Digital Commons Network^™

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …

Long-Term Mine Planning: A Survey Of Classical, Hybrid And Artificial Intelligence-Based Methods, Nurul Asyikeen Azhar, Aldy Gunawan, Shih-Fen Cheng, Erwin Leonardi

Research Collection School Of Computing and Information Systems

The aim of long-term mine planning (LTMP) is two-fold: to maximize the net present value of profits (NPV) and determine how ores are sequentially processed over the lifetime. This scheduling task is computationally complex as it is rife with variables, constraints, periods, uncertainties, and unique operations. In this paper, we present trends in the literature in the recent decade. One trend is the shift from deterministic toward stochastic problems as they reflect real-world complexities. A complexity of growing concern is also in sustainable mine planning. Another trend is the shift from traditional operational research solutions — relying on exact or …

The Lorekeeper’S Trial: Teaching Ai Literacy Through Active Learning In The Library Classroom, Taylor Greene, Douglas R. Dechow

Library Articles and Research

How can librarians engage students in critical, hands-on learning about artificial intelligence within the limitations of a one-shot session? At Chapman University, librarians have developed an AI literacy session that integrates ethics and hands-on exploration into workshops and course-embedded sessions. This presentation highlights how to weave AI literacy into information literacy instruction, with a focus on a First-Year Foundations program.

Presenters will discuss their efforts to reach students, staff, and faculty through AI literacy initiatives across campus. They will also demonstrate how the Lorekeeper’s Trial—a research quest inspired by RPGs—transforms AI and information literacy concepts into collaborative challenges. Through a …

Does Patient History Influence Capsular Contracture? An Exploratory Analysis With Machine Learning, Thomas M. Johnstone, Daniel Najafali, Jennifer K. Shaw, Justin M. Camacho, Chancellor Johnstone, Rahim S. Nazerali, Gordon K. Lee

Faculty Publications

Background: Capsular contracture (CC) is a frequent and distressing complication of breast augmentation and reconstruction. Although numerous patient-, surgical-, and implant-related risk factors have been proposed, reliable population-level predictors remain inconsistent across studies. This study evaluates whether administrative medical history, as encoded by ICD and CPT codes, contains sufficient predictive signal to identify patients at risk for CC using machine learning. Methods: Patients were queried from the MerativeTM MarketScan® Research Databases from 2003 to 2017 with CPT codes for implant-based breast reconstruction and augmentation. ICD codes were then used to identify all events and conditions of a patient’s history. Hyperparameter-tuned …

Making Ai An Intelligent Tool For Our Schools: Using The Perceptions Of Administrators And Teachers In A Midwestern School District To Help Shape Our Educator Preparation Program, John A. Huss

i.e.: inquiry in education

This qualitative practitioner research study explored the attitudes and perceptions of administrators and teachers in a high-performing Midwestern school district regarding the integration of artificial intelligence (AI) in K-12 education. While AI has rapidly emerged as a transformative force in society, its implementation in schools remains inconsistent, with limited policies, training, and usage. Semi-structured interviews with nine educators (three principals and six experienced teachers) revealed widespread interest in AI, but also significant uncertainty and uneven adoption. Educators reported using AI for administrative and instructional tasks, such as grading and resource generation, yet expressed concern over student overreliance and diminished critical …

Frictional Intelligence, Posheng Cheng

Masters Theses

This is an experimental interaction design project that challenges anthropomorphism in human-computer interaction. In particular, the recent advancement of artificial intelligence technologies like Large Language Models has taken anthropomorphism to new heights. The conversational chatbot interface of AI prioritizes mimicking an inherently human communication medium to maximize human-likeness. However, anthropomorphism has several downsides. Conversational interfaces obscure the limitations and the tangible cost of the technology. They also imply fictional moral status and human-level cognitive capabilities, which means general public sentiment focuses on the ``overhyped'' excitement and fear rather than on other socio-ethical and capacity questions that are far more urgent …

Mapping Homogeneous Configuration States For Learning Based Motion Planners, Yazied Hasan

