Digital Commons Network^™

Multi-Frequency Temporal Sampling For Training Video Object Counting Models, Ivor Rendulic, Filip Pavetić

Defensive Publications Series

Machine learning models may face challenges in counting distinct objects in videos, particularly when presented with variations in frame rates or object speeds. Disclosed systems and techniques can address these challenges with a data augmentation methodology for generating training data. For example, an approach can involve creating multiple training examples from a single source video by sampling its frames at various temporal frequencies. A dynamic labeling protocol may be used to assign an object count label to a new sequence that reflects the number of objects discernible in that specific, potentially sparser, sequence. Training a model on these varied representations …

System And Method For Predictive Network Equipment Decommissioning Management, N/A

Defensive Publications Series

The technology described in this paper relates to a predictive network equipment decommissioning management system. The described technology automates the creation and management of decommissioning requests to improve accuracy and reduce cycle times. By utilizing multi-signal context heuristics, the system determines the specific decommissioning scenario for various assets. A hybrid inference engine is employed to predict the presence of unmonitored passive components. An ambiguity resolution engine identifies vague or untagged parts using computer vision and topological exclusion techniques. A dynamic granularity transformation engine re-aggregates discrete components into top-level assemblies, accommodating for configuration drift over time. Furthermore, a retrofit analysis engine …

Automated Security Policy Validation From Natural Language Documentation Using Large Language Models, Leonid Kuligin, Aleksandr Ostapenko

Defensive Publications Series

Determining security permissions from natural language documentation, for example, runbooks, can be a time-consuming and error-prone process that may lead to runtime failures or security vulnerabilities. A system can use large language models (LLMs) to analyze documentation, infer a candidate permission policy, and generate a corresponding test script. The script can then be executed in a sandboxed environment using the candidate policy. An iterative refinement loop may diagnose permission-related failures and use an LLM to propose policy modifications to address those failures. This automated process can assist in generating a functional permission policy derived from operational instructions, which may reduce …

Session Management Architecture For Server-Sent Events Transport In Persistent Connection Delivery Systems, Aaron Burton

Defensive Publications Series

A method for operating a session management process over an SSE transport, where the process maintains an in-memory map of session identifiers to open HTTP response streams, receives personalization payloads from an upstream enrichment pipeline, and writes those payloads as formatted SSE event frames to all registered EventSource connections matching the target session identifier. The process stores HTTP response stream references rather than WebSocket handles, delivers payloads by writing SSE-formatted text to each open stream, and relies on HTTP keep-alive semantics and the EventSource reconnection protocol to manage connection lifecycle without application-layer ping/pong. Client-side reconnection is handled natively by the …

Origai Ecosystem - Integrated Ai-Powered Entrepreneurship Platform, Clinton Orah

Defensive Publications Series

This publication discloses the complete technical architecture of the OrigAI Ecosystem: an integrated suite of AI-powered products guiding entrepreneurs through a six-phase startup lifecycle — Think, Plan, Build, Launch, Scale, and ongoing operations. The primary product, BCAI (Business Creation AI), implements a phase-embedded plan builder architecture in which AI tool capabilities surface as contextual engines within business plan sections rather than as a standalone toolkit, with outputs written permanently to a structured business plan. The ecosystem includes a 20+ tool suite spanning competitive intelligence, offer design, viral marketing, pitch coaching, business registration, and scale-phase analytics, all operating on a shared …

Qbiasnet: Quantum-Enhanced Variational Classifiers For Ethical Bias Detection In Multimodal Ai Models, Nikunj Doshi, Kavach Shah, Shikhar Patel

Artificial Super Intelligence (ASI) Conference

Bias in multimodal AI systems that jointly process image and text inputs creates measurable risks in sensitive deployment contexts including public health, financial services, and automated hiring. Classical detection approaches face a fundamental architectural limitation in that they cannot efficiently model intersectional bias. Intersectional bias emerges from the nonlinear interaction of multiple protected attributes simultaneously across visual and linguistic modalities. This paper introduces QBiasNet, a hybrid quantum-classical system that encodes cross-modal CLIP embeddings into an 8-qubit Variational Quantum Circuit (VQC) implemented in PennyLane. By exploiting quantum entanglement, the VQC learns high-order feature correlations that linear probes and shallow neural networks …

