Digital Commons Network^™

Automation And Autonomy In The Ivf Laboratory: Concepts And Implications For Embryologists, Jacques Cohen, Gerardo Mendizabal-Ruiz, Giles Anthony Palmer, Giuseppe Silvestri, Mina Alikani

EVMS School of Health Professions Faculty Publications

Automation is regarded as the next phase in the evolution of laboratory IVF. Despite technological advances, most laboratory procedures remain operator-dependent, contributing to variability in performance and outcomes. While automation has improved reproducibility and efficiency in many areas of medicine, its adoption in IVF has been slow. This review examines how automation may be integrated into IVF laboratories through a set of conceptual distinctions. Automation refers to the execution of procedural steps by machine-controlled systems, whereas autonomy describes the degree to which such systems can operate without human intervention. This review distinguishes between static automation, which maintains or monitors the …

The Ai Revolution In Virtual Try-Ons: A Means-End Chain Model Perspective, Ju-Young M. Kang, Ji Young Lee, Dooyoung Choi, Sumin Helen Koo, Jeehyun Song, Youngjin Bahng

Educational Leadership & Workforce Development Faculty Publications

Leading brands have begun to implement artificial intelligence-driven virtual try-on (AI VTO) technology, which helps reduce returns and increase conversion rates, repeat purchases, and customer loyalty. This research aimed to examine how retail user experience with specific perceived quality factors of AI VTOs influences users’ value equity and downstream loyalty and to investigate the moderating effects of clothing in relation to the self as structure and concern for physical appearance, based on a Means–End Chain model. Data were collected from 509 U.S. online apparel shoppers using a consumer panel. Structural equation modeling and multigroup analysis were used for data analysis. …

Deep Learning-Based Co-Current Upward Gas-Liquid Two-Phase Flow Regime Identification In An Annular Conduit, Joshua Robert Macomber

Graduate Theses, Dissertations, and Problem Reports (ETD)

Flow regime identification in co-current upward gas-liquid flow through annular conduits remains a significant challenge in petroleum engineering, with major safety and operational implications. It is also important across industries involving the transport of multiphase fluids. Misidentifying flow regimes can introduce major operational risk, yet regime boundaries in annular gas-liquid flow are often visually complex and context dependent.

The objective of this study was to evaluate the utility of convolutional neural network (CNN) classifiers for flow regime identification. The CNN was trained using annular flow image dataset published by Texas A&M University. The dataset consists of approximately 947 RGB images …

Crossing The Theory Threshold: The Pedagogical Potential Of Generative Artificial Intelligence In Educational Research, Amanda Burbage, Jennifer L. Styron

EVMS School of Health Professions Faculty Publications

Purpose

This paper presents findings from an educational research graduate course in which generative artificial intelligence (AI) was incorporated to strengthen learners' understanding of threshold concepts related to theoretical frameworks. Medical and health professionals often struggle with the transition from a clinical role into the educational research role.

Methods

The study posits that the use of generative AI will help learners understand and apply theoretical frameworks beyond a superficial level, furthering their understanding, constructing new knowledge, and strengthening their ability to develop sound educational research studies. Journal and AI transcripts were analyzed for 37 participants.

Results

Open-ended codes were grouped …

What Are Information Literacy Skills? Western Australian Primary Teachers’ Interpretations Of The Ict Curriculum, Louise Moroney, Vaille Dawson

Research outputs 2022 to 2026

Teachers must equip students to navigate an increasingly complex world of unique challenges and opportunities, necessitating the development of a diverse range of transferable skills. These skills are embedded in the General Capabilities (GC) of the Australian school curriculum. Upper primary school teachers’ interpretations of one of the GC, Information and Communication Technology (ICT) learning progressions, was examined, as these skills have become increasingly important with the rise in generative and assistive artificial intelligence. Using an interpretivist paradigm, an exploratory study was used to determine the areas where 36 teachers differed in their interpretations of the learning progression. Data collected …

The Lawyer Of The Future: Ethics And Identity In The Age Of Ai, David Yosifon, Michael Santoro, Isaac Nikssarian

American University Law Review

The dawn of artificial intelligence (AI) poses a fundamental challenge to the legal profession’s practical function and social identity. We argue that this challenge should be met as an opportunity to reclaim the profession’s core ethical intentions. We approach the emergence of AI as an occasion to define and safeguard what is irreducibly human in legal work. We ground our approach in the ethical imperatives set out in the American Bar Association’s Model Rules of Professional Conduct, while extending them into an invigorated framework for the AI era.

