Digital Commons Network^™

Adjusting Large Language Model Context Via User-Initiated Thread Renaming And Organization, Victor Carbune, Florian Hartmann

Defensive Publications Series

Large language model inference context often becomes inefficient or contains irrelevant information as conversational threads grow in length. This disclosure describes methods for adjusting inference context based on user-initiated organizational signals, such as renaming threads or grouping them into projects. When a thread is renamed, the conversation is segmented into topics and re-ranked to prune segments that do not align with the new title. Conversely, when threads are organized into a project or given similar names, relevant context from related threads is dynamically loaded to augment the current session. User feedback signals, such as manual ratings or interface interactions, are …

Eco Cell Ir Drop Signoff Using Machine Learning, Praphulla Pandey, Vaibhav Gupta

Defensive Publications Series

Traditional Engineering Change Order (ECO) cell verification may require a full‑chip Electro‑Migration and IR (EMIR) analysis to confirm that newly integrated cells do not induce excessive IR drop failures. For large‑scale integrated circuits, this comprehensive simulation creates significant bottlenecks due to high turnaround times and intensive storage requirements. A machine learning‑based methodology is disclosed to predict dynamic IR drop specifically for ECO instances. A partition‑specific model is trained using data from a preceding stable EMIR execution. Physical and electrical parameters, including resistance, slew, load, and peak current, are extracted for new ECO cells and processed by the trained model to …

On‑Chip Current Sensor For Resistance Calibration Of High‑Speed Input/Output Peripherals, Karthikeyan Subramanian, Kasi Chunduri

Defensive Publications Series

Resistance calibration in high‑speed input/output (HSIO) physical layers typically uses dedicated automatic test equipment (ATE) channels to force current and measure voltage at an external reference pin. This traditional approach increases testing overhead and limits the capacity for concurrent multi‑site device testing. This disclosure describes a method and system for performing resistance calibration using an on‑chip current sensor. The sensor’s differential voltage sensing pins are connected to the internal resistance network. A mixed‑signal transconductor converts the detected voltage drop into a current, which is then integrated, sampled, and digitized. Internal resistance is calculated from these measurements using Ohm’s Law, and …

Reducing Test Time Through Parallel Execution Of Analog And Digital Bist Sequences, Karthikeyan Subramanian, Kasi Chunduri, Achin Grover, Gurumoorthy, Suman Jayachandra

Defensive Publications Series

Traditional test methodologies for semiconductor devices typically execute Analog and Memory Built‑In Self‑Test (MBIST) sequences in a standalone, serial fashion. This sequential approach involves separate initialization and execution phases for each test block, which contributes to total tester time. Specifically, standalone sequences for components (e.g., Phase Locked Loops (PLL), Digital to Analog Converters (DAC), memory blocks) run independently through Joint Test Action Group (JTAG) or external interfaces. The disclosed method utilizes a concurrency algorithm based on the IEEE 1687 IJTAG standard and Procedural Description Language (PDL) to interleave these test sequences. Digital and analog initialization phases may be combined, followed …

Cost Analysis Formulation For Pv–Evcs–Dstatcom Integrated Distribution Systems Using Enhanced Hunter–Prey Optimization, Pappu Soundarya Lahari, Varaprasad Janamala

Mansoura Engineering Journal

With the rapid and significant growth of Electric Vehicles (EVs) and Distributed Generation (DGs), such as Photovoltaic (PV) deployment, in the distribution system, it is essential to address the challenges of rising power losses, voltage fluctuations, and reactive power imbalances. Optimal DSTATCOM placement in PV-EV integrated systems to mitigate power quality issues is an effective solution. It is thus necessary to evaluate the economic considerations of such heavily compensated networks. This study proposes Enhanced Hunter-Prey Optimization (EHPO) to assess the net savings of the PV-EVCS-DSTATCOM integrated IEEE-33,69, and 118 bus distribution networks in both single and multi-objective modes. The multi-objective …