Meduncertainvlm: Multi-Modal Uncertainty Quantification In Vision-Language Models For Clinical Documentation, Shikhar Patel, Rushabh Darji

Artificial Super Intelligence (ASI) Conference

Vision-language models are increasingly deployed for clinical documentation tasks in radiology. A common application involves extracting diagnostic labels from chest radiographs with reports. These models must communicate calibrated uncertainty to avoid influencing patient care incorrectly. Overconfident predictions from poorly calibrated models pose a documented patient safety risk. Existing medical vision-language models produce only point estimates without any confidence bounds. Standard post-hoc calibration methods such as temperature scaling omit cross-modal signals entirely. They cannot detect cases where image and text branches make genuinely inconsistent predictions. This paper presents MedUncertainVLM, a framework that addresses this gap directly and systematically. The system uses …

Ballistic Trajectories From Triangular Libration Points To Moon, Collin Gentry

Miners Solving for Tomorrow Research Conference

As stable points in the Earth-Moon system, the triangular libration points, L4 and L5, have many advantageous properties for space exploration. Ballistic trajectories at varying delta-Vs and impulse angles are computed and propagated from the libration points, and trajectories that arrive at the lunar surface are investigated. Preliminary conclusions are drawn about the accessibility of the lunar surface from the triangular libration points, and the implications for mission design are discussed. These trajectories present an alternative means of accessing the Moon, expanding the viability of the triangular points for missions and offering additional options for the use of cisular space.

Ai Adoption Tensions For Organ Procurement Organizations, Joely Grace Hall

Miners Solving for Tomorrow Research Conference

Artificial intelligence (AI) has the potential to improve efficiency in healthcare, yet its adoption remains limited, with only 22% of healthcare organizations having implemented domain-specific AI tools. Adoption may be especially complex in specialized domains such as organ transplantation, where ethical, legal, and operational challenges are dominant. This study examined factors influencing AI acceptance within Organ Procurement Organizations (OPOs), focusing on technological, organizational, and environmental contexts.

Semi-structured interviews with 16 OPO executives from 10 OPOs revealed key tensions shaping AI adoption. We identified five tensions that are holding back OPO leaders from AI adoption, (1) misconceptions, (2) training approach, (3) …

Cross Correlation-Based Physiological Synchronization For Multi-Modal Wearable Cognitive Stress Monitoring System, Fariha Alam, Nora Tin, Razvan Voicu

Artificial Super Intelligence (ASI) Conference

Cognitive stress arises from sustained mental demand, information overload, or task complexity, and requires continuous monitoring for timely detection and intervention in real-world settings. It produces subtle physiological changes, including shifts in heart rate and autonomic activity that require continuous monitoring to detect reliably. Wearable sensors such as photoplethysmography (PPG) and electrodermal activity (EDA) enable non-invasive tracking of these responses. However, multi-modal sensor integration remains challenging, as hardware or software-level synchronization does not consider the physiological response delays. To address this, the study collected PPG and EDA sensor data from ten participants under two cognitive stress-inducing conditions. After preprocessing, heart …

Vibroacoustic Characterization Of Manipulator Robot Via Kinematic Discretization, Gershom Richards Pe, David A. Guerra-Zubiaga

Artificial Super Intelligence (ASI) Conference

Using vibroacoustic signals to characterize the health and status of industrial equipment is well-used. Many recent studies leverage a black box approach for developing a vibroacoustic machine learning (ML) architecture capable of identifying anomalous behaviors in the robot operation. While useful for routine automation systems, it is not suitable for dynamic robot systems with flexible or behavioral programming, or robots that will experience consistently changing environmental factors. To address these shortcomings, a discretized approach is explored. The proposed Long Short-Term Memory (LSTM)-Transformer Hybrid ML architecture segments its training data by manipulator joints to incorporate the impact of each subsystem on …

Agripestdatabase-V1.0: A Structured Insect Dataset For Training Agricultural Large Language Model, Yagizhan Bilal Durak, Ashley Morgan-Olvera, Ahsan Ul Islam, Iftekhar Ibne Basith, Shahidul Islam, Syed Hasib Akhter Faruqui

