Physical Sciences and Mathematics Commons^™

Time Series Deep Learning Approach For The Intermittent Operational Performance Of A Wellhead Water Treatment And Desalination System, Michael G. Clement

Electronic Theses, Projects, and Dissertations

Distributed water treatment and desalination (DWTD) systems are becoming significant for serving disadvantaged communities that are geographically segregated from centralized water distribution networks. However, given the remote nature of the communities, these systems must operate autonomously adapting to intermittent operations due to varying water use patterns and unavailability of continuous manual labor support. Machine Learning models describing and forecasting system performance are critical, allowing for model-based control, performance forecasting, fault detection, and determination of causal relationships among process attributes. Accordingly, graph convolutional neural networks with an attention mechanism (GATConv) were developed to describe the intermittent operational profiles of a wellhead …

Modeling Language And Vision At Human Scales, Clayton Fields

Boise State University Theses and Dissertations

The impressive results that have recently been achieved in natural language processing and artificial intelligence have been primarily driven by the introduction of the transformer deep learning architecture, increasingly large models with many parameters and using enormous datasets. The size of models and their training data requirements present costly demands that freeze many researchers out of training with cutting edge models. Beyond these practical implications, current methods learn from text alone, without the rich array of sensory information that human beings use in learning language. This means that language models are often incapable of reasoning about the concrete world that …

The Efficacy Of Incorporating Artificial Intelligence (Ai) Chatbots In Brief Gratitude And Self-Affirmation Interventions: Evidence From Two Exploratory Experiments, Jing Wen Hung, Andree Hartanto, Adalia Y.H. Goh, Zoey K.Y. Eun, K. T. A. Sandeeshwara Kasturiratna, Zhi Xuan Lee, Nadyanna M. Majeed

Research Collection School of Social Sciences

Numerous studies have demonstrated that positive psychology interventions, including brief interventions, can significantly improve well-being outcomes. These findings are particularly important given that many of these interventions are brief and self-administered, making them both accessible and scalable for large populations. However, the efficacy of positive psychology interventions is often constrained by small effect sizes. In light of advancements in generative Artificial Intelligence (AI), this study explored whether integrating AI chatbots into positive psychology interventions could enhance their efficacy compared to traditional self-administered approaches. Study 1 examined the efficacy of a gratitude intervention delivered through Snapchat's My AI, while Study 2 …

Autonomous Intelligence In Fashion: A Comprehensive Analysis Of Agentic Ai Across The Fashion Ecosystem, Andrew Burnstine

Faculty and Staff Publications & Presentations

The fashion industry is undergoing a paradigm shift with the emergence of agentic artificial intelligence (AI), a sophisticated class of intelligent systems exhibiting autonomous decision-making, continuous learning, and adaptive action with minimal human intervention. Moving beyond traditional AI applications in fashion focused on predictive analytics, generative tools, and supervised automation, agentic AI introduces a transformative paradigm wherein intelligent agents proactively navigate the complexities inherent in design, manufacturing, supply chain optimization, and consumer personalization. This paper presents a comprehensive exploration of the evolving role of agentic AI across the multifaceted fashion ecosystem, offering an in-depth analysis of its technological underpinnings, operational …

Using Generative Artificial Intelligence To Improve Software-Defined Network Security: A Brief Survey, Anthony Smith

Honors Theses

This paper aims to explore various approaches to using generative artificial intelligence (GenAI) to improve network security in software-defined networking. While software-defined networks provide a more programmable infrastructure, they are not immune to network security threats. Through a combination of Software-Defined Networking (SDN) technologies and generative AI, it is possible to facilitate improved SDN security approaches that promise enhanced network efficiency and protection. Among these approaches, generative adversarial networks (GAN) based models can be employed to generate adversarial traffic samples to train the proposed AI engines proven to be effective in detecting malicious network traffic. Additionally, generative artificial intelligence can …

Integrating Ai-Driven Neurofeedback With Brain-Computer Interfaces: A Paradigm For Effortless Learning And Workforce Transformation, James Hutson

Faculty Scholarship

This editorial discusses the merging of AI-driven neurofeedback with brain-computer interfaces (BCIs) to create a new model for effortless, unconscious learning. By interpreting and reinforcing specific neural patterns, these technologies can enable users to acquire skills without traditional instruction, making them especially valuable in fast-evolving industries. They also offer powerful tools for individuals with physical impairments by enabling control through thought alone. However, the author emphasizes the importance of ethical oversight, particularly around cognitive autonomy, data privacy, and consent. As the field matures, ongoing research and regulation will be essential to ensure responsible development and widespread, beneficial use.