Psilocybin And The Related Tryptamine, Norbaeocystin, Exert Acute Anxiogenic Effects That Depend On Sex, Marisa J. Savini, Kylie M. King, Noelle M. Molnar, Evelynn J. Schneider, Savannah E. Straub, Joe Parker, Lillianna P. Puppel, Aleece K. Al-Olimat, Allison M. Bach, Andrew Jones, Phillip R. Zoladz

ONU Student Research Colloquium

Single treatments with psychedelics have demonstrated rapid, long-lasting antidepressant effects. However, psychedelics often produce unfavorable psychoactive effects that could worsen existing psychological distress. Thus, we compared the effects of psilocybin and the related tryptamine, norbaeocystin, on anxiety-like behavior in male and female rats. In Experiment 1, rats were treated with 1 mg/kg psilocybin (PSIL), 1 mg/kg norbaeocystin (NOR), or vehicle 30 min before a 5-min trial on an elevated plus maze (EPM) or in an open field test (OFT). On the EPM, PSIL led to decreased open arm time and fewer arm entries in males and females. NOR led to …

Bypassing Distributed Access Control For Subsystem‑Level Debugging, Rohit Sinha, Sumit Jha, Mayank Tutwani

Defensive Publications Series

Distributed access control in modern heterogeneous architectures often leads to debugging complexities during software development. Security enforcement logic is typically embedded across multiple initiators and targets, creating a wide search space when failures occur. It is often difficult to distinguish between functional software bugs and access control misconfigurations, as both may result in similar system behavior or silent failures. A system and method are disclosed for the selective relaxation of access control policies through a hardware‑assisted debug controller. The debug controller may provide granular enable signals to individual subsystems. Each subsystem may include a control status register that, when qualified …

Codex Oracle Architecture (Coa): Signal‑Driven, Meta‑Orchestrated Multi‑Agent Coordination For Autonomous Code Generation, Johny Manuel-Devadoss

Defensive Publications Series

This disclosure describes a novel orchestration architecture for multi‑agent code generation systems, referred to as the Codex Oracle Architecture (COA). COA introduces a signal‑driven coordination layer, a meta‑orchestrator (“Oracle Layer”), and a structured conflict‑resolution mechanism that enables large‑scale, adaptive, and emergent collaboration among heterogeneous AI agents. Unlike existing multi‑agent frameworks that rely on static workflows, deterministic message passing, or hierarchical control, COA enables dynamic agent activation, probabilistic decision making, and context‑aware collaboration. The architecture is designed to support autonomous code generation, refactoring, debugging, and long‑term software evolution in complex environments.

Human-In-The-Loop Workflow For Ai-Assisted Preliminary Bug Investigation, Mira Leung

Defensive Publications Series

A disclosed technology can address challenges in managing new software bugs when engineering capacity is limited, a situation which can be impacted by time-consuming initial investigations. The technology can provide a structured, human-in-the-loop workflow where a bug reporter may use an artificial intelligence (AI) assistant, such as a large language model, to perform a preliminary analysis at the point of bug discovery. This process, which can be guided by structured prompts, may generate an enriched bug report containing analysis from the AI, including, for example, potential root causes, code pointers, and ownership suggestions. By shifting a portion of the initial …

Ai-Driven Pipeline For Automated Prompt Refinement Using Evaluation Feedback, Cristina Elena Budurean, Quinn Halpin, Ibrahim Gunay

Defensive Publications Series

Conventional methods for improving generative artificial intelligence (AI) prompts can rely on manual analysis of evaluation feedback, a process that may be time-consuming, subjective, and may not scale effectively. A data-driven pipeline is described that can facilitate automated prompt refinement. The system may operate in a feedback loop, ingesting evaluation data, for example, rater scores and qualitative comments. The system can then use a large language model to perform a multi-stage analysis that may include sanitizing data, diagnosing response failures, extracting successful patterns, and resolving potentially contradictory feedback to generate a revised prompt. This approach can support a more scalable, …

