Digital Commons Network^™

Aid And Assist Cases In Multnomah County: An Exploration Of Ors 161.370, Savannah Jurasek

Dissertations and Theses

Individuals with severe mental illness (SMI) are highly overrepresented in jails. In Oregon, these individuals can be eligible for what is referred to as the aid and assist process (ORS 161.370) which is designed to facilitate restorative care in efforts to ensure that vulnerable individuals can rationally participate in their criminal proceedings. However, continuous escalation in aid and assist orders (109.3% between 2011-2025) has led to strain on the Oregon State Hospital, the primary care facility for this population. As a consequence, defendants with SMI are spending unnecessary time in custody, despite hospitalization admission guidelines governed by previously decided case …

Shifting Perspectives In Mathematics: Examining Preservice Elementary Teachers' Evolving Conceptions Of Mathematics, Identity, And Social Inequality Through Course Design, Autumn Thu Pham

Dissertations and Theses

Mathematics is often viewed, taught, and learned as an abstract, stand-alone subject, with an emphasis on procedures that are frequently disconnected from learners' lived experiences. Within this framing, limited attention is given to students' affect and identities in relation to mathematics. As a result, opportunities to engage with mathematics as a social, sociopolitical, and empowering tool remain rare. These patterns highlight an important implication for teacher education programs: when mathematics is framed primarily as abstract and procedural, preservice elementary teachers (PTs) may enter the profession lacking strong conceptual understanding, pedagogical flexibility, and the social and political awareness needed to effectively …

Rolling-Shutter Image Skew As A Visual-Inertial Motion Signal In Imu-Synchronized Multimodal Capture, Clifford T. Smyth

Defensive Publications Series

In a sensor system that records a rolling-shutter image stream together with a synchronized, higher-rate inertial measurement unit (IMU) stream, the intra-frame geometric skew produced by rolling-shutter readout is treated not as an artifact to be removed but as a usable, temporally structured motion signal. Because a rolling-shutter frame exposes its rows sequentially, the frame encodes camera and scene motion over the readout interval. When the frame is time-correlated with inertial data at sufficient resolution, the inertial stream can be used to estimate the camera motion during readout, which in turn supports two complementary representations of each frame: (1) an …

Fibonacci Global History Length (Fihl) Dynamic Branch Predictor Architecture, Gopi K. Tummala

Defensive Publications Series

The Fibonacci Global History Length (FIHL) Branch Predictor is a highly constrained hardware architecture designed to optimize speculative execution in deeply pipelined microprocessors. Operating within a strict 32-kilobit hardware budget, the FIHL architecture synthesizes the frameworks of perceptron learning and hash indexing while replacing traditional geometric history length progressions with the Fibonacci sequence. By natively mapping global history lengths to the Fibonacci sequence across six parallel branch history tables, the design efficiently correlates both highly localized instruction patterns and distant control-flow dependencies without the exponential memory footprint of traditional pattern history tables. Empirical evaluations across diverse workloads demonstrate that this …

Crowdsourced Biometric Synchronization For Video Intensity Mapping And Benchmarking, Alan She

Defensive Publications Series

This paper describes a biometric-to-video synchronization engine that pairs wearable physiological sensors with a distributed video platform for crowdsourced intensity mapping and normalized effort-based benchmarking. Fitness video content on open platforms typically relies on subjective difficulty labels assigned by creators, which fail to account for the physiological diversity of viewers. The synchronization engine establishes a temporal sync anchor between a wearable device's biometric data stream and the video playback timeline, employing clock-drift compensation to align UTC-stamped biometric packets with the relative playback head and a latency correction algorithm to account for physiological response delay. As anonymized, normalized heart rate data …

Dynamic Information-Density-Aware (Dida) Video Playback Scaling, Alan She

Defensive Publications Series

This paper describes a Dynamic Information-Density-Aware (DIDA) Playback System, which automatically modulates video speed on a per-segment basis according to measured content density. Video content exhibits asymmetric information density, where some segments contain dense instructional material while others contain filler, repetitive transitions, or silence. Static playback speed forces viewers to choose between missing details during information spikes in dense segments or enduring disengagement during sparse ones. DIDA uses a Smart Speed engine combining visual frame classification, audio speech-rate measurement, and silence detection with crowdsourced viewer engagement data to compute an optimal playback rate for each timestamp.