We survey the uses and ethical challenges associated with cutting-edge deployment of …

From Bias To Bottleneck: A Quantitative Analysis Of Gender Preferences In Tech Hiring, Uma Chidambaram

Theses and Dissertations

This applied dissertation examined whether gender preferences influence hiring decisions in the information technology (IT) sector, and whether such preferences contribute to the ongoing labor shortage in the field. Despite national and international initiatives to close the gender gap, women continue to represent only 28% of the United States IT workforce and remain significantly underrepresented in technical and leadership roles. Grounded in the Eagly and Karau (2002) Role Congruity Theory of Prejudice, this study investigated whether evaluator gender and candidate gender alignment affect interview selection outcomes at the résumé screening stage for both leadership and non-leadership IT positions.

A quantitative, …

Can An Experienced Qualitative Researcher Distinguish Ai From Human Qualitative Content Analysis?, Alexandra T. Lucas, Jianna Ramos, Maria Bajwa, Aaron Calhoun, Mark W. Scerbo, Janice C. Palaganas

Psychology Faculty Publications

Background

Artificial intelligence (AI) has become increasingly embedded in research workflows. Large language models (LLMs) are being used to code segments of text, organise codes into themes and interpret patterns within contexts. Recent comparisons between human and AI analyses demonstrate up to 80% thematic overlap, yet humans consistently exhibit deeper interpretive integration and contextual understanding. This study assesses whether experienced researchers can distinguish between entirely human-generated and AI-generated qualitative content analyses of a simulation debriefing.

Methods

We conducted a qualitative descriptive study comparing human-generated qualitative content analysis (QCA) with ChatGPT-4o-generated QCA using a single focus group transcript on emotion management …

Artificial Intelligence And Machine Learning In Smart Vaginal Formulation Development, Deborah A. Ogundemuren, Vivek Agrahari, Andrew P. Wong, Carolina Herrera, Margaret O. Ilomuanya, Gustavo F. Doncel

CONRAD Publications

Vaginal drug delivery in women's health remains underutilized and insufficiently studied, largely due to the complexity and dynamic nature of the vaginal microenvironment. Variations in vaginal pH, hormonal levels, and microbiota composition introduce significant biological variability, complicating formulation design and contributing to inconsistent therapeutic outcomes and poor patient adherence. Conventional vaginal formulations often fail to account for these individual differences, highlighting the need for more adaptive and predictive approaches. Emerging advances in artificial intelligence (AI) and machine learning (ML) offer promising strategies to address these challenges by enabling multi-parameter, data-driven formulation development that explicitly considers biological variability. Despite their transformative …

An Incidental Standard For Medical Ai, Nicholson W. Price Ii

Articles

Medical AI is poised to make a major difference in the provision of health. It brings major challenges, though: how can developers and implementers ensure that it will work safely and effectively—especially within the context of complex and highly variable health-care systems? Standards provide one key tool, potentially providing guidelines for everything from privacy to accuracy to how AI interacts with human clinicians. This Essay considers the last of these, describing a powerful quasi-standard from a surprising source: an FDA guidance document that tells developers when certain AI systems are not considered medical devices, and are therefore not regulated by …

Large Language Model-Assisted Research Question Development In Public Health: A Case Study In The Special Supplemental Nutrition Program For Women, Infants, And Children (Wic), Qi Zhang, Bidusha Neupane, Priyanka Patel, Futun N. Alkhalifah, Yi He, Leslie Hodges

Health Behavior, Policy & Management Faculty Publications

Objective:

To assess the feasibility of using large language models (LLMs) to develop research questions about changes to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food packages.

Design:

We conducted a controlled experiment using ChatGPT-4 and its plugin, MixerBox Scholarly, to generate research questions based on a section of the USDA summary of the final public comments on the WIC revision. Five questions weekly for three weeks were generated using LLMs under two conditions: fed with or without relevant literature. The experiment generated 90 questions, which were evaluated using the FINER criteria (Feasibility, Innovation, Novelty, Ethics, …

Against Ai Half Measures, Woodrow Hartzog, Neil Richards, Ryan Durrie, Jordan Francis

Faculty Scholarship

So far, U.S. consumer protection policy for artificial intelligence (AI) accountability has largely consisted of industry-led approaches such as encouraging transparency, mitigating bias, promoting principles of ethics, and empowering people. These approaches are vital, but they are only half measures. To bring AI within the rule of law, lawmakers must start drawing substantive lines.

