Artificial Intelligence and Robotics Commons^™

Data-Driven Decision Support Tool Co-Development With A Primary Health Care Practice Based Learning Network, Jacqueline K. Kueper, Jennifer Rayner, Sara Bhatti, Kelly Angevaare, Sandra Fitzpatrick, Paulino Lucamba, Eric Sutherland, Daniel J. Lizotte

Epidemiology and Biostatistics Publications

Background: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project.

Methods: We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in …

Atomistic-Informed And Machine Learning-Assisted Crystal Plasticity Modeling For Materials Interface, Ibrahim Altarabsheh

Doctoral Dissertations

This dissertation presents a comprehensive study that addresses two critical challenges in the field of computational materials science and engineering from nano- to mesoscale. First, to overcome the well-acknowledged length scale limitation associated with atomistic simulations, a novel two-step approach is introduced for a probabilistic prediction of stress-strain curves in terms of material volume. The method combines Molecular Dynamics (MD) simulations and a multioutput Gaussian process (MOGP) with Bayesian analysis to model stress-strain behavior and predict stress and strain values. The model effectively captures the intricate three-stage curve shape exhibited in stress-strain plots, discerning key points such as yielding, hardening, …

Hybrid Flexible (Hyflex) Learning Space Design And Implementation At Graduate Level: An Iterative Process, David Santandreu Calonge, Mark Thompson, Leisa Hassock, Mohammad Yaqub

Computer Vision Faculty Publications

This paper investigates the process of designing HyFlex classrooms at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), a graduate-level research university located in Abu Dhabi, United Arab Emirates, underpinned by the application of the EDUCAUSE Learning Space Rating System (LSRS). This investigation takes the form of a case-study and specifically focuses on the rationale, planning, design, and technology behind the implementation of the flexible HyFlex spaces as deployed in several classroom environments at MBZUAI. Iterations’ performance was assessed with the LSRS—V3. The findings should make an important contribution to the field of HyFlex learning spaces and technology-enhanced classroom design …

Uavs And Deep Neural Networks: An Alternative Approach To Monitoring Waterfowl At The Site Level, Zachary J. Loken

LSU Master's Theses

Understanding how waterfowl respond to habitat restoration and management activities is crucial for evaluating and refining conservation delivery programs. However, site-specific waterfowl monitoring is challenging, especially in heavily forested systems such as the Mississippi Alluvial Valley (MAV)—a primary wintering region for ducks in North America. I hypothesized that using uncrewed aerial vehicles (UAVs) coupled with deep learning-based methods for object detection would provide an efficient and effective means for surveying non-breeding waterfowl on difficult-to-access restored wetland sites. Accordingly, during the winters of 2021 and 2022, I surveyed wetland restoration easements in the MAV using a UAV equipped with a dual …

Large Language Model Use Cases For Instruction, Plus A Primer On Prompt Engineering, Roy Haggerty, Justin Cochran

LSU Health New Orleans Symposium Series on Artificial Intelligence

AMA Credit Designation Statement: The Louisiana State University School of Medicine, New Orleans designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

NCPD Credit Designation Statement: Nursing participants may earn 1.0 NCPD contact hours. Each nursing participant must be present for the entire session for which NCPD contact hours are requested and must complete an evaluation of the session to receive credit.

The Fast And The Curious: Accelerating Literature Reviews With Ai, Jennifer Freer, Natalia Tingle Dolan, Gabrielle Wiersma

Presentations and other scholarship

As the world of academic research shifts gears into the digital age, AI-powered tools are beginning to shape the scholarly landscape. Just as high-performance vehicles transformed the world of car racing, AI-powered tools like scite, Elicit, and Research Rabbit have the potential to revolutionize the traditional literature review process. This presentation will accelerate your understanding of AI literature review tools and how these technologies can turbocharge the research process. Navigating between traditional library tools and AI-powered systems can be like choosing the right vehicle for the race. AI tools can enhance the speed, depth, and breadth of literature reviews, allowing …

Machine Learning For Electronic Design Automation: Specification Mining And High-Level Synthesis, Md Rubel Ahmed

USF Tampa Graduate Theses and Dissertations

The rapid growth of complex system-on-chip (SoC) designs has presented unprecedented opportunities and challenges in electronic design automation (EDA). This dissertation explores two facets of electronic design automation: message flow specification mining using data mining and natural language processing (NLP) and high-level synthesis (HLS) acceleration using different machine learning (ML) methods. It also discusses an ML model co-optimization method for energy-efficient hardware implementation.