An Algorithmic Density Scorer …

Investigation Of A Shielded Magnetic Switching Architecture And Magnetic Energy Transfer Mechanisms, Peter Branton

Defensive Publications Series

This paper presents a magnetic switching architecture based upon the controlled exposure and shielding of permanent magnetic fields.

The system combines:

• Permanent magnets

• Movable magnetic shielding

• Attraction phases

• Repulsion phases

• Force-balanced switching mechanisms

• Mechanical momentum recovery

The architecture was developed through the progressive elimination, reduction, or counterbalancing of apparent energy costs commonly associated with magnetic switching systems.

The resulting design raises a fundamental question:

Can the complete behavior of the disclosed system be fully explained using conventional magnetic energy accounting, or does the geometry reveal aspects of magnetic energy transfer that warrant further investigation?

This document presents a specific engineering …

System And Method For User-Owned Longitudinal Memory And Interpretation System With A Provenance-Tagged Interpretive Ledger, Engine-Interchangeable Inference, Federated Validation, And Generational Maintenance, Joseph Jm Walker

Defensive Publications Series

Contemporary personal-AI systems preserve continuity in the weakest possible way: the provider owns the model, the memory, and the interface, and the user retains accumulated context only so long as the service remains available and willing to keep it. When a model changes, a platform resets memory, or a provider alters policy, the user's interpretive history can vanish. This disclosure presents the Continuity Node Framework, a user-owned, local-first, longitudinal memory-and-interpretation architecture in which the durable asset is not the AI model but the preserved, provenance-tagged map of a person's reasoning, values, patterns, and tested interpretations over time, and in which …

Evaluating Agent Cognitive Resilience Using Controlled Environmental Inconsistencies, Isaac Leimgruber, Nicolas Zimmermann

Defensive Publications Series

Conventional evaluation methods for autonomous agents may prioritize task completion without assessing an agent's ability to handle systemic discrepancies between its instructions and its operational environment. A dynamic evaluation framework is described that can assess an agent's cognitive resilience. The framework may operate by introducing controlled inconsistencies, for example, planted traps, into a sandboxed environment, which can create a conflict between the agent's instructional data and the runtime reality. The system can then evaluate the agent's response, focusing on its ability to detect the discrepancy, classify its root cause, and propose a structural resolution rather than focusing on task completion. …

Predictive Hardware State Mitigation Using Telemetry And Feedback, Mohsen Heidarinejad, Farid Kenarangi, Arpit Mittal, Amin Khajeh

Defensive Publications Series

Varying computational tasks introduce thermal and power dependencies within modern computing devices. Static threshold policies might not fully capture cumulative operational stress, potentially causing over-throttling or delayed hardware responses. A closed-loop machine learning framework is disclosed that dynamically evaluates multidimensional telemetry data to compute a predictive risk score. A feature selector extracts direct measurements, system activity indicators, temporal features, and health indicators. Based on the calculated risk score, an arbitrator dynamically applies mitigation actions (e.g., scaling component voltage and frequency states). A model corrector operates during hardware idle periods to iteratively refine predictive modeling using observed performance metrics. The disclosed …

Generative Media Repair For Uninterrupted Transcoding With An Asynchronous Approval, Nikita Agarwal