In this Article, we identify four AI regulatory approaches to consumer, data, and democratic harms as half measures. First, transparency does not produce accountability on its own. Second, while mitigating bias in AI systems is critical, even unbiased systems are a threat to the vulnerable. Third, …

Artificial Intelligence In Higher Education: A Bibliometric And Science-Mapping Analysis From An Institutional And Management Perspective, Kürşat Taştan, Nalan Sabır Taştan

Khazar Journal of Humanities and Social Sciences

This article maps the field of artificial intelligence in higher education (HEI-AI) from an institutional and management perspective. We draw on 52,270 peer-reviewed articles and reviews indexed in Web of Science and Scopus between 1959 and 2025. Using the bibliometrix package and its biblioshiny interface in R, we combine descriptive indicators with science-mapping techniques, including co-authorship and co-citation networks, keyword co-occurrence, thematic mapping and thematic evolution. The initial corpus of 94,845 records was cleaned by merging the two databases, removing duplicates and restricting the sample to full-length journal articles and reviews that explicitly address AI in higher education.

The results …

Getting Started With Artificial Intelligence In 2025, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2025

Meeting proceedings of a seminar by the same name, held November 25, 2025.

Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber

Al-Esraa University College Journal for Engineering Sciences

Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …

From Enhancement To Substitution: A Strategic Provocation On Simulation-Based Sport, Grant B. Morgan, Andreas Stamatis

Journal of Applied Sport Management

Advances in artificial intelligence, large-scale machine learning, and simulation technologies are rapidly transforming how sport is played, analyzed, and consumed. To date, most scholarly and industry discussions frame these technologies as tools that enhance embodied sport by improving performance, officiating, media production, and fan engagement. This paper extends that conversation by posing a more provocative strategic question: under what conditions might simulation move from enhancement to substitution? Focusing explicitly on sport as a business and entertainment enterprise, we argue that many of sport’s core sources of cultural and economic value—uncertainty of outcome, narrative continuity, legitimacy, and collective meaning—are structurally …

Panda-Plus: Improved Dataset Of Prostate Whole Slide Images From Panda Challenge With Pixel-Level Expert Annotations, Spencer Hopson, Carson Mildon, Corbyn Kubalek, Joshua L. Ebbert, Ryan Vance, Lauren Laverty, Paul Urie, Dennis Della Corte

Faculty Publications

Artificial intelligence (AI)-based prostate cancer detection through whole slide images (WSIs) offers promising potential to address the global pathologist shortage while improving clinical consistency. Digital slides and improving image analysis methods encourage the creation of tools to aid in WSI classification. Despite promising advances, these tools are still limited by available training data. Current publicly available datasets, such as Kaggle's PANDA Challenge, while large in scale, rely on slide-level labels that may introduce noise and limit model reliability. Others contain detailed annotations, but are smaller in size due to manual processing efforts. In this work, we introduce PANDA-PLUS, a 546-image …

The Role Of Ai In Addressing The United Nations Sustainable Development Goals (Sdgs): A Comprehensive Survey, Walid Abdullah, Muhammad Nawaz, Basma Nasir, Muhammad Javed Ramzan

Sustainable Machine Intelligence Journal

Artificial Intelligence (AI) emerges as a transformative tool in addressing global challenges, particularly in achieving the United Nations Sustainable Development Goals (SDGs). This paper provides a comprehensive survey of how AI technologies contribute to addressing global challenges across social, economic, and environmental domains. By enabling advanced data analysis, predictive modeling, and automation, AI offers innovative solutions across sectors such as poverty reduction, healthcare, quality education, sustainable cities, climate action, and the protection of life on land and below water. Special attention is given to practical, real-world examples where AI enables more efficient resource management, predictive analytics, environmental monitoring, and data-driven …