The Fear Of Replacement: How Ai Panic In Journalism Mirrors Existential Crisis In Industry, James Hutson

Faculty Scholarship

This study systematically examines the portrayal of artificial intelligence (AI) errors, such as hallucinations and deepfakes, in journalistic contexts, evaluating whether these narratives reflect a broader existential anxiety about AI's role in reshaping journalism. Using a systematic literature review combined with a qualitative content analysis of recent AI-focused news reports, this study identifies recurring themes in media coverage to assess the accuracy and context of reported AI errors relative to actual technological limitations and affordances. Findings suggest that while AI errors are comparatively rare, they receive amplified coverage, often fueling public mistrust in AI technologies. Nevertheless, a balanced examination reveals …

Dictating The Divine: Revisiting Authorship, Intention, And Authority From Sacred Texts To Generative Ai, James Hutson, W. Travis Mcmaken

Faculty Scholarship

This article interrogates the historical practice of mediated authorship in religious texts to draw critical parallels with contemporary debates surrounding generative artificial intelligence (AI), specifically large language models (LLMs). By juxtaposing the mediated authorship of sacred texts, such as the Hebrew Bible and New Testament—where figures like the Apostle Paul dictated theological concepts to scribes who infused these directives with their interpretive insights—with the generative processes of LLMs, this research underscores the shared dynamics of co-constructed authorship across historical and technological contexts. Employing interdisciplinary methodologies from art history, textual studies, and reception theory, as well as theological and biblical studies, …

Ai Foundations And Applications: Summary Of A Panel Discussion At Loyola University Chicago, George K. Thiruvathukal, Dmitry Dligach, Shilpika, Michael B. Burns, Joseph Vukov, Fraser Turner, Mary Usher

Computer Science: Faculty Publications and Other Works

This document summarizes the panel discussion titled "AI Foundations and Applications," held at Loyola University Chicago as part of the "Forum on Global Affairs: Artificial Intelligence in a Globalized World" series. The panel brought together interdisciplinary experts to discuss the foundational aspects of artificial intelligence (AI), its applications, ethical considerations, and implications for education and society.

Reframing Information Seeking In The Age Of Generative Ai: A Critical And Humanistic Approach, Joseph Kevin Sebastian

Library Faculty Research

Information-seeking has long been the subject of theoretical modeling, often drawing from cognitive, behavioral, computational, and even evolutionary perspectives to explain how individuals navigate, filter, and utilize information. Several dominant frameworks—Carol Kuhlthau’s Information Search Process, Marcia Bates’ Berrypicking Model, Peter Pirolli & Stuart Card’s Information Foraging Theory, Kiyohiko Nakamura’s Information Criteria framework, and Ian Ruthven’s Information Shaping Theory —have provided structured ways of understanding how people interact with information environments. However, while these frameworks offer valuable insights, they often operate within mechanistic or efficiency-driven paradigms, which risk overlooking the complex, embodied, and socioculturally situated nature of human information behaviors. These …

Grounding Ai Use In Learning Science: A Conversation With Steven Miller, Steven Miller, Lieven Demeester

CASTLe: Collection of Articles on Scholarship for Teaching and Learning

In this insightful interview, SMU Associate Provost (Teaching and Learning Innovation) Lieven Demeester and Professor Emeritus of Information Systems Steven Miller discuss the integration of artificial intelligence (AI) in teaching and learning, emphasising the importance of grounding AI use in the fundamentals of learning science. They explore the evolving role of education in the context of AI advancements, highlighting the need for educators to focus on the cognitive aspects of learning, such as goal-directed practice and feedback. They also address the potential of AI as a collaborative agent in group projects and the importance of maintaining accountability and quality control …

Ethical Work Cultures & Ai, Andrew Brei

Presentations - 2025

With the help of moral theories, several case studies, and insights from the world of behavioral ethics, my project aims to provide engineering professionals with the means to deal properly with moral issues that commonly arise in their chosen fields.