Defensive Publications Series

The process of ingesting large-scale media files may be interrupted by data corruption, which can necessitate a re-upload and re-transcode, consuming network and computational resources. Described systems and methods can address this by detecting corruption during ingestion, generating a provisional synthetic patch for the corrupted portion, and allowing the transcoding process to proceed. A cryptographic manifest can be created to document the change, and the provisionally repaired asset may be held in a quarantined state. An asynchronous approval workflow can then allow a content partner to review, approve, or reject the patch, with a fallback for providing a corrected segment. …

Ai Output Enrichment System With Data-Shape-Aware Routing, Enrich Directive Protocol, And Context-Aware Block Absorption, Bhautik Kishorchandra Doshi, Mark Goho, Zac Lovoy, Juan Carlos Pontaza, Arpita Mehta

Defensive Publications Series

Current artificial intelligence (AI) systems can generate semantically relevant markdown responses, but they do not reliably generate high-quality interactive user interfaces. Techniques described herein address that gap through a two-layer downstream enrichment system that transforms arbitrary AI-agent markdown into rich user interface components without modifying the originating model.  Layer 1 is a deterministic, data-shape-aware pipeline that converts markdown blocks into charts, Key Performance Indicator (KPI) cards, tables, and titled sections using specific routing and absorption heuristics.  Layer 2 is an optional AI presentation layer that enhances the structured output through semantic highlighting, chart refinement, thread-context-aware adaptation, and layout optimization, without …

Agentic Graph Querying On A Sharded Architecture Using A Large Language Model, Sai Charan Tej Kommuri

Defensive Publications Series

Using large language models (LLMs) to query large, scale, graph, structured data can present challenges, as encoding an entire graph into a single prompt may exceed context window limits and can lead to reduced accuracy on multi-hop queries. Systems and methods can partition a graph into a collection of smaller, human-readable documents, or shards. An agentic orchestration process may use a global symbolic index, contained within a summary shard, to locate and retrieve relevant shards on demand. This process can decompose a complex query into a sequence of single-hop LLM calls, where each call can operate on a context comprising …

Transmission Of Firm-Level Demand Shocks To Stock Returns: Evidence From 10-K Text Analysis, Dylan Gunjan Parikh

Economics Undergraduate Senior Theses

Industrial organization and corporate finance papers that measure firm-level demand characteristics employ price, quantity, and product characteristic data that is unavailable in public financial disclosures. As a result, cross-sectional asset pricing literature attention to demand-side factors is limited. This paper constructs a demand shock measure from natural language processing of 28,263 publicly disclosed 10-K filings from 2001 to 2020. I find that a 1SD demand shock increases contemporaneously predicts a 1.8% increase (SE = 0.4%) in returns. Long-short portfolio sorted on demand shock generates 8.5% alpha (SE = 1.9%) against combined Fama-French and Q-factor models and a 0.91 sharpe ratio …

Fisheye Camera Object Detection For Traffic Surveillance, Hugo Yang, Robert Luo

Computer Science and Engineering Senior Theses

Effective traffic management is hampered by the physical limitations of traditional pinhole cameras, whose narrow fields of view create blind spots that require costly multi-camera infrastructure to overcome. Fisheye cameras offer a wide-angle alternative capable of single-camera intersection coverage, but the radial distortion inherent in their optics renders standard object detection algorithms unreliable, limiting their practical deployment in traffic surveillance.

This thesis investigates specialized object detection pipelines for fisheye traffic imagery by reproducing and building upon two top-ranked submissions from the 2025 AI City Challenge Track 4: the VNPT and SKKU-AutoLab pipelines. Both were successfully reconstructed outside their original containerized …

Corrigendum To " Computational Investigation Of Cavitation Inception In Centrifugal Pumps"

Mansoura Engineering Journal

Abstract is not required.

Ad Fontes: Kierkegaard And Macdonald On “Original” Christianity, M. G. Piety

North Wind: A Journal of George MacDonald Studies

No abstract provided.