Computer Science ETDs

Reinforcement learning (RL) excels at solving complex tasks, but training times can become prohibitively large for challenging motion-planning problems. Methods that address this cost often require additional training or tuning, counteracting the goal of reducing training time. A more effective approach is to exploit inherent task equivalences: many elements of the state space, dynamics, or structure are functionally interchangeable, enabling simplification or knowledge reuse. We present learning solutions that leverage these equivalences to enhance the RL process. First, we leverage the symmetry of homogeneous multi-agent teams to simplify the task to a single strategy. Second, we map correspondences between distinct …

Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy

Turkish Journal of Electrical Engineering and Computer Sciences

This research proposes an end-to-end procedure for arrhythmia detection based on electrocardiogram (ECG) signals using complex-valued convolutional neural network (CVCNN) incorporated with time-frequency representation. The proposed model leverages complex numbers to capture amplitude and phase information that enhances the ability of the model for detecting time-frequency variation in cardiac signals. First, signal preprocessing techniques---including normalization, wavelet denoising, and R-peak detection---are applied. Subsequently, the model extracts complex features from raw ECG data by employing the Hilbert transform to derive the analytic signal and the short-time Fourier transform (STFT) to generate a time–frequency representation. The proposed CVCNN framework effectively learns spatial-temporal features …

Welcome Tilly Norwood: Forecasting Hollywood’S Ai Policy Futures, Samuel P. Rooker

Senior Honors Projects, 2020-current

In late 2025, weekly trade publication Variety Magazine reported on the announcement of a new acting talent in Hollywood: Tilly Norwood. Norwood is an industry outsider and the pet project of Eline Van der Velden, who unveiled the actress’ existence to the world at the Zurich Film Festival. The announcement quickly gained media coverage while Van der Velden has since faced cyclical backlash from Hollywood trade unions, which does not seem entirely without reason. Tilly Norwood is a digital persona, a generative artificial intelligence (GenAI) program, designed by Van der Velden’s novel AI talent studio, Xicoia, to become the next …

An Evaluation Of Artificial Intelligence Chatbots As Alternatives To Specialized Software In Teaching Bayesian Pharmacokinetic Analysis, Reza Mehvar

Pharmacy Faculty Articles and Research

Objective

Methods

A Governance-Aware Multi-Agent Framework For Enhancing Fairness & Temporal Accuracy In Disaster Response Systems, Md. Ashfaqur Rahman

Theses and Dissertations

Large Language Models (LLMs) have demonstrated significant potential in disaster-response decision support, however, their deployment in high-stakes humanitarian settings raises critical concerns regarding factual reliability, fairness, temporal validity, and governance compliance. Hallucinated outputs, demographic bias, and outdated recommendations can directly impact vulnerable populations and undermine public trust. This dissertation proposes a governance-aware multi-agent framework designed to enhance fairness and temporal accuracy in disaster-response systems through structured Retrieval-Augmented Generation (RAG), verification-driven orchestration, and adaptive correction mechanisms.The proposed architecture decomposes response generation into specialized agents responsible for real-time retrieval, fact-checking, bias auditing, temporal validation, threshold-based correction, and monitoring. By embedding governance constraints …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …

Muth's Law: Anticipating Ai Model Collapse, Karl T. Muth

The University of Cincinnati Intellectual Property and Computer Law Journal

No abstract provided.

Leveraging Artificial Intelligence (Ai) To Strengthen Mtss Within Catholic Schools, Kaitlin D. Reichart, Adam B. Lockwood, Jessica Pizzute (Kukura)

Education: School of Education Faculty Publications and Other Works

Many Catholic schools face resource challenges that result in limitations surrounding the implementation of multi-tiered systems and support (MTSS). Artificial intelligence (AI) offers a potential tool for Catholic schools to strengthen systems of support. This article provides a conceptual analysis regarding opportunities for AI to strengthen core components of MTSS, such as identifying evidence-based interventions, developing progress monitoring tools, analyzing student data, and facilitating personalized instruction. The article also discusses the challenges and limitations of leveraging AI within Catholic schools, specifically when supporting staff and students. Although the article is focused on US contexts, there are conceptual implications that may …