System For Real-Time User Compositing Into Media Streams Using Generative Ai Conditioned On Extracted Scene Context, Dev Daftari, Akash Verma

Defensive Publications Series

A system is described for compositing a user's image into media streams protected by digital rights management (DRM). The system may operate via a multi-stage pipeline, which can begin with context extraction on a user device, such as a smartphone or smart television. Computer vision models may analyze a media stream to create a context packet detailing information such as scene lighting, spatial depth, and artistic style. This packet can then be used to condition a generative artificial intelligence (AI) model, which may synthesize the user's likeness into the scene with corresponding visual characteristics. A resulting composite can be rendered …

Arachne Aero-Skin, Michael Victor Caldwell Mr.

Defensive Publications Series

The Arachne Aero-Skin is a passive aerodynamic surface film designed to reduce aircraft skin-friction drag through microstructured riblet geometry aligned with local airflow. The system is intended for external application on non-structural aircraft surfaces and is designed for manufacturability, durability, and measurable performance under realistic contamination, cleaning, and environmental conditions.

This Phase 1 system excludes active flow control, propulsion modification, plasma systems, or engine integration.

Privacy-Preserving Cross-Customer Threat Intelligence Platform With Embedded Ml, Predictive Attack Trajectory, And Multi-Agent Trust Management For Web, Mobile, And Ai Agent Protection, Duncan Ndegwa Ndungu

Defensive Publications Series

This publication discloses twelve platform-scale security intelligence inventions for web, mobile, and AI agent protection. Core platform inventions (B1–B4) include: privacy-preserving cross-customer threat intelligence via a two-layer alias architecture with k-anonymity; SDK-embedded quantized ML inference (<100KB, INT8, sub-5ms) with knowledge distillation and signed over-the-air updates; consent-scoped alias lifecycle management for automatic GDPR/CCPA compliance; and multi-hop AI agent trust chains with configurable attenuation and cascading revocation. Advanced security infrastructure (B5–B10) covers IDOR detection via per-alias resource access baselines, runtime dependency integrity verification via Ed25519-signed manifests, AI agent output exfiltration detection via semantic and entropy analysis, multi-level TLS certificate pinning with safe rotation and air-gapped fallback, constant-time authentication response orchestration, and shadow agent detection via distributed registry and behavioral fingerprinting. Predictive infrastructure (B11–B12) includes DNS hijacking detection via multi-path resolution consensus with challenge-response verification, and a Bayesian predictive attack trajectory engine with pre-emptive countermeasure deployment and outcome feedback learning.

Comprehensive Pre/Post-Authentication Attack Detection And Mitigation Framework For Web, Mobile, And Ai Agent Applications, Duncan Ndegwa Ndungu

Defensive Publications Series

This publication discloses fourteen specialized attack detection modules operating within an SDK event observation pipeline at zero incremental infrastructure cost, covering both pre-authentication and post-authentication phases across web, mobile, and AI agent applications. Pre-authentication modules (A5–A10) detect password spraying via cross-account fingerprint correlation, mass registration abuse, AI agent tool-call sequence violations and infinite loops, OAuth redirect hijacking, and SDK configuration tampering. Post-authentication modules (A11–A18) detect MFA fatigue attacks, session fixation, business logic abuse via learned transaction flow graphs, refresh token theft via device fingerprint binding, indirect prompt injection via pre-ingestion content scanning, feedback poisoning, and clock manipulation via dual-clock comparison. …

Hukum Internasional Sebagai Sarana Pembangunan Masyarakat Internasional, Sri Setianengsih Suwardi

Jurnal Hukum & Pembangunan

Abstract

Electronic Recording Of Custodial Interrogations: A Jurisdictional Analysis Of U.S. State Requirements, Alyssa Fox

Psychology Student Publications

• Custodial interrogations serve as the primary mechanism through which information is gained for evidence.
• Human memory is reconstructive rather than reproductive, leaving it vulnerable to contamination and suggestibility, especially with employment of psychological interrogation tactics and the inherently coercive nature of custodial interrogations. This causes false confessions, which lead directly into wrongful convictions.
• Juveniles and people with disabilities are particularly vulnerable to this, with heightened compliance and diminished decision-making capacity.
• Electronic recording of custodial interrogations has emerged as a safeguard against false confessions through documentation, accountability, and preservation; however, practical implementation remains limited.