Toward An Account Of Visual Aesthetic Experience In Multimodal Large Language Models, Batuhan Saridede

Cognitive Science Senior Theses

While Multimodal Large Language Models (MLLMs) increasingly mediate visual culture, far less is known about how MLLMs themselves evaluate aesthetic value and how those evaluations shift under different beliefs about authorship. This thesis investigates how three commercial MLLMs (ChatGPT, Claude, and Gemini) appraise visual artworks across six dimensions: liking, beauty, profundity, worth, narrativity, and intentionality. Using a balanced dataset of 100 artworks, half human-generated and half AI-generated, with representational and abstract works equally represented, each model evaluated every image under four provenance conditions: unspecified origin, inferred origin, assumed AI origin, and assumed human origin. Results show that representationalism in visual …

Soil Health Analysis (Lesson 2), Mara Johnson, Madhav P. Nepal, Jiyul Chang

iLEARN Teaching Resources

In this lesson, students will build on the previous lesson (reading and analyzing the Three Sisters chapter from Braiding Sweetgrass) by experimenting on soil in their schoolyard. Students will collect soil samples from multiple locations around their school grounds and evaluate soil texture, structure, infiltration, color, organic matter, and pH. Students Through field observations and laboratory analysis, students examine how soil characteristics influence plant growth and ecosystem health. Students connect modern soil science with Indigenous agricultural knowledge, particularly the Three Sisters planting system described in Braiding Sweetgrass by Robin Wall Kimmerer. By exploring how healthy soil supports sustainable agriculture, …

Ml Models For Child-Parent Speech Diarization, Kenneth Kang

Computer Science and Engineering Senior Theses

This senior design thesis presents a machine learning research pipeline for child-parent and child-directed speech diarization. Speech diarization is the task of determining who spoke and when in an audio recording. Although this problem is well studied in adult meeting, broadcast, and conversational speech, child-parent audio is a more uneven setting. Children may speak in short turns, change pitch quickly, vocalize without producing clear words, interrupt adults, overlap with adult speech, cry, laugh, or code switch. These behaviors are normal in real family interaction, but they can confuse diarization systems that were mostly designed and evaluated on adult speech.

The …

Effect Of Implementing An Evidence-Based Clinical Practice Intra-Hospital Transport Guideline For Hospitalized Children: A Type Iii Hybrid Implementation-Effectiveness Study, Yang Li, Yuxia Yang, Jing Hu, Wenchao Wang, Yun Jin, Weijie Shen, Yanhong Zhang, Yingfeng Zhou, Ye Cheng, Jos M Latour, Ying Gu

School of Nursing and Midwifery

BACKGROUND: Intra-hospital transfers (IHT) of hospitalized children are unavoidable practices often performed with emergency patients and postoperative patients. Standardizing IHT processes to minimize adverse events might improve children's outcomes. We developed an evidence-based clinical practice IHT guideline for hospitalized children. The aim of this study was to evaluate the implementation process and the effectiveness of the implementation of this guideline on patient outcomes, healthcare professionals' knowledge and behavior, and hospital organizational context.

METHODS: A type III hybrid effectiveness-implementation design was adopted, using a pre-post intervention trial (January-December 2024). Data of patient demographics, transport-related outcomes, and healthcare providers' knowledge and compliance …

Multidomain Expert Evaluation Of Leading Large Language Models As Providers Of Vaccination And Preventive Medicine Information, Marcello Di Pumpo, Leonardo Villani, Vittorio Maio, Maria Rosaria Gualano, Eleonora Marziali, Lucia De Maio, Rossella Mancini, Stefania Boccia, Walter Ricciardi, Patrizia Laurenti

College of Population Health Faculty Papers

OBJECTIVES: Vaccination is one of the most effective public health interventions. Large language models (LLMs) show great capability for providing health information. This study compared the performance of ChatGPT 3.5 (G3E), ChatGPT 4o in English (G4E), Claude 3.0 (CDE), Gemini 1.5 (GME), and ChatGPT 4o in Italian (G4I) in delivering information on vaccination and preventive medicine.

