Artificial Intelligence and Robotics Commons^™

Advancing Deep Learning With Graph-Based Structural Insights: From Graph Classification To Semantic Segmentation, Xin Ma

Computer Science and Engineering Dissertations - Archive

Deep learning has profoundly transformed machine learning by offering sophisticated data representations, yet effectively incorporating structural information remains a challenge. Structural data, whether explicit or implicit, has the potential to significantly enhance the performance of deep learning tasks. This research investigates the benefits of structural information across three crucial tasks: classification, clustering, and segmentation. For explicit structural data, where inputs are directly represented as graphs, we investigate graph-level classification in brain connectivity networks. We introduce the Multi-resolution Edge Network (MENET), a novel framework designed to identify disease-specific connectomic benchmarks with high discriminatory power across diagnostic categories. MENET leverages graph-level representations …

A Unified Cross-Modal Interactive System For Assisting Vision Impaired In Human Navigation And Indoor Based Human Robot Interaction, Harish Ram Nambiappan

Computer Science and Engineering Dissertations - Archive

People who are blind and vision impaired often require assistance in performing various tasks. With new technologies emerging in the recent years, vision impaired people either require assistance in accessing those technologies or in using those technologies to perform different tasks in real life. Previous works have focused on assisting vision impaired people in different scenarios such as navigation, accessing smartphone interfaces etc. With the recent developments in robotics, a new research has emerged where new systems can be developed for vision impaired people to interact with robots to perform various human robot interactive tasks. But with developing new and …

Development Of A Positive Urinalysis Criteria Using A Machine Learning Approach, Kari Flicker, Jessica Parrott, Tammy Speerhas, Turaj Vazifedan, Theresa Guins, Jeffrey Bobrowtiz, Anne Mcevoy, Jade Eves, Debra Conrad, Benjamin Klick

Ellmer School of Nursing Faculty Publications

Background: Urinary tract infections (UTIs) are a commonly encountered diagnosis at pediatric urgent care (UC) centers. The urinalysis (UA) is usually the initial study in UC settings used to guide decisions regarding initiating empiric antibiotics and/or pursuing urine culture. However, studies in pediatric UC settings examining the ideal threshold for a positive result are lacking.

Methods: UA result data were extracted from the records of 6,327 pediatric patients, which were collected as part of a previous QI project. Logistic regression was used to determine the predictors of positive urine cultures. Decision trees for a positive UA result for both clean …

A Prototype Of A Conversational Virtual University Support Agent Powered By A Large Language Model That Addresses Inquiries About Policies In The Student Handbook, Joseph Benjamin R. Ilagan, Jose Ramon Ilagan

Quantitative Methods and Information Technology Faculty Publications

Universities gain a competitive advantage by deliberately improving overall service, student, faculty, and staff experience, leading to attractiveness, retention, and improved outcomes. Quality services are achieved partly by addressing employee satisfaction, specifically in the work environment. This paper presents a prototype study of a virtual university support agent, a system grounded in a Large Language Model (LLM) engineered to address inquiries from university students, faculty and staff related to the student handbook. The study investigates the integration of generative artificial intelligence and natural conversation properties inherent in LLMs to overcome customer service shortcomings identified in previous chatbot applications. The LLMs' …

Exploratory Prompting Of Large Language Models To Act As Co-Pilots For Augmenting Business Process Work In Document Classification, Jose Ramon Ilagan, Joseph Benjamin R. Ilagan, Claire Louisse Basallo, Zachary Matthew Alabastro

Quantitative Methods and Information Technology Faculty Publications

Businesses deal with different types of documents containing unstructured documents. The data in these documents must be converted into digital forms other automated systems could only process. One generic use case is document classification, which usually involves manual transformation due to human understanding needed in the process. These documents go beyond those generated through regular business transactions and operations and also include web-based content such as online news, blogs, e-mails, and various digital libraries. Recent developments in robotic process automation (RPA) and artificial intelligence (AI) aim to automate the otherwise expensive, time-consuming, and repetitive manual steps. Through more powerful natural …

Ethical Education Data Mining Framework For Analyzing And Evaluating Large Language Model-Based Conversational Intelligent Tutoring Systems For Management And Entrepreneurship Courses, Joseph Benjamin R. Ilagan, Jose Ramon Ilagan, Ma. Mercedes T. Rodrigo