Development And Evaluation Of The Da Vinci Ai Tutor: Enhancing Accessibility And Personalized Learning In Art History Education, James Hutson, Tiffani Barner

Faculty Scholarship

This study examines the implementation of the Da Vinci AI Tutor, an innovative artificial intelligence (AI)-based tutoring platform designed specifically for enhancing personalized and accessible learning in art history within higher education. Launched in Fall 2024 at a private liberal arts institution in the Midwest, the system integrates a conversational AI avatar modeled after Leonardo da Vinci, incorporating immersive virtual reality environments and multimodal interaction capabilities to engage students across undergraduate survey courses, advanced Renaissance classes, and graduate comprehensive exam preparations. Addressing significant gaps in existing humanities education research, the current study explores two primary research questions: (i) How AI-driven …

Enhancing Metacognitive Competencies Through Human-Centered Ai: The Role Of Custom-Trained Intelligent Agents In Workforce Upskilling, James Hutson

Faculty Scholarship

This editorial examines the integration of human-computer intelligent interaction (HCII), specifically through human-centered artificial intelligence (AI) and custom-trained intelligent agents, to foster metacognitive competencies critical for workforce upskilling. With 59% of the workforce projected to require substantial upskilling by 2030, developing personalized AI models tailored to individual cognitive and learning profiles presents an innovative pathway. These custom-trained agents leverage human-computer interaction (HCI) technologies and machine learning methodologies to enhance understanding of one’s own learning processes-metacognition-thus empowering individuals to optimize their future learning and adaptability. This approach not only enhances the individual’s ability to engage effectively with complex tasks in the …

Research On Quantitative Evaluation Of Artificial Intelligence Policy Texts In The Yangtze River Delta Region, Ying Zhou, Danjie Yang, Mei Jiang, Xiaochun Zhao

Journal of Scientific Information Research

[Purpose/significance]The quantitative evaluation of existing effective artificial intelligence (AI) policies aims to provide reference for government department to formulate scientific and reasonable AI policies and promote the development of AI. [Method/process]Taking 10 AI policies in the Yangtze River Delta region from 2015 to 2024 as the research samples, the text mining method is used to construct the evaluation index system of AI policies in the Yangtze River Delta region, and conduct quantitative evaluation by combining the PMC index model. [Result/conclusion]The study found that from a macro policy text perspective, the average PMC index of the 10 AI policy samples in …

News From The Front: How To Win The Ai War, Christine Haverington

Journal of the National Collegiate Honors Council Online Archive

While artificial intelligence is currently and justifiably a hot topic among scholars and university administrators, students are way ahead of the curve in terms of its use and application. Calling for educators to stop trying to catch AI “cheaters,” this essay provides evidence from honors and other classroom observations, student research on peer and faculty usage and attitudes, course evaluations, and external sources to demonstrate how and why generative AI can be creatively and effectively incorporated into teaching. Toward this end, practical pedagogical strategies are shared describing teaching modalities and innovative curricular design, avoiding the cognitive degradation of students, and …

The Role Of Artificial Intelligence In Workforce Learning And Development: A Systematic Review, Mildred V. Jones

Educational Leadership & Workforce Development Theses & Dissertations

The purpose of this study is to investigate how artificial intelligence (AI) is currently employed in workforce learning and development. The study examined the types of AI employed and the affordances realized for organizations and employees. A PRISMA systematic review methodology was utilized to address the overarching problem statement and answer the three questions guiding the study. The PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta Analysis for Protocols was used to direct each phase of the research. In addition, the Preferred Reporting Items for Systematic Reviews and Meta Analysis was used to conduct the article selection process. …

Predictive Modelling For Vessel Traffic Flow: A Comprehensive Survey From Statistics To Ai, Deshan. Chen, Chen. Huang, Tengze. Fan, Hoong Chuin Lau, Xinping. Yan

Research Collection School Of Computing and Information Systems

Recognizing the specific complexities of vessel traffic flow, this comprehensive survey exclusively addresses the predictive modelling in maritime transportation, tracing the evolution from conventional statistical approaches to modern artificial intelligence (AI) techniques. The survey examines a broad range of predictive targets, including vessel volume, trajectories, velocities, destinations and traffic patterns. Through bibliometric analysis utilizing Citespace, the central research themes and technological trends characterizing the vessel traffic flow prediction domain have been identified and discussed. Our analysis indicates a clear trend towards AI-based models, highlighting their increasing dominance in enhancing predictive accuracy and efficiency. Additionally, we highlight persistent challenges, such as …

