Digital Commons Network^™

Adaptive Bayesian Clinical Trials: The Past, Present, And Future Of Clinical Research, Donald A Berry

Faculty, Staff and Student Publications

Background/Objectives: Decision-analytic Bayesian approaches are ideally suited for designing clinical trials. They have been used increasingly over the last 30 years in developing medical devices and drugs. A prototype trial is a bandit problem in which treating participants is as important as treating patients in clinical practice after the trial.

Methods: This article chronicles the use of the Bayesian approach in clinical trials motivated by bandit problems. It provides a comprehensive historical and practical review of Bayesian adaptive trials, with a focus on bandit-inspired designs.

Results: The 20th century saw advances in Bayesian methodology involving computer simulation. In the …

Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala

School of Computing: Dissertations, Theses, and Student Research

Multi-agent systems (MAS) possess significant potential for modeling real-world scenarios requiring coordinated actions (like wildfire fighting or ridesharing) among autonomous entities or agents (e.g., wildfire fighting agents) in complex, dynamic environments. Effective decision-theoretic planning (where each agent must carefully consider both the immediate and the future situations or states, and coordinate with the other agents (neighbors) to evaluate what needs to be done at present) within MAS, especially multiagent planning, where the planning agent directly models its neighbors in order to estimate their optimal actions, is critical, yet challenged by factors like partial observability, openness, and diverse agent types with …

Towards Sustainable Community-Designed Ai Systems In The Public Sector, Victoria Chui, Kelly Mcconvey, Erina Seh-Young Moon, Maya Ghai, Shion Guha

Health Services and Informatics Research

Advancements in data-driven modeling and artificial intelligence applications in public sector settings can lead to increased ten sions between stakeholder needs and tangible model capabilities from developers. Engaging multiple stakeholder groups in model development through the gleaning of sociotechnical, theoretical in sights using qualitative methods can contribute to more impactful, beneficial model solutions. Qualitative methods can complement quantitative model development, emphasizing stakeholder priori ties, informing model design choices, and promoting sustainable connections and model longevity. We are excited to discuss human centered qualitative methods, sustainable modeling practices, and community engagement in this workshop, engaging with scholars on system-level modeling strategies.

Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang

Journal of System Simulation

Abstract: With the rapid advancement of artificial intelligence and computing technologies, simulation technologies have leapfrogged, propelling the discipline of simulation toward greater maturity. Research progress in computer simulation technologies both in China and abroad was reviewed, and the definition and connotation of simulation were clarified. It was proposed that the Chinese terms "仿真" "仿效"and " 模拟" be unified under a single term " 仿真" with corresponding "Simulation" "Emulation" and "Analog" in English translated uniformly as "Simulation". Simulation science and engineering discipline was delineated, which was grounded in three core theoretical foundations: analogical theory,computational theory, and model validation theory. The first-level …

Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai

Pepperdine Dispute Resolution Law Journal

Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …

Prediction, Comparison And Visualization Of Premium Pricing Using Machine Learning Methods, Lal S Jan, Farzan Tashfeen, Mohid Hussain, Nadi M Alresheedi, Syed Muhammad Hassan Ahmer, Nahla M Albarkati

Yanbu Journal of Engineering and Science

This study investigates the efficacy of machine learning in forecasting and comparing health insurance premiums. The all-inclusive goal line is to improve the accuracy of premium pricing and minimize the manual labor associated with the traditional methods and present data trends in a logical manner. An open-source dataset of US medical premiums has been utilized and a systematic machine learning model in python programming language has been developed. This model took into account factors like age, bmi, smoking habits, and geographical location. The XGBoost model excels other models with an RMSE value of 0.349 and an adjusted R2 of 90.1% …

Research And Education In Robotics: A Comprehensive Review, Trends, Challenges, And Future Directions, Mutaz Ryalat, Natheer Almtireen, Ghaith Al-Refai, Hisham Elmoaqet, Nathir Rawashdeh