Effective SoC design validation relies heavily on message flow specifications. This dissertation presents an efficient technique for synthesizing finite state automaton (FSA) models from SoC execution traces. The synthesized models can provide valuable insights into the on-chip …

Big Data Analytics For Healthcare Social Media: New Algorithms And Insights, Negar Maleki

USF Tampa Graduate Theses and Dissertations

Over the last two decades, there has been a rapid evolution in information and communication technology, including the emergence of social media. Social media has a significant impact on various fields such as politics, business, culture, education, careers, innovation, and especially healthcare. This influence is not a new phenomenon since a survey from ten years ago showed that up to 78\% of American adults used the internet to look for health-related information for themselves or someone else. With the shift towards on-demand services in society, healthcare is also affected by this trend. Instead of waiting for weeks or months to …

Human Vs Machine: Hyper-Realistic Avatars And Their Efficacy As A Communication Channel, Jill S. Schiefelbein

USF Tampa Graduate Theses and Dissertations

Hyper-realistic avatars (HRAs), a form of synthetic media, are custom-created digital embodiments of a human, created by capturing and combining that person’s video and vocal likeness. This is the first known study of the efficacy of videos delivered by hyper-realistic avatars as a communication channel in comparison to videos delivered by their human counterparts. An experiment testing how information retention, engagement, and trust vary between viewers of videos delivered by a real human, videos delivered by the HRA representing that same human, and videos delivered by the HRA that discloses to viewers that it is a hyper-realistic avatar is presented. …

Preface: Special Issue On Nlp Approaches To Offensive Content Online, Marcos Zampieri, Isabelle Augenstein, Siddharth Krishnan, Joshua Melton, Preslav Nakov

Natural Language Processing Faculty Publications

No abstract provided.

Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Disease Informed Neural Network And Mathematical Modeling Of Covid-19 With Human Intervention, Jeremis Morales-Morales, Alonso Gabriel Ogueda, Carmen Caiseda, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Smart Street Light Control: A Review On Methods, Innovations, And Extended Applications, Fouad Agramelal, Mohamed Sadik, Youssef Moubarak, Saad Abouzahir

Computer Vision Faculty Publications

As urbanization increases, streetlights have become significant consumers of electrical power, making it imperative to develop effective control methods for sustainability. This paper offers a comprehensive review on control methods of smart streetlight systems, setting itself apart by introducing a novel light scheme framework that provides a structured classification of various light control patterns, thus filling an existing gap in the literature. Unlike previous studies, this work dives into the technical specifics of individual research papers and methodologies, ranging from basic to advanced control methods like computer vision and deep learning, while also assessing the energy consumption associated with each …

Limitations And Possibilities Of Digital Restoration Techniques Using Generative Ai Tools: Reconstituting Antoine François Callet’S Achilles Dragging Hector’S Body Past The Walls Of Troy, Charles O'Brien, James Hutson, Trent Olsen, Jay Ratican

Faculty Scholarship

Digital restoration offers new avenues for conserving historical artworks, yet presents unique challenges. This research delves into the balance between traditional restoration methods and the use of generative artificial intelligence (AI) tools, using Antoine François Callet’s portrayal of Achilles Dragging Hector’s Body Past the Walls of Troy as a case study. The application of Easy Diffusion and Stable Diffusion 2.1 technologies provides insights into AI-driven restoration methods such as inpainting and colorization. Results indicate that while AI can streamline the restoration process, repeated inpainting can compromise the painting’s color quality and detailed features. Furthermore, the AI approach occasionally introduces unintended …

Novus Ex Machina: Realise Your Organisation’S Creative Potential With Ai, Adam Tatarynowicz, Utz Claassen

Asian Management Insights

Innovation managers must learn how to harness AI’s transformative potential.