Ai And The Ethos Of Education: Reflections On Human Learning Past And Present, Melanie Trotochaud

Yale Divinity School Theses

This thesis reflects on contemporary issues of “Artificial Intelligence” (AI), while also bringing into conversation 12th century Christian mystic and polymath Hildegard Von Bingen and 18th century Humanist philosopher Giambattista Vico. Hildegard’s and Vico’s contexts philosophically and historically share similarities to our present moment: reassessing our humanity and learning in times of technological, economic, and social shifts. Holding up their writing to various conversations about our contemporary world helps illuminate the present. Key aspects of the discussion include what constitutes tools or technologies, the agency we have in choosing to use or not to use them, and how we make …

Digital Grief Technology To Support Bereavement: A Systematic Review Of Potential Benefits And Risks, Xun Ci Soh, Adalia Yin Hui Goh, Paye Shin Koh, Andree Hartanto

Research Collection School of Social Sciences

Grief is a universal and inevitable experience. However, the way we support the bereaved is changing, especially in the digital era. This systematic review examines the potential benefits and risks associated with various digital grief technologies, including online grief support groups, generative AI chatbots, online memorials, online therapy interventions, virtual reality, and digitally reproduced visuals or audio of the deceased. A systematic search was conducted in seven databases, and 30 articles were included in the final review. Findings indicate that digital grief technologies offer several benefits, such as reductions in grief and depressive symptoms, enhanced social support, greater accessibility, and …

You Are Me, And I Am You: Bias, Ai, And The Academic Self, Frances E. Anderson

Journal of Educational Leadership in Action

Being black, brown, caramel, immigrant, French speaking, divorced, mother of six, economically disadvantaged, neurodivergent, foster care graduate, survivor of abuse, child of divorce, and health-impacted person, I’ve often examined the wheel of power and privilege with sadness and dismay. In contrast, being white, catholic, intellectually advantaged, athletic, American, Canadian, middle-class, mathematics mastermind, and Doctor of Education, I’ve needed to examine this wheel fiercely as I come face-to-face with my privilege. Through reflection and self-interrogation, I carefully and imperfectly consider how my bias informs me of my disposition towards others, my educational privileges, and my experience in the world of academia. …

Ai-Assisted Case Conceptualization: Enhancing Ethical Decision-Making In Graduate Counseling Education, Thang S. Tran, Praveen K. Rudra, Justin Jacques

Journal of Educational Leadership in Action

As artificial intelligence (AI) is increasingly integrated into counselor education, a significant gap exists between the rapid adoption of technology and the development of structured pedagogical frameworks for ethical decision-making. This article introduces a multi-component framework to support ethical AI integration in graduate counseling education, comprising three key elements: (1) a case conceptualization model with AI assistance, (2) Morgan (SC), an intentionally imperfect AI school counseling thought partner trained on ethical standards and decision-making models, and (3) structured protocols for ethical decision-making aligned with American Counseling Association and National Board for Certified Counselors guidance. The framework is designed to center …

Assessing The Effectiveness Of Ai-Based Adaptive Learning Systems In Higher Education, Ibrahim Olasunkanmi Yusuf, Suleiman Yusuf

Journal of Educational Leadership in Action

The integration of artificial intelligence (AI) in education is transforming teaching and learning by enhancing outcomes and personalizing learning experiences. This study investigates the effectiveness of AI-based adaptive learning systems in higher education using a quantitative research design involving 500 students from five institutions. The primary goal is to assess the impact of these systems on academic performance, student engagement, and retention rates. Data were collected through surveys and academic records, comparing students using adaptive learning systems to those in traditional classroom environments. Academic performance of students utilizing AI systems demonstrated significant improvement in grades compared to peers in conventional …

Integrating Ai Into Collection Development Workflows: Prompts, Rubrics, And Responsible Use, Ivan Portillo, David Carson, Margaret Puentes

Library Presentations, Posters, and Audiovisual Materials

AI technologies are advancing at a rapid pace and offer new opportunities for library advancement. This session highlights practical ways AI can support collection development and discusses opportunities to improve library workflows.  Attendees will also learn how AI can strengthen library resource management by optimizing decision making and use of resources.

