multi-Modal Cross-Platform Recommendation System With Aggregated Social Context Signals, Anonymous

Defensive Publications Series

Systems and methods are described for cross-platform, social-context-aware product recommendation. Interaction signals associated with a user are aggregated across multiple applications and normalized into features used to populate an inspiration graph representing entities and relationships reflecting user interests and context. A conversational shopping mode receives multi-turn requests and constraints and may accept multi-modal inputs such as room, wardrobe, or invitation images. Candidate products are retrieved from one or more catalogs and ranked using features derived from the inspiration graph and, when provided, the multi-modal inputs. In some embodiments, a trend momentum score is computed from velocity and recency of style …

Dynamic Image Conversion, Anonymous

Defensive Publications Series

Systems and methods are described for converting still images into short video clips at scale. A computing system receives a still image, determines an image pattern using extracted features, and selects one or more motion context files that map the pattern to standardized minimal-motion templates. The system generates a plurality of frames by applying the selected template(s) and encodes a short video clip that begins and/or ends with a frame identical to the original still image. In some implementations, a purpose-built image-to-video conversion model generates or refines frames, optionally conditioned on motion context files and template outputs that may also …

Recoverable Multimedia Export With Pre-Export Validation And Element-Level Automated Remediation, Anonymous

Defensive Publications Series

Techniques are disclosed for recoverable multimedia export using pre-export validation and element-level automated remediation. A validation engine traverses a composition graph before an export pipeline begins and checks referenced elements such as media assets, audio tracks, fonts, effects, filters, LUTs, and external resources for existence, decodability or integrity, permissions, compatibility, dependencies, and license validity. A structured validation report identifies each problematic element with a failure type and severity and provides remediation options. A user interface presents the report prior to export, including per-issue detail and a fix-all control, and accepts user overrides. A remediation engine applies selected actions such as …

Ensemble Model Divergence Analysis For Adversarial Prompt Detection In Generative Ai Systems, Anonymous

Defensive Publications Series

Techniques are disclosed for detecting adversarial, obfuscated, or harmful prompts in generative AI platforms by using model disagreement as a risk signal. A user prompt is routed to an ensemble of language models selected for diversity in architecture, size, generation, and safety tuning, optionally including smaller canary models. Each model generates a response, and the responses are embedded into a shared semantic vector space. Pairwise divergence values, such as cosine distances between response embeddings, are computed and aggregated into a divergence score for the prompt, with optional per-model divergence diagnostics. The divergence score is compared to a calibrated threshold to …

Active-Feedback User Simulation Agent For Bidirectional Content Retrieval In Recommendation Systems, Anonymous

Defensive Publications Series

Techniques are described for bidirectional candidate generation in a recommendation pipeline using an active-feedback user simulation agent. An initial candidate set is retrieved using one or more retrieval paths. A user digital twin consumes a live session state, including an emotional-state embedding, and evaluates the candidates by predicting a session trajectory. When the predicted trajectory indicates low engagement, disengagement risk, or a coverage gap between predicted preference and available candidates, the agent generates a structured, machine-readable retrieval query (e.g., topic, content-type, social, negative, emotional, or mixing requests). A query handler executes the query to obtain additional candidates, forming an expanded …

Multimodal Session Simulation With Sequential User State Evolution For Content Ranking, Anonymous

Defensive Publications Series

Techniques are described for multimodal simulation of a user browsing session through an ordered content feed. A feed is rendered into a visual representation, and recent engagement events are encoded into a live session state vector that includes an emotional state embedding inferred from behavior. A multimodal autoregressive model consumes the rendered feed and the session state to predict a trajectory across feed positions, including predicted interactions and predicted emotional-state shifts conditioned on prior positions. A planner and/or safety checker uses the predicted trajectory to select among candidate orderings or to block a slate and serve a fallback ordering when …

Language Model System For Account Compromise Detection Via Multi-Signal Business Graph Reasoning, Anonymous

Defensive Publications Series

Systems and methods are described for pre-monetization detection of business account compromise using large language model reasoning over business-graph evidence. A pipeline selects candidate accounts based on novel behavior such as advertising on previously unseen pages or domains. For each candidate, signals are aggregated across categories including account structural metadata, creator indicators, candidate ad content attributes, historical baseline ad attributes, administrative access modification records, and business activity events. Heterogeneous signals are transformed into a structured natural-language representation organized by category and combined with embedded domain heuristics specifying compromise indicators, non-compromise indicators, and exclusion criteria. A large language model processes the …

Split-Trust Key Derivation For Passkey-Authenticated Encrypted Data Backup And Recovery, Anonymous

Defensive Publications Series

Techniques are described for passkey-authenticated encrypted backup and recovery using split-trust key derivation. A client device performs passkey authentication via WebAuthn/FIDO2 and invokes a PRF extension to obtain a high-entropy pseudorandom output. The client derives a client-side key component (e.g., a BackupRootKey via HKDF) from the PRF output and obtains a server-side secret from a backup service only after successful passkey authentication. The client combines the client-side key component and the server-side secret using a key derivation function to produce a backup encryption key used to encrypt backup data for cloud storage and to decrypt the backup during restore. Passkey …

Adaptive Real-Time Video Communication With Latency-Aware Codec Selection And Asymmetric Codec Design, Anonymous