Effects Of Mindfulness Induction Before And After Encoding On False Recognition, Jacob Phillips

Psychology Student Publications

• Mindfulness is a mental state which refers to complete mental awareness of one’s surrounding emotions and events, which if practiced may hold greater implications for improvements in memory and attention (Namias & Huff, 2024).
• Recent studies examined mindfulness on false memory for DRM word list materials (e.g., Alberts et al., 2017; Calvillo et al., 2018; Wilson et al., 2015), reporting mixed findings.
• Practically, if a mindfulness technique were to be administered to eyewitnesses by police, this would occur prior to memory retrieval and concern negative emotional information.
• This study builds on a prior student study (Frederickson, 2022) to examine the …

Doomed To Scroll: Examining The Role Of Motives In Problematic Social Media Use And Associated Psychopathologies, Charlotte Eley

Psychology Student Publications

Problematic Social Media (PSMU) is a serious concern in society—as illustrated by recent lawsuits filed against big tech companies.

PSMU is related to anxiety and depression, but the directionality of that relationship remains unclear (Andreassen et al., 2016; Coyne et al., 2020).

Time spent on social media, by itself, is not a strong indicator of negative physical or mental health outcomes (Burénet al., 2023; Coyne et al., 2020), suggesting that certain motivational or dispositional factors may underlie and further explain PSMU.

This study aims to examine how one’s motives behind using social media relate to the experience of fear of …

Evil Done In The Age Of “New Terrorism”: A Red-Team Study Of U.S. Lone Actor Target Selection Across Weapon Conditions, Torrin Jacobson

Psychology Student Publications

Background of the Present Study 1. Starting in the early 2000s, the internet has played a larger role in all aspects of terrorist activities, creating the age of “New Terrorism”. 2. This has led to a more unstructured model of violence, allowing homegrown domestic lone actors to become the largest terrorist threat in America. The Present Study 3. However, little research has been conducted on how this affects target selection decisions. Building on prior lone actor–red team research (Romyn & Kebbell, 2014; 2018), the present study uses a red team simulation to examine how lone actor target selection is influenced …

Ceres Cow Excrement For Renewable Energy Supplies, Jeremy J. Land

Chemistry and Chemical Engineering Student Publications

On March 27th, 2026, President Trump announced the finalization of the Renewable Fuel Standard “Set 2”, which establishes a 60% increase in the requirement for renewable fuels from 2025 to 2026 & 2027. AIChE issued the 2026 Senior Design Challenge to design a renewable natural gas plant for a 12-Farm Dairy Co-Op in Green Bay Wisconsin. This design integrates the latest cutting-edge technologies to sustainably optimize NPV.

Large-Scale Production Of Polyethylene Furanoate From Algae- Derived Feedstocks, Anjolaoluwa Buraima, Jasmine Gordon, Christian Jung, Brianna Oropeza

Chemistry and Chemical Engineering Student Publications

This work presents a process to convert microalgal feedstocks (Chlorella vulgaris) into Polyethylene Furanoate (PEF), a biobased alternative to Polyethylene Terephthalate (PET) with improved barrier properties, proving a sustainable pathway for bioplastic production.