Michigan Tech Publications

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is …

Digital Forensics And Ai: Artifact Analysis And Using Ai In The Forensics Domain, Clinton Joel Walker

LSU Doctoral Dissertations

Digital Forensics (DF) is a field of forensic science focusing on the acquisition, authentication, and analysis of digital evidence while maintaining integrity of that data. DF analysts use forensic tools to parse large volumes of data for investigations and depend on them for identification of pertinent digital evidence in vast amounts of data. Keeping up with innovations and ever-expanding data volumes is a constant challenge for these investigators. The prevalence of Artificial Intelligence (AI) in everyday computing is rapidly expanding, with the use of Machine Learning (ML) and Large Language Models (LLM)s becoming increasingly commonplace. Innovations in technology bring new …

"Chatgpt Told Me To Say It": Ai Chatbots And Class Participation Apprehension In University Students, Daisuke Akiba

Publications and Research

The growing prevalence of AI chatbots in everyday life has prompted educators to explore their potential applications in promoting student success, including support for classroom engagement and communication. This exploratory study emerged from semester-long observations of class participation apprehensions in an introductory educational psychology course, examining how chatbots might scaffold students toward active and independent classroom contribution. Four students experiencing situational participation anxiety voluntarily participated in a pilot intervention using AI chatbots as virtual peer partners. Following comprehensive training in AI use and prompt design given to the entire class, participants employed systematic consultation frameworks for managing classroom discourse trepidations. …

Type-2 Neutrosophic Numbers For Artificial Intelligence Software Choice For Cybersecurity Testing, O.M. Akash, We’Am Adel Talafha, Mamdouh Gomaa

Neutrosophic Systems with Applications

The choice of artificial intelligence (AI) software for cybersecurity testing is a multi-criteria decision-making approach (MCDM) due to it including different criteria. Evaluation decision making problems include uncertainty and vague information. So, the neutrosophic set is used in this study to overcome this uncertainty and vague information. It has three functions such as truth, indeterminacy, and falsity functions. Type-2 neutrosophic numbers is a type of neutrosophic set that includes nine membership functions. This study uses the average method of computing the criteria weights. The CoCoSo method is used to rank alternatives. Six experts and decision makers created the decision makers …

Bridging Classical Rhetoric And Ai: A Systematic Framework For Developing Authorial Voice Through Large Language Models, Daniel Plate

Theses

This project addresses critical gaps in AI-assisted writing by developing the first systematic framework that integrates classical rhetorical principles with modern large language model capabilities for authorial voice development. The primary focus is on creating reliable methods for stylistic control through strategic AI collaboration rather than ad hoc prompting approaches. The project develops a comprehensive coding system for analyzing prose style, creates ten distinct authorial personas, and establishes a dual curation methodology that structures both stylistic analysis and content preparation. Implementation through the AI Writing Guide website provides practical tools including prompt templates, annotated examples, and instructional materials that demonstrate …

Analysis Of Vision Transformers And Domain Adaptation In Long-Range Facial Recognition, Zachary Michael Swanson

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Atmospheric turbulence presents a significant barrier to long-range facial recognition, introducing severe geometric distortions and blur that degrade image quality. This thesis investigates deep learning approaches for mitigating these effects, with a focus on transformer based architectures and domain adaptation strategies.

An in-depth benchmarking study was performed using convolutional neural networks (CNNs) and vision transformers (ViTs) on the Husker BRIAR Research Collection from up to 500m (HBRC-500) face dataset. The results demonstrated that vision transformers, particularly hierarchical vision transformers like the shifted-window (Swin) transformer, outperform CNN-based models at long distances due to their ability to model global spatial relationships and …

Artificial Intelligence In Sport Management: A Systematic Review, Scale Development And Validation, And Implications, Kemardo Tyrell