Pixel-Perfect Segmentation Of Solar Filaments, Jamie Harris

Undergraduate Research Symposium

The observation and classification of solar filaments has a drastic impact on the ability to predict solar-magnetic weather phenomena that threatens to put both satellite infrastructure and astronauts at risk. Using the Hɑ filter provided by the Global Oscillations Network Group (GONG), a network of six telescopes around the world dedicated to 24/7 surveillance of the sun, we are able to get images that clearly and prominently display filament activity. With the vast amount of images the GONG takes, it is not possible to manually analyze every image. Using the U-Net model for computer vision, we were able to train …

Is Ai Replacing Human Mental Health Professionals?, Michiko Ueda

Population Health Research Brief Series

An increasing number of people are turning to generative artificial intelligence (AI) tools and AI-assisted chatbots to manage mental health concerns. This data slice presents findings from a national survey of U.S. adults aged 18-49 (N = 1,805) conducted in October 2025. Among respondents, 35.2% reported using AI tools more than once a week for mental health support. Among those who had ever seen a human mental health professional, 28.4% reported visiting human providers less often since beginning to use AI for the same purpose. The findings suggest that a subset of users may be using AI to replace, rather …

Nursing Faculty Attitudes Toward Artificial Intelligence: A Quantitative Causal-Comparative Cross-Sectional Study, Micaela Mcspadden

Doctoral Dissertations and Projects

The rapid growth of artificial intelligence (AI) in healthcare has highlighted the importance of understanding how nursing faculty perceive this technology. Although prior studies have explored public views, nurses’ perceptions, and faculty attitudes toward technology and curriculum change, limited research has focused on nursing faculty perspectives toward AI. Through the lens of the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM), this study examined factors that influence nursing faculty attitudes toward AI in nursing education. This study used a quantitative, causal-comparative, cross-sectional design with 263 nursing faculty participants from undergraduate pre-licensure programs in the United States. Participants …

Hollywood, Ai, And The Moral Universe: An Analysis Of The Terminator And Battlestar Galactica, Lara Sumera Samms

Masters Theses

This thesis defends the argument that depictions of artificial intelligence in Hollywood film and television point to a moral universe. Films The Terminator (1984) and Terminator 2: Judgment Day (1991), as well as the television series Battlestar Galactica (2004-2009) are analyzed to find clues of moral facts. This research paper submits that these stories add weight to the moral argument and provide evidence that humans implicitly recognize a moral universe. Such acknowledgment of moral structures cannot be adequately explained within a secular framework such as utilitarianism or evolutionary ethics. However, the Christian worldview frames reality around the existence of God, …

Exploring The Influence Of Artificial Intelligence On Teaching Strategies In Higher Education: A Phenomenological Approach, Dawn M. Hamilton

Doctoral Dissertations and Projects

The purpose of this transcendental phenomenological study was to describe the lived experiences regarding the influence of artificial intelligence (AI) on the teaching strategies for higher education instructors. Guided by Vygotsky’s constructivist learning theory, which emphasizes the active role of learners in constructing knowledge through engagement and interaction, this study aimed to explore how educators interpret, adapt to, and implement AI in their classrooms. The central research question asked: What are the lived experiences of higher education instructors regarding the influence of AI on their teaching strategies? The study was conducted at with higher education faculty actively who were directly …

Integrating Chatgpt In Teacher Education: Examining Early Childhood And Elementary Pre-Service Teachers’ Experiences In Ai-Assisted Math Lesson Planning, Hae Min Yu, Hyeseong Lee, Seung Kim

Education Department Faculty Articles

This study examines how pre-service teachers in early childhood education (ECE) and elementary education (ELE) integrate ChatGPT into mathematics lesson planning. Using a mixed-methods case study framed by the Technological Pedagogical Content Knowledge (TPACK) with Contextual Knowledge (XK) framework and AI literacy, we analyzed the experiences of 44 pre-service teachers (24 ECE, 20 ELE) in mathematics method courses at a university in the Midwestern United States. Data sources included pre- and post-assessments, documentation of ChatGPT interactions, lesson plans, and reflection papers. Findings reveal significant gains in participants’ knowledge of and confidence in using ChatGPT, with increased willingness to incorporate generative …

Scholarai Scholarly Article Search Strategies With The Ayni Method Multi-Neutrosophic For Ethical Information Management In Ai, Ennio Jesús Mérida Córdova, Elizabeth Esther Vergel Parejo, Raúl López Fernández