Halo: High Autonomous Low-Swap Operations, Sloan Hatter, Blake Gisclair

Mathematics and System Engineering Student Publications

Orbital object detection is a vital aspect of space operations, particularly for identifying satellite components. Convolutional Neural Networks (CNNs) are typically used for such operations by running onboard models directly on satellite systems. However, a new neural network architecture, known as Vision Transformers (ViTs), have shown greater effectiveness due to their ability to capture global context. One main issue of deploying systems with such capabilities is resource allocation. One solution is to run models on a Low-SWaP system; however, this results in inefficient performance. To enable efficient ViT operations on Low-SWaP systems, the model must be scaled down through quantization, …

Stochastic Network Resilience Under Random Failures, Blake Gisclair

Mathematics and System Engineering Student Publications

This project investigates threshold-crossing probabilities in stochastic networks. Using probabilistic modeling and transform-based analytical methods, the work derives expressions that characterize when cumulative losses exceed prescribed limits with the goal of providing insight into the relationship between local random behavior and global network risk.

Determining Material Transport Method For Moon Colony Using Differential Equations, Scott Meeson, Anthonie Page, Matas Vaitkevicius

Mathematics and System Engineering Student Publications

NASA Artemis Missions: NASA’s Artemis program marks a fundamental shift from short-term lunar exploration to sustained, permanent colonization.

Slait - Secure Language Assembly Inspector Tool, Michael Bratcher, Maria Linkins-Nielsen

Electrical Engineering and Computer Science Student Publications

Develop a secure web-based platform that enables users to:

• Upload assembly programs through a browser
• Select instruction inspection points
• Execute code inside an isolated sandbox
• Capture register and flag state changes
• Visualize execution behavior step-by-step

Diode-Pumped Solid-State (Dpss) Laser, Ryan Farrar, Kiahna Taylor, Jules Stone, Finn Mcmanus, Zoe Kreisler, Reis Knowles

Electrical Engineering and Computer Science Student Publications

The objective of this project is to create a working Nd:YAG laser design using an 808nm laser instead of a traditional flashlamp. The reason for the 808nm laser is to enable controlled lasing, and furthering accuracy & efficiency relative to a flashlamp.

Rapid Reach, Rishi Ammanabrolu, Alex Dumbell, Peyton Hay, Ashley Hurtado, Ryan Matthews, Mac Mchale, Sean Miller, Dan Zschau

Electrical Engineering and Computer Science Student Publications

Survival of out-of-hospital cardiac arrest depends on rapid heart defibrillation, yet automated external defibrillator (AED) retrieval, high acquisition costs, and maintenance requirements often limit unit availability. Consequently, the delay inherent in traditional manual retrieval and EMS arrival frequently prevents aid from reaching victims in time.

Chess Observation Based Operable Technology (Cobot), Brandon Goerz, Jeremy Hay, Luke Jacobsen, Sean Kalkiewicz, Logan Steele

Electrical Engineering and Computer Science Student Publications

This project aims to develop an autonomous robotic chess system capable of interpreting board state and physically executing moves. With a focus in real time against a human opponent. Utilizing integrating computer vision, game logic, user friendly GUI, and a robotic arm.

Srcis: Human-Robot Collaboration In Urban Search And Rescue Operations, Younghoon Cho, Yavanni Ensley, Jaylin Ollivierre

Electrical Engineering and Computer Science Student Publications

Search and Rescue Coordinated Intelligence System (SRCIS) is a human-agent system designed to:

• Improve the effectiveness of real-time search and rescue operations.
• Integrate human judgement with robotic autonomy and capabilities
• Enable coordinated action and adaptive response in dynamic environments.

Nocap: Article Fact-Checking With Ai, Thomas Chamberlain, Anthony Ciero, Varun Doddapaneni, Joshua Pechan

Electrical Engineering and Computer Science Student Publications

Fact checking media is important for properly obtaining information

Create a website that uses AI knowledge to allow users to fact check an article

Give these articles an authenticity score and report on what is fact or fiction

Aggregate scores of articles by the same publisher in a database allowing users to view their scores and article authenticity reports