Theses and Dissertations

The democratization of intelligent systems and their ubiquitous presence across the sport industry have created an urgent need to understand the current environment and how stakeholders perceive artificial intelligence (AI) as it reshapes decision-making, engagement, and organizational design. This three-manuscript dissertation conceptualizes artificial intelligence as a contested domain shaped by stakeholder meaning-making, consumer perception, and shifts in organizational practice. The first manuscript provides a systematic review of AI in sport management using the PRISMA framework, mapping how AI has been conceptualized as a methodological tool or contextual innovation across the sport industry segmentation (performance, production, and promotion). The second manuscript …

Process-Grounded Knowledge-Infused Learning And Decision Making, Kaushik Roy

Theses and Dissertations

This dissertation introduces process-grounded knowledge-infused learning and reasoning, a novel framework for integrating domain-expertise-based process knowledge into the learning and reasoning mechanisms of artificial intelligence systems. This approach is designed to produce controlled, transparent, and reliable predictions in critical tasks such as medical diagnosis and recommendation. By focusing on the case study of mental illness diagnosis and recommendation—where decision-making must be grounded in processes such as disorder-specific diagnostic criteria—this work demonstrates methods to embed structured decision-making directly into the system architecture during both training and inference. This integration facilitates end-to-end training and reasoning while ensuring that outputs strictly adhere to …

Smart Traffic Management At Intersections, Gezim Hoxha, Piotr Gorzelanczyk, Rame Likaj, Shaban Thaqi, Flori Cikaqi

Journal of Sustainable Construction Materials and Technologies

Effective traffic control methods, whether at intersections or other nodes within the road network, play a critical role in ensuring traffic quality and safety. An inappropriate choice of traffic control techniques or poorly optimized light signal programming at intersections often leads to unsatisfactory service levels. This study specifically addresses the issues related to intersections controlled by traffic lights. It aims to identify the key factors influencing the regulation and programming of traffic lights, with a focus on using different microcontrollers, particularly the Raspberry Pi. The primary objective of this research is to develop a methodology and an adapted programming approach …

Ai‐Assisted Integration Of Computational Thinking: Pre‐Service Teachers’ Experiences In Early Childhood Mathematics Education, Hae Min Yu, Seung Kim, Hyeseong Lee

Education Department Faculty Articles

This study examined how pre-service teachers utilize artificial intelligence (AI) tools to integrate computational thinking (CT) in early childhood mathematics education. Through a qualitative case study guided by the TPACK framework, we examined 24 early childhood pre-service teachers enrolled in a mathematics methods course as they developed CT-integrated math lesson plans using AI assistance. Data sources included pre- and post-course open-ended questionnaires, CT exploration assignments, AI interaction documentation, lesson plans, and reflection papers. The findings revealed three patterns in how pre-service teachers leveraged AI as a scaffold: generating initial ideas for CT integration, refining these ideas for specific teaching contexts, …

Development Of “Defaketicon” An Educational Deepfake Awareness Website For Senior High School Stem-Technology Students, Killua Andrei S. Nava, Trisha Nicole E. Sese, John Carlo A. Tan, Juan Antonio D. Gulles, Princess Angel E. Miraflores, Christine Rae T. Hecto

DLSU Senior High School Research Congress

This study addresses the increasing threat of deepfake media by developing “Defaketicon” an educational website designed to raise awareness among senior high school STEM-Technology students at Adamson University. The primary objective is to evaluate the students’ perceptions towards the website in terms of performance expectancy, effort expectancy, social influence, and facilitating conditions. Using a convergent mixed-method approach, the researchers conducted a non-experimental descriptive design for the quantitative data and a narrative inquiry for the qualitative aspect. A total of 117 students participated through simple random sampling, while 8 were purposively selected for in-depth qualitative analysis. Findings from the quantitative data …

Forging The Future, Kenneth Benoit

Asian Management Insights

How AI is rewriting the rules of knowledge, expertise, and practice.