Quantitative Methods and Information Technology Faculty Publications

Educational data mining (EDM) can be used to design better and smarter learning technology by finding and predicting aspects of learners. Amend if necessary. Insights from EDM are based on data collected from educational environments. Among these educational environments are computer-based educational systems (CBES) such as learning management systems (LMS) and conversational intelligent tutoring systems (CITSs). The use of large language models (LLMs) to power a CITS holds promise due to their advanced natural language understanding capabilities. These systems offer opportunities for enriching management and entrepreneurship education. Collecting data from classes experimenting with these new technologies raises some ethical challenges. …

Sparse Representer Theorems For Learning In Reproducing Kernel Banach Spaces, Rui Wang, Yuesheng Xu, Mingsong Yan

Mathematics & Statistics Faculty Publications

Sparsity of a learning solution is a desirable feature in machine learning. Certain reproducing kernel Banach spaces (RKBSs) are appropriate hypothesis spaces for sparse learning methods. The goal of this paper is to understand what kind of RKBSs can promote sparsity for learning solutions. We consider two typical learning models in an RKBS: the minimum norm interpolation (MNI) problem and the regularization problem. We first establish an explicit representer theorem for solutions of these problems, which represents the extreme points of the solution set by a linear combination of the extreme points of the subdifferential set, of the norm function, …

Automatic Hemorrhage Segmentation In Brain Ct Scans Using Curriculum-Based Semi-Supervised Learning, Solayman H. Emon, Tzu-Liang (Bill) Tseng, Michael Pokojovy, Peter Mccaffrey, Scott Moen, Md Fashiar Rahman

Mathematics & Statistics Faculty Publications

One of the major neuropathological consequences of traumatic brain injury (TBI) is intracranial hemorrhage (ICH), which requires swift diagnosis to avert perilous outcomes. We present a new automatic hemorrhage segmentation technique via curriculum-based semi-supervised learning. It employs a pre-trained lightweight encoder-decoder framework (MobileNetV2) on labeled and unlabeled data. The model integrates consistency regularization for improved generalization, offering steady predictions from original and augmented versions of unlabeled data. The training procedure employs curriculum learning to progressively train the model at diverse complexity levels. We utilize the PhysioNet dataset to train and evaluate the proposed approach. The performance results surpass those of …

Addressing Spectral Bias Of Deep Neural Networks By Multi-Grade Deep Learning, Ronglong Fang, Yuesheng Xu

Mathematics & Statistics Faculty Publications

Deep neural networks (DNNs) have showcased their remarkable precision in approximating smooth functions. However, they suffer from the spectral bias, wherein DNNs typically exhibit a tendency to prioritize the learning of lower-frequency components of a function, struggling to effectively capture its high-frequency features. This paper is to address this issue. Notice that a function having only low frequency components may be well-represented by a shallow neural network (SNN), a network having only a few layers. By observing that composition of low frequency functions can effectively approximate a high-frequency function, we propose to learn a function containing high-frequency components by composing …

Latent Space Dynamics Learning For Stiff Collisional-Radiative Models, Xuping Xie, Qi Tang, Xianzhu Tang

Mathematics & Statistics Faculty Publications

In this work, we propose a data-driven method to discover the latent space and learn the corresponding latent dynamics for a collisional-radiative (CR) model in radiative plasma simulations. The CR model, consisting of high-dimensional stiff ordinary differential equations, must be solved at each grid point in the configuration space, leading to significant computational costs in plasma simulations. Our method employs a physics-assisted autoencoder to extract a low-dimensional latent representation of the original CR system. A flow map neural network is then used to learn the latent dynamics. Once trained, the reduced surrogate model predicts the entire latent dynamics given only …

Review Of How Ai Works: From Sorcery To Science, By Ronald T. Kneusel, Taylor J. Greene

Library Articles and Research

A review of How AI Works: From Sorcery to Science, by Ronald T. Kneusel.