Artificial Super Intelligence (ASI) Conference

Agricultural pest management increasingly relies on timely and accurate access to expert knowledge, yet high quality labeled data and continuous expert support remain limited, particularly for farmers operating in rural regions with unstable or no internet connectivity. At the same time, the rapid growth of artificial intelligence (AI) and large language models (LLMs) has created new opportunities to deliver practical decision support tools directly to end users in agriculture through compact and deployable systems. This work addresses (i) generating a structured insect information dataset to be used for LLM training, and (ii) adapting a lightweight LLM model (<= 7B) by fine tuning it for possible future edge device uses in agricultural pest management. The textual data collection was done by reviewing and collecting information from available pest databases and published manuscripts on nine selected pest species. These structured reports were then reviewed and validated by a domain expert. From these reports, we constructed question-answer (Q/A) pairs to support model training and evaluation. A LoRA-based fine-tuning approach was applied to multiple lightweight LLMs and evaluated. Initial evaluation shows that Mistral 7B achieves an 88.9% pass rate on the domain-specific Q/A task, substantially outperforming Qwen 2.5 7B (63.9%), and LLaMA 3.1 8B (58.7%). Notably, Mistral demonstrates higher semantic alignment (embedding similarity: 0.865) despite lower lexical overlap (BLEU: 0.097), indicating that semantic understanding and robust reasoning are more predictive of task success than surface-level conformity to reference text in specialized domains. By combining expert organized data, well structured Q/A pairs, semantic quality control, and efficient model adaptation, this work contributes towards providing support for farmer facing agricultural decision support tools and demonstrates the feasibility of deploying compact, high-performing language models for practical field-level pest management guidance.

Bridging Economic Growth And Literacy: Mediation–Moderation Pathways Linking Agriculture, Environment, And Poverty Reduction Across Asian Economies, Muhammad Abubakar, Wasim Abbas Shaheen, Umair Umer

Business Review

In the framework of reducing poverty, this study explores the numerous connections between economic, environmental, and agricultural aspects, paying particular attention to the moderating role of literacy. The Study aims to assess how agricultural employment, arable land, forest area, fertilizer usage, and ecological resources shape poverty outcomes in Asia. Utilizing panel data from 46 nations between 2000 to 2023, sourced from the World Development Indicators, the analysis applies advanced econometrics such as FMOLS and DOLS, alongside a panel co-integration framework validated through panel unit root and cointegration tests. Results indicate that agricultural employment significantly reduces poverty, arable land has mixed …

Implementation Of A Human Donor Breastmilk Education Program On The Usage Rates Of Pasteurized Human Donor Breastmilk For Supplementation Of Breastfed Infants In The Well-Baby Nursery, Nicole Sadorra

Doctor of Nursing Practice Projects

Background: Exclusive breastfeeding provides significant health benefits for infants and lactating individuals; however, national rates remain below Healthy People 2030 targets. Evidence suggests that infants supplemented with pasteurized human donor breast milk (HDBM) during postpartum hospitalization have higher exclusive breastfeeding rates at discharge and at six months. At a suburban Maryland hospital, formal HDBM education was not routinely provided, contributing to low utilization and stagnant breastfeeding rates.

Purpose: To determine whether implementing a structured HDBM education program for postpartum parents increases HDBM supplementation among breastfed infants and improves exclusive breastfeeding rates at discharge.

Methods: This pre-/post-test quality improvement project was …

Fcrh Honors Program: 2025-26 Year In Review, Fcrh Honors Program

FCRH Honors Program Newsletters and Reports

No abstract provided.

تقييم أثر تطوير محاور الحركة على المرونة الحضرية في المناطق ذات القيمة – حالة دراسية "مصر الجديدة", Maha Abdel Sattar

Emirates Journal for Engineering Research

ملخص

برزت قضايا تجديد البنية الأساسية للتنقل الحضري في محافظة القاهرة كأحد محاور تحقيق استراتيجية التنمية لعام 2030، وهى استراتيجية حملت أهدافا قومية واعدة لتحسين وتقوية البنية الأساسية ورفع مستوى جودة الحياة الحضرية، حيث بدأت الحكومة في تنفيذ خطة تطوير شاملة في حي مصر الجديدة. تهدف إلى حل مشكلة الازدحام المروري وربط المحاور الرئيسية للقاهرة بشكل أفضل بالمدن الجديدة في الشرق. ومن أجل تحقيق هذا الهدف اتخذت الحكومة إجراءات تطوير تركز على توسيع الطرق وتوفير المزيد من المساحة لاستيعاب تدفق المرور وبناء الكباري العلوية.