Defensive Publications Series

Techniques for adaptive real-time video communication are described. A device capability classifier, optionally based on a machine-learning model, determines codec eligibility beyond static device attributes. During a session, an endpoint measures encoding latency to adjust encoder complexity presets and to switch from a higher-complexity codec to a lower-complexity codec when real-time criteria are not satisfied. A receiving endpoint measures decoding latency and can signal the sender to change codec or configuration responsive to receiver-side performance. The techniques also support asymmetric operation in which an endpoint transmits using a first codec while receiving using a second codec. Additionally, temporal layering is …

Aggregate Cpu Core Frequency Scoring For Instant Mobile Device Performance Classification, Anonymous

Defensive Publications Series

Techniques are described for instant performance classification of a computing device using an aggregate CPU frequency score. A client device obtains, for each CPU core, a maximum clock frequency value from an operating system-exposed hardware descriptor and computes a continuous score by aggregating the per-core maximum frequencies, such as by summation. The score can be computed with low overhead and reported in telemetry to a backend service that builds a device capabilities table keyed by device model identifier and serves scores via a cache. Feature gates use threshold comparisons against the continuous score to enable, disable, or adapt compute-intensive features. …

Stochastic Codebook Nearest-Neighbor Decoding For Robust Digital Watermark Recovery, Anonymous

Defensive Publications Series

Systems and methods are disclosed for recovering invisible digital watermark messages from modified media using database-backed nearest-neighbor decoding. An embedding subsystem generates an n-bit binary message sampled uniformly at random, embeds the message into a media item using a watermark encoder, and stores an association between the message and a content identifier in a message database. A decoding subsystem extracts a noisy n-bit message from a candidate media item, performs a Hamming-distance nearest-neighbor search over stored messages to obtain a closest stored message and distance, and applies threshold-based decision logic to determine a match. A two-threshold policy may trigger optional …

Unified Multi-Channel Messaging History, Gustavo Matthew Assuncao

Defensive Publications Series

An AI agent that converses with the same person across several messaging providers — WhatsApp, Telegram, Signal, Discord — conventionally keeps one message history per provider. When a contact moves between channels the agent loses continuity: the earlier exchange is in another store, behind another code path, keyed by another identity. The two common remedies both fail: a table-per-provider design forces a schema migration every time a new channel is onboarded, and a lowest-common-denominator schema discards the provider-specific fields (Discord guild id, WhatsApp template id, Telegram thread id) that the agent later needs.

This publication discloses a design that resolves …

Interview With Orca Award Winner Ross Thompson, Unl Psychology; Childhood Emotional Development, Mark Griep, Ross Thompson

UNL ORCA Interview Series

Ross Thompson was awarded the ORCA in 2000. He was born in 1954 in Madison, Wisconsin. He traveled nearly 2000 miles west to earn a bachelor’s in psychology magna cum laude from Occidental College in Los Angeles. Then, he traveled east over 2200 miles to earn a master’s and doctorate in psychology at the University of Michigan in Ann Arbor. In 1981, he joined the University of Nebraska-Lincoln as an assistant professor of psychology and rose quickly through the ranks while studying childhood emotional development. In 2003, three years after earning the ORCA, Ross left UNL to join the psychology …

Effective Strategies For Improving Communication In Organizations That Hr Leaders Use To Increase Employee Productivity, Susan Dean

Walden Dissertations and Doctoral Studies

No abstract provided.

Customer Engagement Strategies Among U.S. Food Service Leaders In The Postpandemic Digital Era, E'Yanna Yvette Davis

Walden Dissertations and Doctoral Studies

No abstract provided.

Trump Approval Continues To Erode In New Hampshire; Most Believe Iran War Was Wrong Decision 6/29/2026, Unh Survey Center

All UNH Survey Center Polls

Nearly two-thirds of Granite Staters say the decision to go to war with Iran was wrong, few expect a full agreement to materialize during the 60-day negotiating window, and most oppose restarting military operations against Iran if no deal is reached on Iran's nuclear program. President Trump’s job approval rating continues to decline and approval of his handling of foreign policy is at its lowest in either of his terms. Only one-third believe the country is headed in the right direction.

Mathematical Modeling And Image Processing Algorithms In Artificial Intelligence-Based Technical Vision Systems, Erkin Uljaev, Ulmasjon Ulfat Ogli Abdixalilov

Chemical Technology, Control and Management

This paper presents a comprehensive study on the development of a mathematical model and image processing algorithms for artificial intelligence-based technical vision systems. The research focuses on analyzing the structural organization and functional components of the system, including image acquisition devices, illumination subsystems, and data processing modules that ensure stable and accurate operation. A systematic and integrated approach is applied to model the transformation of object parameters and to enhance the accuracy, robustness, and reliability of object detection processes. Particular attention is given to image preprocessing, segmentation techniques, and contour detection algorithms, as these stages play a crucial role in …

Investigating Burnout Among Hospital Social Workers: A Qualitative Exploration, Crystal Marie Herring

Walden Dissertations and Doctoral Studies

No abstract provided.

Intersecciones Hispánicas Número Completo 3

Intersecciones Hispánicas: Revista de Cultura, Literatura y Lingüística

No abstract provided.

Siguiendo Los Pasos Del Teatro De Mario Vargas Llosa: Homenaje- Entrevista Completa, Mara L. García

Intersecciones Hispánicas: Revista de Cultura, Literatura y Lingüística

No abstract provided.