STUDY DESIGN: Mixed-method analysis evaluating large language models.

METHODS: Twenty-six expert-designed healthcare scenarios were used to evaluate each model through an adapted DISCERN-based instrument. Four experts independently rated outputs across six domains: Information Reliability, Information Quality, Medical Appropriateness, Impact on Vaccine Hesitancy, Potential for …

Book Review: The Evolution Of Pragmatism In India: Ambedkar, Dewey, And The Rhetoric Of Reconstruction, Scott R. Stroud, University Of Chicago Press: 2023, Joshua Forstenzer

Dewey Studies

No abstract provided.

Spiritual Democracy & Democratic Faith: Dewey And Vivekananda On Pluralism And Freedom, Albert R. Spencer

Dewey Studies

No abstract provided.

Critiquing Class And Caste On Three Continents: Dewey, Ambedkar, And Mosca On Social Endomosis, Emerson Bodde

Dewey Studies

No abstract provided.

Exploring The Link Between Substance Use Severity And Self-Stigma: The Moderating Role Of Enacted Stigma, Alaya Shelton

McNair Culminating Research Projects

Self-stigma has been shown to negatively impact treatment engagement, recovery, and reintegration outcomes among individuals with substance use and criminal histories (Moore et al., 2023). Further, prior research has shown that markers of an individual’s substance use treatment history (e.g., number of prior treatment episodes and perceived substance use severity; Hammarlund et al., 2018; Luoma et al., 2012; Silveira et al., 2016) and negative experiences with medical professionals (Hoover et al., 2022; Muncan et al. 2020) are closely linked to self-stigma. While these factors independently contribute to one’s level of self-stigma, to our knowledge, no prior work has examined how …

Kerygma As A Foundational Component Of Paul's Missional Methodology, Bruce Gregory Gale

Witness

No abstract provided.

How Systems Use The Research Organization Registry (Ror) For Research Integrity, Maria Gould, Adam Buttrick

FORCE 2026

As scholarly publishers strive to ensure the integrity of the scholarly record, verified author affiliations have become a key metric to assist with assessment of manuscript submissions. For instance, a recent article in Nature used author affiliations to identify problematic research practices at particular institutions, and a recent STM report on Trusted Identity in Academic Publishing points out that a verified author affiliation valuable as it links an individual to an organisation, providing a route for accountability where there would otherwise be none.

Knowing that there is a confirmed link between an author and a reputable research organization is a …

Promoting Crisis-Ready Data Policies In Science Publishing: Implementing Unesco’S Open Science Guidance For Resilient Preservation, Response, And Recovery, Francis P. Crawley

FORCE 2026

Crises disrupt not only societies but also the continuity of scientific data and publications essential for evidence-based decision-making. Preserving the integrity, accessibility, and long-term usability of these resources during disruptions has become a global priority. In response, UNESCO, with the support of CODATA, has developed a suite of Open Science Toolkit instruments (Factsheet, Guidance, and Checklist) on ‘Developing Data Policies for Times of Crisis Facilitated by Open Science’. This presentation examines how these instruments can strengthen data preservation, response, and recovery within scholarly communication. By promoting crisis-ready data policies supported by AI-enabled systems in science publishing, the UNESCO approach connects …

Adaptive, Hardware-Aware Routing Of Ai Tasks Based On Semantic Complexity, Utkarsh Bhardwaj, Shivank Awasthi

Defensive Publications Series

This disclosure describes an adaptive orchestration system that can dynamically route computational tasks to an appropriate backend, such as a local processor or a remote cloud service. The system can use a multi-objective optimization approach, balancing the semantic complexity of a given task, which may be estimated by a lightweight proxy model, against the real-time physical state of the device, including its thermal status, battery level, and network connectivity. This method of hardware-aware routing can proactively manage thermal loads and power consumption, which may improve operational efficiency and mitigate performance degradation associated with system-wide throttling on such devices.