يهدف هذا البحث إلى استكشاف العلاقة بين السمات والملامح التصميمية لشبكات الطرق في المناطق الحضرية، وبين …

When The Weeds Strike Back: Rethinking Aphis's Regulation Of Genetically Engineered Plants Post-National Family Farm Coalition V. Vilsack, Reagan Powers

Celebrating WCL Student Authors

No abstract provided.

Una Aproximación A La Ia En La Educación Centrada En El Cuidado Para Fomentar La Confianza Y La Motivación Académicas, Izabella Sabharwal De Bessenyey

The International Journal of Ethical Leadership Special Volumes

No abstract provided.

D’Une Approche De L’Ia Éducative Axée Sur La Bienveillance Pour Encourager La Confiance Personnelle Et La Motivation Dans Les Études, Izabella Sabharwal De Bessenyey

The International Journal of Ethical Leadership Special Volumes

No abstract provided.

A Care-Centred Approach To Ai In Education To Cultivate Academic Confidence And Motivation, Izabella Sabharwal De Bessenyey

The International Journal of Ethical Leadership Special Volumes

No abstract provided.

Mitigating Renewal Risk In Banks: An Analysis Of Ai Adoption, Customer Loyalty And Macroeconomic Conditions, Mackenzie M. Cauthorn

ASPIRE 2026

Renewal risk, the uncertainty surrounding whether customers will continue existing financial relationships such as loans, deposits, credit lines, or insurance products, poses a growing challenge for modern banks because customer retention is critical for revenue stability, cross-selling opportunities, and long-term profitability. This study examines how the adoption of artificial intelligence (AI) in banking interacts with macroeconomic conditions to influence renewal risk and customer attrition. Specifically, the research addresses three primary questions: (1) whether macroeconomic conditions, such as perceived economic health, inflation concerns, unemployment expectations, and personal financial confidence, affect the likelihood and timing of banking product renewal; (2) how AI …

Casa Milá As A Sensory Laboratory A Neuroarchitectural Approach To Gaudí'S Modernism, María Beltrán Rodríguez, Chloe Sharpe, Alejandro Martínez González, Ivette Caldelas

Artículos científicos

This paper examines Antoni Gaudí’s Casa Milà (La Pedrera) through the lens of neuroarchitecture, exploring how form, light, and texture shape perception and emotional response. Integrating architectural analysis with neuroscience, it proposes an experimental framework combining EEG, eye-tracking, and behavioral data to assess spatial experience within immersive environments. By linking formal complexity to cognitive and physiological responses, the study reveals how Gaudí’s architecture transcends aesthetics to engage the brain’s sensory and emotional systems. The approach positions his work as a bridge between art, science, and urban creativity, expanding our understanding of architecture as a multisensory cognitive phenomenon.

Copley Connects | Fall 2025/Spring 2026, University Of San Diego

Copley Connects Library Newsletter

Message From the Dean | 3
Writing in Visual Form: noé olivas’ Neon Art Installation | 4
San Diego’s French Connection | 6
Instagrammable Moments: A Librarian’s Reflections on San Diego and USD | 8
Copley Celebrates the 3rd Annual Filipino American History Month Event | 10
Banned Books Week | 10
Copley Library Hosts the Inaugural Student Success Symposium | 11
Veterans/Armistice Day: Veterans for Peace Visit Copley Library | 11
UDEM and USD Sign Sister Libraries MOU | 12
Cruising Through History: The Lowrider Stamp Unveiling | 13
Copley Reads | 14
Cultural Mosaic: Celebrating Asian American and …

Scdi X Mass Timber: Design Optimization, Emily Leane, Ifran Mohamed, Jacey Niiya, Gabriela Valle

Civil, Environmental and Sustainable Engineering Senior Theses

The Civil Engineering industry is a major contributor to global carbon emissions, creating a need for more sustainable structural alternatives to traditional steel and concrete systems. This project investigates the feasibility of redesigning the gravity structural system of Santa Clara University’s Sobrato Campus for Discovery and Innovation (SCDI) using mass timber. By replacing the original steel and concrete gravity system with cross-laminated timber (CLT) floor panels and glue-laminated timber (glulam) beams and columns, the study explores how mass timber can impact structural design, constructability, cost, schedule, geotechnical demand, and sustainability. The redesign maintains the original structural grid and loading assumptions …