Neutrosophic Sets and Systems

In a digital world where scientific articles are published at an unprecedented rate, an additional step in the research process to facilitate discovery is an effective search and filtering for worthwhile articles. Thus, this study aims to solve the following research problem: how to search for scientific articles using artificial intelligence (AI) while applying ethical considerations and ancestral knowledge? The topical relevance is that as AI is a great vessel to seek potentially accessible knowledge, searches can be guaranteed through accuracy, inclusivity, and ethics. While many studies exist on the topic of AI related to searching, few, if any, extend …

Artificial Intelligence And The Translation Of Culture-Specific Terms On Arabic Monolingual Signs At Aseer Tourist Sites, Saudi Arabia, Ali Mohammad A. Alghamdi, Bakr Bagash Mansour Ahmed Al-Sofi

UB Journal for Humanities

Artificial intelligence (AI) tools are increasingly used in various fields, including the translation of signs within linguistic landscapes. This field-based study investigates the performance of AI tools, namely, Google Gemini and DeepSeek, in translating culture-specific terms (CSTs). To this end, Arabic monolingual signs at tourist sites in Aseer region in Saudi Arabia were documented and a comparative content analysis approach was employed to evaluate the accuracy, cultural sensitivity, and contextual relevance of the AI-generated translations. These translations were then compared to human translations using the same criteria designed for independent human evaluation. The findings indicated that Gemini consistently outperformed DeepSeek …

Artificial Intelligence In Higher Education: Opportunities And Challenges, Maytha Al-Ali, Adam Marks, Jasur Umirzokov, Noura Metawa

Iraqi Journal for Computer Science and Mathematics

While AI is often presented as a panacea for the challenges facing higher education, there is limited empirical evidence supporting its effectiveness in improving student learning and institutional performance. This gap between expectation and reality emphasizes the need for rigorous research, realistic goal-setting, and careful planning to ensure that AI technologies deliver on their promises in higher education. This study contrasts the potential utilization of AI technologies in Higher Education from the literature, against actual utilization in universities. The study also investigates the key barriers of AI implementation in higher education. This study uses a mixed-research methods approach, including case …

From Static Prediction To Mindful Machines: A Paradigm Shift In Distributed Ai Systems, Rao Mikkilineni, W. Patrick Kelly

Barowsky School of Business | Faculty Scholarship

A special class of complex adaptive systems—biological and social—thrive not by passively accumulating patterns, but by engineering coherence, i.e., the deliberate alignment of prior knowledge, real-time updates, and teleonomic purposes. By contrast, today’s AI stacks—Large Language Models (LLMs) wrapped in agentic toolchains—remain rooted in a Turing-paradigm architecture: statistical world models (opaque weights) bolted onto brittle, imperative workflows. They excel at pattern completion, but they externalize governance, memory, and purpose, thereby accumulating coherence debt—a structural fragility manifested as hallucinations, shallow and siloed memory, ad hoc guardrails, and costly human oversight. The shortcoming of current AI relative to human-like intelligence is therefore …

A Comparision Of Teachers' Ratings Of Published Versus Ai-Generated Descriptions Of Evidence Based Practices In Education., Lora T. Hall

Electronic Theses and Dissertations

The persistent gap between educational research and classroom practice continues to limit teachers’ use of evidence-based practices (EBPs), despite strong empirical support and federal mandates encouraging their implementation. A key barrier to closing this research-to-practice gap is the limited accessibility, usability, and perceived relevance of traditional research dissemination formats. With the rapid rise of artificial intelligence (AI) tools capable of summarizing and restructuring complex information, this study examined whether AI-generated practitioner-oriented descriptions of an EBP would be rated differently from a published practitioner article on the same practice. Using an experimental cross-sectional survey design, 70 in-service teachers were randomly assigned …

Emotion Analysis And Neural Language Models For Classification, Andrew Mackey

Graduate Theses and Dissertations

Emotion analysis is a branch of artificial intelligence and natural language processing focused on recognizing emotions hidden throughout various forms of digital data, including text, images, and multi-modal representations. In this dissertation, we present four published and planned works that investigate different methodologies for natural language analysis tasks using deep learning techniques. The first published work we present considers the task of identifying fake news using various text and emotion representations. We demonstrate that emotion representations combined with word embedding techniques can improve the accuracy of fake news classification. Our second published work further investigates the fake news classification task …