Strategy And Stewardship In An Uncertain World, Havovi Joshi

Asian Management Insights

This issue, as we continue to celebrate Singapore Management University’s (SMU) 25th anniversary, we explore leadership in higher education, the rise of artificial intelligence (AI), ethical stewardship, and other challenges, highlighting how they intersect in our increasingly complex, fast-changing world.

The Overstated Cost Of Ai Fairness In Criminal Justice, Ignacio Cofone, Warut Khern-Am-Nuai

Indiana Law Journal

The dominant critique of algorithmic fairness in AI decision-making, particularly in criminal justice, is that increasing fairness reduces the accuracy of predictions, thereby imposing a cost on society. This Article challenges that assumption by empirically analyzing the COMPAS algorithm, a widely used and widely discussed risk assessment tool in the U.S. criminal justice system.

This Article makes two contributions. First, it demonstrates that widely used AI models do more than replicate existing biases—they exacerbate them. Using causal inference methods, we show that racial bias is not only present in the COMPAS dataset but also worsened by AI models such as …

Computerized Diagnostic Decision Support Systems-Isabel Pro Versus Chatgpt-4 Part Ii, Joe M Bridges, Xiaoqian Jiang, Michael Ige, Oluwatoniloba Toyobo

Faculty, Staff and Student Publications

Objective: Does a Tree-of-Thought prompt and reconsideration of Isabel Pro's differential improve ChatGPT-4's accuracy; does increasing expert panel size improve ChatGPT-4's accuracy; does ChatGPT-4 produce consistent outputs in sequential requests; what is the frequency of fabricated references?

Materials and methods: Isabel Pro, a computerized diagnostic decision support system, and ChatGPT-4, a large language model. Using 201 cases from the New England Journal of Medicine, each system produced a differential diagnosis ranked by likelihood. Statistics were Mean Reciprocal Rank, Recall at Rank, Average Rank, Number of Correct Diagnoses, and Rank Improvement. For reproducibility, the study compared the initial expert panel run …

Alibaba: Building Advanced Intellectual Property Governance For E-Commerce Marketplaces, Liang Chen, Sin Mei Cheah, Can Huang, Guoqiao Liu

Asian Management Insights

How the global e-commerce powerhouse harnessed artificial intelligence (AI) to balance innovation and intellectual property (IP) rights protection.

Digital Resurrection Of Thonis-Heracleion: Technological Advances In Underwater Archaeology And A Speculative Ai-Driven Reconstruction Methodology, James Hutson, Passent Chahine

Faculty Scholarship

This article synthesizes past archaeological research on the submerged Egyptian city of Thonis-Heracleion, critically reviewing excavations and technological interventions deployed since its rediscovery by Franck Goddio and the IEASM team. Situated approximately 10 meters beneath Aboukir Bay near Alexandria, the city represents a significant nexus of Greek and Egyptian cultural heritage, vividly documented in classical sources such as Herodotus and Strabo. Prior excavations have recovered temple complexes, colossal statues, ritual artifacts, and an extensive array of ancient shipwrecks, mapping only a fraction of the extensive site. These investigations utilized pioneering geophysical methods, including multibeam sonar, side-scan sonar, and photogrammetry, establishing …

Facial Recognition Ai, Margaret Hu

Faculty Publications

The integration of algorithmic decisionmaking and artificial intelligence (“AI”) into facial recognition technology poses new, unprecedented risks to privacy and individual autonomy rights, particularly in urban settings. The murder of Brian Thompson, CEO of UnitedHealthcare, in New York City on December 4, 2024, provides a timely case study to examine the deployment of facial recognition systems by the New York Police Department and other law enforcement agencies to identify the suspect. New York City deploys some of the most sophisticated surveillance architecture in the nation, put into place following the terrorist attacks of September 11, 2001. This Article explores the …

Potential And Pitfalls Of Romantic Artificial Intelligence (Ai) Companions: A Systematic Review, Qi Hui Jerlyn Ho, Meilan Hu, Tracy Xi Chen, Andree Hartanto