Logistics Center: Sustainable Design Build, Dylon Moala, Daryn Nguyen, Andrew Sabuda, Gage Urbach, Nicolae Vesca

Civil, Environmental and Sustainable Engineering Senior Theses

The Cal Centre Distribution Center is a proposed 4,000,000 square foot, four (4) warehouses total, e-commerce warehouse and logistics facility located along Interstate 5 (the I-5) in Kern County, California. The site occupies a very strategic location for overall distribution logistics of the Western United States being close to the Port of Los Angeles allowing for 65,000,000 people to be reached within a two (2) day truck turn. The site also addresses the local economic needs of Kern County and the greater Bakersfield area. Ranking as one of the highest functional unemployment rates among cities, this site will provide approximately …

Where Did It Go Wrong? Attributing Undesirable Llm Behaviors Via Representation Gradient Tracing, Zhe Li, Wei Zhao, Yige Li, Jun Sun

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their deployment is frequently undermined by undesirable behaviors such as generating harmful content, factual inaccuracies, and societal biases. Diagnosing the root causes of these failures poses a critical challenge for AI safety. Existing attribution methods, particularly those based on parameter gradients, often fall short due to prohibitive noisy signals and computational complexity. In this work, we introduce a novel and efficient framework that diagnoses a range of undesirable LLM behaviors by analyzing representation and its gradients, which operates directly in the model's activation space to provide a semantically meaningful signal linking …

Llmqua: Practical Backdoor Injection On Large Language Model Quantization, Xiangxiang Chen, Peixin Zhang, Jun Sun, Jin Song Dong, Wenhai Wang, Jingyi Wang

Research Collection School Of Computing and Information Systems

Quantization is widely used to enable local deployment of large language models (LLMs) on resource-constrained devices. Recent work (e.g., QuRA) shows quantization can be exploited via rounding manipulation to implant backdoors. However, such an attack has been evaluated only on small models and does not directly apply to LLMs due to three key constraints: (1) limited poisoning data from small, task-agnostic calibration sets; (2) layer-wise quantization restricting adversarial access to global representations; and (3) lack of gradient access in quantization pipelines, blocking gradient-based attacks.We propose LLMQuA, a practical quantization-phase backdoor attack tailored to the LLM setting. LLMQuA (i) injects backdoors …

The Canon, Spring 2026, Dordt University

Dordt Canon

• Stream of Consciousness by Gabriella Micheel
• I saw a whale in the sky by Hannah Mulder
• A woman like the one who raised me by Grace Bruin
• Summer on the Farm by Sophie Memmelaar
• Gift by Malachi Myers
• Let The Mountains Rejoice by Mackenzie Gossman
• Sewn From Scrap by Sophie Memmelaar
• Coffee with the Grim Reaper by Gabriella Micheel
• What I Never Really Got to Say by Malahi Myers
• Fluttering Light by Bria Alpaugh
• Mabel by Amalia Visser
• Master and Apprentice by Billy Varble
• King Hero by Emma Anderson
• Champ by Tim DeVries
• Afraid of the Dark by Grace Bruin …

Neuroplasticity And Motor Recovery After Stroke: How Timing, Dosage, And Behavioral Practice Shape Rehabilitation Outcomes, Seth Taukolo

Mentorship Program 2025-2026

No abstract provided.

Entomo-Composting Of Plantain Stems Using Black Soldier Fly Larvae, Kl Njoku, Cj Okonkwo, Cd Okoye

Journal of King Abdulaziz University: Meteorology, Environment and Arid Land Agriculture

Food safety and security are major global concerns. Given the growing global population and limited available resources, a sustainable and stable food supply is essential. An environmentally friendly soil amendment (compost) is required to improve soil fertility and food security. This study investigated the use compost of Black Soldier fly larvae as natural substitutes for artificial fertilizers. The research was conducted by feeding different proportions of Black Soldier Fly larvae either plantain stem or a mixture of plantain stem and with plantain stem and plantain stem mixed with cow dung for 21 days. The amount of nutrients in the compost …