Framework For Integrating Industry Knowledge Into A Large Language Model To Assist Construction Cost Estimation, Prashnna Ghimire

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The construction industry generates a large amount of data across projects produced by digital devices, tools, and methods, and this volume is rapidly increasing. However, the industry lags behind in adopting data-driven technologies. On the other hand, the rapid advancement of generative AI (GenAI) in recent years, especially state-of-the-art large language models (LLMs), shows great potential and has been increasingly adopted in many industries; however, the construction industry is behind in adoption. While academic studies have proposed various machine learning applications for construction, industry implementation has lagged due to a disconnect between these proof-of-concept developments and practical industry needs. Also, …

Experimenting With Machine Learning Using Diabetes Datasets, Wyatt Mcdonnell, Hongbiao Zeng

SACAD: Scholarly Activities

The purpose of this research is to understand how to implement machine learning in a practical scenario. There were two diabetes datasets[5][6] used for testing the machine learning models. These datasets contain information relevant to a person’s health, as well as whether that subject had diabetes. I used a total of four models, and three of those models were manually programmed. The model which was not manually programmed was used for comparison with a similar model. This research directly compares and shows the factors which affect the efficiency of each machine learning model.

Evaluating A Large Language Model’S Accuracy In Chest X-Ray Interpretation For Acute Thoracic Conditions, Adam M. Ostrovsky

SKMC Student Presentations and Publications

BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing acute thoracic conditions in the emergency department (ED), but interpretation delays due to radiologist availability can impact clinical decision-making. AI models, including deep learning algorithms, have been explored for diagnostic support, but the potential of large language models (LLMs) in emergency radiology remains largely unexamined.

METHODS: This study assessed ChatGPT's feasibility in interpreting chest X-rays for acute thoracic conditions commonly encountered in the ED. A subset of 1400 images from the NIH Chest X-ray dataset was analyzed, representing seven pathology …

International Expert Consensus On The Current Status And Future Prospects Of Artificial Intelligence In Metabolic And Bariatric Surgery, Mohammad Kermansaravi, Sonja Chiappetta, Shahab Shahabi Shahmiri, Julian Varas, Chetan Parmar, Yung Lee, Jerry T. Dang, Asim Shabbir, Daniel Hashimoto, Amir Hossein Davarpanah Jazi, Ozanan R. Meireles, Edo Aarts, Hazem Almomani, Aayad Alqahtani, Ali Aminian, Estuardo Behrens, Dieter Birk, Felipe J. Cantu, Ricardo V. Cohen, Maurizio De Luca, Nicola Di Lorenzo, Bruno Dillemans, Mohamad Hayssam Elfawal, Daniel Moritz Felsenreich, Michel Gagner, Hector Gabriel Galvan, Carlos Galvani, Khaled Gawdat, Omar M. Ghanem, Et Al

School of Medicine Faculty Publications

Artificial intelligence (AI) is transforming the landscape of medicine, including surgical science and practice. The evolution of AI from rule-based systems to advanced machine learning and deep learning algorithms has opened new avenues for its application in metabolic and bariatric surgery (MBS). AI has the potential to enhance various aspects of MBS, including education and training, decision-making, procedure planning, cost and time efficiency, optimization of surgical techniques, outcome and complication prediction, patient education, and access to care. However, concerns persist regarding the reliability of AI-generated decisions and associated ethical considerations. This study aims to establish a consensus on the role …

Artificial Intelligence And Communication Technologies In Academia: Faculty Perceptions And The Adoption Of Generative Ai, Aya Shata, Kendall Hartley

Hank Greenspun School of Journalism and Media Studies Faculty Research

Artificial intelligence (AI) is ushering in an era of potential transformation in various fields, especially in educational communication technologies, with tools like ChatGPT and other generative AI (GenAI) applications. This rapid proliferation and adoption of GenAI tools have sparked significant interest and concern among college professors, who are dealing with evolving dynamics in digital communication within the class-room. Yet, the effect and implications of GenAI in education remain understudied. Therefore, this study employs the Technology Acceptance Model (TAM) and the Social Cognitive Theory (SCT) as theoretical frameworks to explore higher education faculty’s perceptions, attitudes, usage, and motivations, as the underlying …

A Student Guide To Using Ai To Enhance Algebraic Understanding, Karan Puri

Open Educational Resources

This is a step-by-step guide that students can follow to use AI tools to check their understanding of concepts that have been tested in the introductory/college algebra classroom.