Road Extraction On Remote Sensing Imagery: Historical Mapping Of The Brazilian Amazon, Jonas Paiva Botelho Jr

Graduate Theses/Dissertations

This work proposes an artificial intelligence model based on U-Net architecture to map road networks in the Brazilian Amazon. Over the years, the Amazon region has been heavily exploited, leading to increased deforestation rates, contributing to CO2 emissions, amplifying global warming, and causing a disturbance in local fauna and flora. The expansion into the forest by illegal miners, loggers, and land grabbers can be tracked down by the construction of roads, which we can refer to as the arteries of deforestation. Previous works on the matter proposed algorithms that use high-resolution imagery to map roads precisely. However, this work approach …

Towards Dynamic Context Detection From Voice Commands And Conversations With Smart Assistants In Smart Homes, Jeniya Sultana

Graduate Theses/Dissertations

Voice-enabled interactions have become increasingly popular with the rise of voice assistants. Identifying contexts or meanings from voice commands and conversations with smart assistants can contribute to the autonomous control of smart home devices and appliances. To improve automation, there is a growing need for efficient context detection that eliminates the need to memorize voice commands. To address this need, I followed a two-step approach in my research. In the first step, I developed a unique context recognition model using a transformer, an attention mechanism, and a fully connected neural network. I trained this model on a conversational dataset of …

Title Page/Book Information, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

Table Of Contents, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

Contributors, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

34. "Language Weaves Its Tapestry": Crafting Found Poetry Using Ai Tools, Ruth Li

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

In this chapter, I offer a pedagogical approach to teaching creative writing in the era of Al technologies. I share an activity that engages students in crafting found poetry using Al tools such as ChatGPT. Found poems are collage-like assemblages drawn from other sources such as newspaper or magazine articles. By immersing students in crafting found poems using Al, I inspire creative experimentation with Al-generated texts. Even as writing processes become automated and writing styles standardized, I posit that this found poem activity nurtures students' careful attunement to the materiality of language, to its shape and texture as words unfold …

33. Chatgpt Assistance In Creating Chemistry Practice Problems: Pitfalls, Positives, And Possibilities, Michael A. Christiansen

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

ChatGPT, a relatively new Large Language Model (LLM) artificial intelligence (Al) chatbot, has gained significant attention as the most downloaded software app, accruing over 100 million users within two months of its release. This software can generate quick, articulate responses to virtually any textual query. Many educators are concerned about its potential for enabling student cheating. However, it currently suffers significant limitations in solving chemistry problems-documented through peer-reviewed articles and from the author's experience suggesting that chemistry students will perform far better, on average, by studying than by relying on ChatGPT. This is particularly true of math-centric problems, which the …

32. Using Generative Ai In The Music History Classroom, Reba Wissner

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Generative Al affords students and college teaching both challenges and opportunities, though faculty mainly focus on the challenges, as most discussion centers on assignment modification to prevent plagiarism and concentrate on text-generating Al. However, there is an entire world of Al tools that are not text limited that can be used to create non-text-based outputs and can be used for information recall and transferability of student knowledge; these tools are well-suited to the arts. One discipline in which these tools can be used is music; specifically, music history. Al generation tools not specifically created for music, such as chatbots, can …

Part Vi: Section 6: Disciplinary Approaches, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

31. Collaborative Writing And Ai: A Research Assignment For An Undergraduate Professional Communication Course, Beth Buyserie

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This chapter contextualizes and describes a collaborative Al research assignment for an in-person 2000-level Professional Communication general education course. This "Collaborative Writing and Al" assignment asks teams of students to 1) conduct their own secondary research on a specific topic connected to Al, 2) conduct primary research using Al itself, and 3) make recommendations to their peers and future colleagues in the profession or community on how to navigate and respond to a range of interdisciplinary conversations and perspectives on the technology. Within this chapter, the author provides a rationale for the assignment, includes suggestions for background readings included in …

30. Revising Llm Text To (Re)Discover Rhetoric In A Graduate Seminar, Clancy Ratliff

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

In this essay, I share an assignment that asks students to engage in rhetorical revision of LLM text using a changelog table as a tool to document the revision. To demonstrate to the students what I was asking them to do, I did the assignment myself, and my example is included in this chapter as well. I argue that the style of generated text from LLMs calls for increased resistance to the norms and conventions of school writing and an embrace of writing that's more rhetorical: a bit more personal, risky, rule-breaking, creative, and experimental, intentionally centering purpose and audience. …