Healthaichain: Improving Security And Safety Using Blockchain Technology Applications In Ai-Based Healthcare Systems, Naresh Kshetri, James Hutson, Revathy G

Faculty Scholarship

Blockchain as a digital ledger for keeping records of digital transactions and other information, it is secure and decentralized technology. The globally growing number of digital population every day possesses a significant threat to online data including the medical and patients’ data. After bitcoin, blockchain technology has emerged into a general-purpose technology with applications in medical industries and healthcare. Blockchain can promote highly configurable openness while retaining the highest security standards for critical data of medical patients. Referred to as distributed record keeping for healthcare systems which makes digital assets unalterable and transparent via a cryptographic hash and decentralized network. …

Digitizing The Cultural Capital: Harnessing Digital Humanities For Heritage Preservation In Bujumbura, Burundi, James Hutson, Pace Ellsworth, Matt Ellsworth, Jean Bosco Ntungirimana

Faculty Scholarship

In an era where the erosion of cultural heritage is increasingly prevalent, there exists a critical imperative to explore and implement innovative methods for the preservation and revitalization of cultural identities, as exemplified by the urgent situation in Bujumbura, Burundi. Central to this study is the exploration of innovative digital methodologies for archiving a wide spectrum of cultural artifacts, including both notable and everyday heritage elements, in Bujumbura. Traditional approaches to biographical and historical profiling have predominantly focused on official records and significant events, often neglecting the richness of personal experiences and everyday interactions that substantially shape cultural identities. To …

Individuality And The Collective In Ai Agents: Explorations Of Shared Consciousness And Digital Homunculi In The Metaverse For Cultural Heritage, James Hutson, Jay Ratican

Faculty Scholarship

The confluence of extended reality (XR) technologies, including augmented and virtual reality, with large language models (LLM) marks a significant advancement in the field of digital humanities, opening uncharted avenues for the representation of cultural heritage within the burgeoning metaverse. This paper undertakes an examination of the potentialities and intricacies of such a convergence, focusing particularly on the creation of digital homunculi or changelings. These virtual beings, remarkable for their sentience and individuality, are also part of a collective consciousness, a notion explored through a thematic comparison in science fiction with the Borg and the Changelings in the Star Trek …

A Review Of Cyber Attacks On Sensors And Perception Systems In Autonomous Vehicle, Taminul Islam, Md. Alif Sheakh, Anjuman Naher Jui, Omar Sharif, Md Zobaer Hasan

School of Mathematical & Statistical Sciences Faculty Publications

Vehicle automation has been in the works for a long time now. Automatic brakes, cruise control, GPS satellite navigation, etc. are all common features seen in today's automobiles. Automation and artificial intelligence breakthroughs are likely to lead to an increase in the usage of automation technologies in cars. Because of this, mankind will be more reliant on computer-controlled equipment and car systems in our daily lives. All major corporations have begun investing in the development of self-driving cars because of the rapid advancement of advanced driver support technologies. However, the level of safety and trustworthiness is still questionable. Imagine what …

Smartphone Based Object Detection For Shark Spotting, Darrick W. Oliver

Master's Theses

Given concern over shark attacks in coastal regions, the recent use of unmanned aerial vehicles (UAVs), or drones, has increased to ensure the safety of beachgoers. However, much of city officials' process remains manual, with drone operation and review of footage still playing a significant role. In pursuit of a more automated solution, researchers have turned to the usage of neural networks to perform detection of sharks and other marine life. For on-device solutions, this has historically required assembling individual hardware components to form an embedded system to utilize the machine learning model. This means that the camera, neural processing …