The Future Of Ai: Join The Conversation, Jennifer Wojton, Cassandra Branham, Vijay Tummala, Laxima Niure Kandel, Kayla D. Taylor

Publications

Join the Conversation! The Future is AI? There is so much conflicting information about what AI is capable of, how it could/should be used, by whom and for what purpose. In this panel discussion, we hope to provide a baseline of information that will help all participants think critically and articulate thoughtful questions about the mechanics of AI, ethical use or non-use of AI in particular contexts (school, industry, business, art, etc.), and the impacts we are currently experiencing or are likely to experience. Hear from ERAU faculty of different disciplines to discuss what the current state of AI technology …

The Role Of Artificial Intelligence In Transforming Physical And Online Fashion Retail: Enhancing Experiences, Driving Sustainability, And Fostering Innovation, Andrew Burnstine

Faculty and Staff Publications & Presentations

This study explores the transformative role of artificial intelligence (AI) in revolutionizing the fashion industry, with a focus on enhancing consumer experiences, promoting sustainability, and driving innovation in retail. It examines AI applications in personalized recommendations, virtual try-ons, and supply chain optimization, while also addressing societal implications. Sustainability is a central theme, highlighting how AI minimizes overproduction, enables circular fashion, and encourages conscious consumerism. Case studies, such as Nike’s AI-powered retail stores and Lynn University’s Surreal Fashion Show, demonstrate practical applications and innovations during the COVID-19 pandemic. This research synthesizes insights from reports by The Business of Fashion and McKinsey …

If You Were A Sesame Street Character, Which One Would You Be? Natural Language Processing And Personality With Big Bird And Friends, Joseph Uran Meyer

Doctoral Dissertations

This paper examined and compared several natural language processing and machine learning techniques in predicting self-reported Big Five personality traits from text responses. The models were validated on the open-source 2019 SIOP Machine Learning Competition dataset (N = 1,689). The techniques evaluated included bag-of-words, Empath dictionary, LSTM networks, fine-tuning Transformer models, and stacked generalization. Results indicated that the present study’s models had lower error in four of the five constructs analyzed. Limitations of the study include use of an MTurk sample and small sample size. Future research should explore similar techniques on larger applicant samples. Practical implications and contributions to …

Why Ai’S Role In Advancing Sustainability Is Underestimated, Lipika Bhattacharya

CCX Research

AI has quietly, but powerfully, woven itself into the fabric of our everyday lives. Yet, AI's potential impact on creating a more sustainable world is undervalued. The author examined artificial intelligence's (AI) role in advancing sustainability. She outlined how AI can be applied in various domains such as agriculture, water management, industry, urban planning, and biodiversity conservation for transformative effects.

Learning: Human Versus Machine, Sanjay Sarma

Asian Management Insights

Outdated education paradigms must be revamped to reclaim the all-important human quality: agency.

Sanjay Sarma, CEO, President, and Dean of the Asia School of Business, Kuala Lumpur, Malaysia and the Fred Fort Flowers (1941) and Daniel Fort Flowers (1941) Professor in Mechanical Engineering at the Massachusetts Institute of Technology (MIT), shares insights on the artificial intelligence (AI)-agency revolution and how the human brain works.

The Ethics Of Ai Nudges: How Ai Influences Decision-Making, Seema Chokshi

Asian Management Insights

And why decision-makers should care about it. Artificial intelligence (AI) systems, through mechanisms like nudges and choice architecture, actively, yet often subtly, shape human decision-making in everyday life and professional settings. AI systems can prioritise profit or efficiency at the expense of human agency, fairness, and well-being, highlighting the need to balance AI’s capabilities with ethical considerations. The EU AI Act is a landmark framework designed to curb manipulative AI practices, emphasising the protection of human autonomy and accountability in decision-making.