29. An Ai Workshop For The Overwhelmed And Uninterested, Ritamarie Hensley

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

The impact of ChatGPT and other Generative Al technologies on the role of an Instructional Designer prompted a quest to understand the pros and cons of Al for course development. Despite initial enthusiasm from some educators, many instructors resisted Al, expressing concerns about assignments, academic integrity, and Al-induced hallucinations. The workshop is designed for faculty members who may feel overwhelmed by the myriad uses of Al in education or simply lack interest in Al tools. It offers nuanced approaches to assignments, emphasizes fostering digital literacy for academic integrity, and explores turning Al-induced hallucinations into teaching tools. The workshop also underscores …

27. Pushing Past The First Draft: Exercises In Revision, Jacob Taylor

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This essay provides a series of global and local revision exercises for writing students to use while developing their revision processes. These revision exercises offer physical and digital possibilities, including opportunities to use Al learning models. Each of the included exercises can be done with or without the use of Al to accommodate individual preferences. The provided global revision strategies promote major structural and/or thematic revisions while requiring writing students to take risks. The local revision exercises help writing students tighten up sentences and improve minor stylistic elements while remaining focused on patterns they can begin to identify in future …

25. Using The Ai Explainpaper To Help Students Better Understand Journal Articles, Erin Jensen, Daniel Hutchinson

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

We have students use the Al Explainpaper to be able to read and understand journal articles as this is a common assignment in many core classes. In our experiences, students often struggle to understand the content of journal articles and then struggle to use the journal article as a source in their writing. The Al Explainpaper provides an opportunity for students to use the bot to better understand the journal article and have an opportunity to ask the program additional questions about the article. We have found Explainpaper to provide help to students in being able to read and understand …

24. Revisioning A Bibliography Assignment To Center Discovery And Critical Source Engagement, Lillian Campbell, Jenna Green, Nicole Bungert

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This chapter shares context, assignment details, and impact of revisions of a research journal assignment in our first-year writing program at a mid-sized private university in the Midwest. With the rise of access to large language processing models like ChatGPT in Spring 2023, we reviewed our curriculum to consider what assignments might be most vulnerable to Al-generated writing. Our bibliography assignment was an obvious contender, since it focused on summary of individual sources. Thus, we worked with our research librarian liaison to reimagine this assignment, guided by a conversation about learning goals. After reviewing relevant scholarship on source use and …

Part V: Section 5: Teaching Resources, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

22. Examining Ways Of Using Ai To Better Support Teaching Faculty, Mitigate Burnout, And Increase Teaching Creativity, Jennifer Grewe

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Faculty burnout is a concern within academics particularly for the most student-centered teaching faculty. In attempts to support students, faculty can sometimes do so at the expense of their own time and energy that over time can become overwhelming. There exist many concerns within academia on the use of Al and yet this is a tool that could be helpful to teaching loads if utilized properly. This chapter explores ways in which Al might help alleviate some of the workload that teaching faculty experience, which is a start to addressing burnout issues. Ideas are shared in this chapter surrounding Al's …

21. My Summer With Chatgpt, Mary Lourdes Silva

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Out of necessity, I first used ChatGPT to process mentally and emotionally two major injuries. Trapped at home for the entire summer, I learned to write with ChatGPT to complete a large-scale research project. The anthropomorphizing experience left me feeling less alone. For nearly a year, news about Al-generated writing software sparked nationwide concern about the future of traditional essays. As an early adopter of most digital technologies and the type of person who welcomes chaos, I chose to learn everything | could about ChatGPT, which meant I needed to learn how to "cheat" with ChatGPT. Inspired by similar assignments …

20. Fit To Resist In Post-Product Space: Underserved Student Populations And Generative Ai's Writing Norms, John Paul Tassoni

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This essay describes ways the specter of Al altered interactions with students in a first-year composition course and how the response speaks to the broader impact of generative Al on underserved populations-especially in the sense that large language models and writing instruction can both affirm center/dominant discourses, values, and practices. The essay argues that the emergence of Al should shift writing instruction for "at-risk" and other marginalized student populations into post-product space. In such space, course work emphasizes students' negotiations with the expectations of higher education's hidden curriculum alongside the finished products that Al can now always already provide.