Learning Outcomes: 

• Attendees will learn about approaches to integrating artificial intelligence into collection development
• Attendees will learn about artificial intelligence tools and their applicability to collections 
• Attendees will learn about the ethical use of artificial intelligence tools 

Leading The Choreography: Preserving Creative Agency In Ai-Supported Problem-Solving, Mikhaila Ackerbauer

Creativity and Change Leadership Graduate Student Master's Projects

As artificial intelligence tools become increasingly present in creative and problem-solving contexts, a critical question emerges: how can users engage with AI in ways that preserve rather than erode their own creative capacity? This project explores that question through research synthesis, practitioner conversations, coursework, international conference presentations, and the development of custom AI chatbots trained in the Creative Problem-Solving process. The central finding is a theoretical triangle comprising three interdependent capacities: autonomy, creative self-efficacy, and critical thinking. Grounded in Rhodes' (1961) Four P's framework, the triangle sits within the Person dimension. Convergent themes across the literature, practitioner conversations, and direct …

Non-Destructive Automated Classification Of Human And Large Mammal Long Bone Fragments: A Deep Learning Approach Using Micro-Ct Histomorphology And Grad-Cam Interpretation, Kathleen Marie Kelley

Department of Anthropology: Theses and Student Research

This study explores the development and validation of an automated, deep learning system designed to differentiate human from large mammal long bone fragments using micro-CT imagery. A comprehensive dataset of cross-sectional µCT images was assembled from human and animal skeletal material processed at the DPAA, Nebraska. A convolutional neural network (CNN) based on a ResNet-18 architecture, utilizing transfer learning from ImageNet weights, was trained to classify µCT images as human or animal. The model achieved a mean classification accuracy of 89.85% (± 8.27%) across five sample-level cross-validation folds, with a sensitivity of 96.21% and a 95% bootstrap confidence interval of …

You Can’T Spell Audit Without Ai: The Current Uses Of Artificial Intelligence In Audit, Jena Perkins

Senior Honors Theses

The accounting profession continuously adapts to the innovations provided by the broader context in which it exists. Artificial intelligence (AI) is a forerunner among tools used to enhance and optimize auditing services within the accounting profession. The realm of AI offers advancements to procedures used within an audit to detect misstatements. Based on the proprietary platforms developed by Big 4 accounting firms, AI is a key component in maintaining an advanced approach towards auditing.

Personalized And Adaptive Therapeutic Music Generation From Biosignals Using Knowledge-Guided Multimodal Large Language Models, Amin Amiri

Masters Theses and Doctoral Dissertations

Multimodal generative models are reshaping digital therapeutics by enabling real-time synthesis of personalized content aligned with a user’s physiological and affective state. However, existing systems remain fragmented across modalities and often lack a unified framework that can jointly represent biosignals, natural language intent, music, and video under long-context constraints. This dissertation presents an end-to-end multimodal large language model ecosystem for personalized therapeutic music generation that combines discrete tokenization, evidence-grounded reasoning, and stabilized preference alignment. At the representation layer, the dissertation develops a family of tokenizers that convert continuous biomedical and media signals into compact discrete sequences for transformer-based modeling. Harmonizer …

Artificial Intelligence In Medicine: Barriers, Solutions, And Strategies, Anil Harrison, Melissa Stradley Moreno, Caroline E. Williams, Munevver Mine Subasi, Ersoy Subasi

HCA Healthcare Journal of Medicine

The integration of artificial intelligence (AI) and machine learning (ML) into health care holds the potential to revolutionize patient care by enhancing clinical decision-making, improving diagnostic accuracy, and reducing costs. Despite this promise, adoption remains limited due to a range of technical, regulatory, educational, and cultural barriers. This paper examines these challenges and proposes strategies to support safe and effective implementation of AI in clinical practice.