Research Collection School of Social Sciences

As Artificial Intelligence (AI) becomes more integrated into daily life, individuals have increasingly turned to AIdriven systems for emotional support, companionship, and even romantic relationships. These relationships can be both beneficial and detrimental. Given the need for a comprehensive understanding of this phenomenon, this systematic review uses Sternberg’s Triangular Theory of Love to provide a holistic summary of its key potentials and pitfalls. A total of 23 articles were identified from the following databases: EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus, and Web of Science. Results highlighted the key potentials of being in a romantic relationship with AI companions as: the …

Artificial Intelligence Use In Medical Education: Best Practices And Future Directions, Rasheed A. M. Thompson, Yash B. Shah, Francisco Aguirre, Courtney Stewart, Costas D. Lallas, Mihir S. Shah

Department of Urology Faculty Papers

PURPOSEOF REVIEW: This review examines the various ways artificial intelligence (AI) has been utilized in medical education (MedEd)and presents ideas that will ethically and effectively leverage AI in enhancing the learning experience of medical trainees.

RECENT FINDINGS: AI has improved accessibility to learning material in a manner that engages the wider population. It has utility as a reference tool and can assist academic writing by generating outlines, summaries and identifying relevant reference articles. As AI is increasingly integrated into MedEd and practice, its regulation should become a priority to prevent drawbacks to the education of trainees. By involving physicians in …

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

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 explores how AI can 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 outlines different AI tools available to schools and discusses potential benefits and challenges of leveraging AI within Catholic schools. Future researchers should consider evaluating and analyzing implementation of AI tools within MTSS, specifically how AI tools …

A Proposed Coding Algorithm With Ai-Assisted Restoration Capability, Parviz Gharehbagheri, Hamid Haj Seyyed Javadi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces an innovative encoding method based on the concept of "distancecodes" , which allows characters to appear randomly in different locations during the decoding process. Codeword-based algorithms decode and present their characters sequentially, which can hinder accurate reconstruction in the event of incomplete text decoding, as there is no intelligent or non-intelligent model available for continuing the text reconstruction.In contrast, our proposed algorithm allows for the non-sequential and scattered appearance of characters throughout the data during the decoding process. This enables AI algorithms to restore undecoded characters using contextual information such as decoded characters, adjacent complete and incomplete …

The Impact Of Utilizing Ai-Enhanced Cognitive Trips On Academic Achievement And Attitude Improvement Towards Mathematics Among Secondary School Students, Rahma S. Thakir Dr

International Journal for Research in Education

This research aims to investigate the effectiveness of utilizing AI-enhanced cognitive trips in enhancing academic achievement and improving attitudes towards mathematics among second-grade secondary school students in the Jeddah Education Administration, Saudi Arabia. The study employed an experimental methodology with a pre-test-post-test design, utilizing control and experimental groups and a qualitative research approach. The research sample comprised 60 students, divided into control and experimental groups, each consisting of 30 students. To achieve the study's objectives, cognitive trips enhanced with AI tools were designed. An academic achievement test and a mathematics attitude scale were developed, alongside an interview questionnaire to identify …

Selected Artificial Intelligence Provisions In U.S. Fiscal Year 2025 National Defense Authorization Act, Bert Chapman

Libraries Faculty and Staff Presentations

The 2025 Fiscal Year National Defense Authorization Act contains multiple provisions relating to artificial intelligence (AI). These congressionally mandated provisions direct various sections of the Department of Defense (DOD) and individual U.S. armed service branches to execute congressional intent for AI policymaking. Examples of such intent include identifying and planning DOD's AI workforce, demonstrating AI biotechnology applications for national security, improving the human usability of AI systems, and establishing an AI security center. This presentation will note that reports on these initiatives must be prepared for relevant congressional oversight committees, and, in many cases, are in many cases, publicly released …