Key barriers include the lack of model interpretability, often referred to as the "black box" problem, which undermines clinician trust and accountability in clinical settings, evolving regulatory frameworks and unresolved questions surrounding liability, and …

Dementia Detection In Low-Resource Languages: Evaluating Translation-Assisted Transfer Learning For Multilingual Clinical Assessment, Kylar A. Deloach

Honors Theses

Alzheimer's disease (AD) is a growing global health concern, with millions of people affected worldwide and cases expected to rise significantly in the coming decades. Early detection is critical for patient treatment and care, and recent advances in natural language processing (NLP) have shown promise in identifying linguistic markers associated with AD. However, most existing work has focused on English, leaving speakers of other languages with limited access to such tools. This study investigates how effective AD detection models trained on English data are at transferring to Greek, a low-resource language with limited dementia-related speech data available. We propose a …

Comparison Of Chatgpt, Claude Ai, And Dental Students In The Detection Of Artifacts On Panoramic Radiography, Elif Çeçen Erol, Ceren Aktuna Belgin, Gözde Serindere, Kaan Gunduz

Journal of Dentistry Indonesia

Background: Accurate radiographic diagnosis requires images obtained with proper technique. Artifacts are unwanted irregularities or densities not produced by the primary X-ray beam and may obscure anatomical details in radiographic images. This retrospective study aimed to evaluate the performance of ChatGPT, Claude AI, and intern dental students in detecting artifacts in panoramic radiographs (PRs).

Methods: Between January and December 2024, panoramic radiographs of 40 patients containing 74 artifacts (motion, mispositioning, airway/soft tissue, and foreign body/metal artifacts) were retrospectively evaluated. The artifact detection performance of ChatGPT-4.0, Claude AI 3.5 Sonnet, and intern dental students was subsequently evaluated and compared …

Ai-Based Environmental Economic - Modeling: A Case Of Germany (1994–2024), Zahraa Taha Naqee

Journal of Economics and Administrative Sciences

This research aims to analyse the impact of economic and energy variables on carbon emissions in Germany during the period (1994–2024), within the framework of environmental economic modelling based on artificial intelligence techniques. The study is based on the hypothesis that the nature of the energy structure and the level of economic activity contribute to explaining changes in carbon dioxide emissions to varying degrees. To verify this hypothesis, an artificial neural network model was adopted to analyse the relationship between a set of independent variables represented by total energy consumption, total energy production, the proportion of renewable energy in total …

Ai Mistakes: "Confabulation" And Abduction, Not "Hallucination", Stephen M. Mcjohn, Ian Mcjohn

Suffolk University Law School Faculty Works

"Hallucination" has become the common term for errors by AI systems, yet it implies a misleading analogy to human perception. LLM's process tokens. They do not have conscious experience or conscious perception. A hallucination is an experience, and (to our knowledge, to date) LLM's do not experience anything. This paper suggests that legal scholars follow the lead of a small number of AI researchers who have suggested that "confabulation" is a more accurate term, a metaphor grounded in psychology. People confabulate when they unknowingly invent spurious explanations or facts. We then take this terminological question and stretch it into a …

Using Ai To Identify National Security Threats: A Holistic Examination Of The Legal Risks And Increased Need For Regulation, Skylar Mcvicar

Duke Journal of Constitutional Law & Public Policy Sidebar

Artificial intelligence (AI) is integrating rapidly into daily practice, including in the national security sector. AI has the potential to improve bureaucratic efficiency, enhance military intelligence and threat assessment, and develop autonomous vehicles and weapons, making it a revolutionary tool in national security. Since AI implementation is a relatively recent phenomenon, there is currently limited governmental regulation in place to safeguard against potential violations of civil liberties and other legal risks. Given AI's capacity to infringe on certain civil liberties such as the Fourth Amendment right to privacy and the Fourteenth Amendment protection against discriminatory policies, establishing strong oversight measures …