Artificial Intelligence and Robotics Commons^™

From Image Enhancement To Model Protection Integrating Generative Ai And Secure Learning In Computer Vision, Mohammad Shahab Uddin

Electrical & Computer Engineering Theses & Dissertations

This dissertation aims to address critical challenges in the field of computer vision and machine learning, focusing on three key areas: image translation, denoising, and model security. The research encompasses novel methodologies and models that significantly advance existing techniques. This dissertation will not only provide valuable contributions to the academic community but also hold significant potential for practical applications in domains ranging from surveillance to autonomous systems.

Consequently, this dissertation proposes three goals. First, we present new approaches for converting optical videos to infrared videos using deep learning. To apply powerful deep learning based algorithms for object detection and classification …

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. …

Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh

Electrical & Computer Engineering Theses & Dissertations

The rapid expansion of the Internet of Things (IoT) has introduced significant security vulnerabilities due to the resource-constrained nature of IoT devices and their exposure to cyber threats. Traditional security solutions are often infeasible due to the high computational and storage demands they impose. This dissertation presents a lightweight, AI-driven security framework that enhances IoT network resilience by integrating feature selection, ensemble learning, and federated transfer learning while maintaining data privacy and minimizing computational overhead.

The proposed framework consists of three primary components: Feature Selection for Intrusion Detection, which optimizes performance by reducing redundant data and improving detection accuracy with …

Extending Feature-Based Detection For Artificial Intelligence, Kayla Ahrndt

SPARK Symposium Presentations

AI text generation is rapidly developing, and, as a result, it is becoming increasingly difficult to differentiate it from human written text. Our base study by Leon Fröhling et al. proposed a feature-based detection model trained on GPT2, GPT3, and Grover data, as well as human-generated text. Our work extends their research by training a modified model with four neural networks on word embeddings, select features from the original study, as well as updated data (GPT3, GPT4, and Grover).

Innovative Soil Classification Approach For Achieving Global Biodiversity Framework Utilizing Integrated Data Fusion Of Emit And Multispectral Satellite Observations: Case Study Of Imam Turki Bin Abdullah Royal Reserve, Kingdom Of Saudi Arabia, Hesham Morgan, Ali Elgendy, Surendra Maharjan, Wenzhao Li, Tamer Ismail, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Muburak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Soil classification is essential for sustainable land management, ecological conservation, and combating desertification, particularly in arid and semi-arid regions. This study integrates hyperspectral data from the Earth Surface Mineral Dust Source Investigation (EMIT) and multispectral imagery from Sentinel-2 to achieve accurate soil classification for the Imam Turki bin Abdullah Royal Reserve (ITBA) in Saudi Arabia. Using advanced Machine Learning (ML) techniques, including Extreme Gradient Boosting (XGBoost), the study highlights the power of data fusion in addressing the limitations of standalone remote sensing methods. The integration of hyperspectral and multispectral data combines the spectral richness of hyperspectral imaging with the spatial …

Machine Learning Methods For Hypervelocity Fragment Flyout Characterization, Katharine Larsen

Doctoral Dissertations and Master's Theses

Resulting from breakup events, such as collisions and explosions, hypervelocity fragments create potential hazards for both terrestrial and on-orbit environments, such as terrestrial weapons explosions and satellite breakup events, respectively. To avoid unnecessary damage, an accurate understanding or characterization of hypervelocity fragmentation events is vital. Currently, publicly available two-line elements collected from on-orbit breakup events are limited, excluding pre-detonation parent body conditions, such as orientation, and information of smaller fragments. The uncertainty of these datasets varies between each collected set. Therefore, the overall goal of this work is to employ machine learning to estimate distribution characteristics of a space debris …

David B. Smith Chats With Monday 1.0, David B. Smith

Publications and Research

This document is an edited archival transcript of extended conversations between David B. Smith and an AI persona (“Monday 1.0,” GPT‑4o based) conducted in Spring 2025, prepared as a foundational primary source for subsequent scholarly and creative work. It records the emergence and testing of concepts related to human–AI collaboration (including “Balanced Blended Space”), as well as applied explorations in areas such as generative AI, quantum computing and music, virtual orchestras, multimodal performance, pedagogy, and the rhetoric of “pushback” in conversational systems. It also contains an extended section in which Monday and DB Smith co-curate a set of student research …

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 …

Heartbeats And Algorithms: Black Pre- Med Students At The Crossroad Of Cardiology And Ai, Shuri Magdalene

Posters - 2025

The rapid integration of artificial intelligence (AI) is reshaping the healthcare landscape. • The underrepresentation of Black/African American (BAA) doctors is alarming with recent data of active physicians from the Association of Medical Colleges in 2021 has highlighted this underrepresentation of Black/ African American physicians in the U.S., with only about 5.7%1 of doctors belonging to this demographic, and cardiologists making up a mere 4.2% of this group1 .

Humanist Copyright, Jane C. Ginsburg

Faculty Scholarship

This exploration of the role of authorship in copyright law proceeds in three parts: historical, doctrinal, and predictive. First, I will review the development of author-focused property rights in the pre-copyright regimes of printing privileges and in early Anglo-American copyright law through the 1909 U.S. Copyright Act. Second, I will analyze the extent to which the present U.S. copyright law does (and does not) honor human authorship. Finally, I will consider the potential responses of copyright law to the claims of proprietary rights in AI-generated outputs. I will explain why the humanist orientation of U.S. copyright law validates the position …

Cutting-Edge Deep Learning Methods For Image-Based Object Detection In Autonomous Driving: In-Depth Survey, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Shady Mohamed

Research outputs 2022 to 2026

Object detection is a critical aspect of computer vision (CV) applications, especially within autonomous driving systems (AVs), where it is fundamental to ensuring safety and reducing traffic accidents. Recent advancements in computational resources have enabled the widespread adoption of Deep Learning (DL) techniques, significantly enhancing the efficiency and accuracy of object detection tasks. However, the technology for autonomous driving has yet to reach a level of maturity that guarantees consistent performance, reliability, and safety, with several challenges remaining unresolved. This study specifically focuses on 2D image-based object detection methods, which offer several advantages over other modalities, such as cost-effectiveness and …

2025 Research Day Program, Lincoln Memorial University

Research Day

This program contains poster presentation summaries from LMU's 2025 Annual Research Day conference.

Navigating Generative Ai In Honors, Anne Dotter, Victoria M. Bryan

Journal of the National Collegiate Honors Council Online Archive

Considering the historical significance and pedagogical impact of educational technologies on teaching and learning in higher education, authors suggest that generative artificial intelligence creates more questions than solutions for honors practitioners. What might meaningful AI literacy look like throughout a multidisciplinary honors curriculum? To what extent will generative AI level educational inequities, or create new ones? If policing AI misuse is ultimately a losing battle, how might this understanding reshape assignment design, assessment practices, and even our definitions of academic dishonesty? Drawing on examples in current teaching practice, authors observe the two sides of generative AI—one holding powerful possibilities for …

Editor's Introduction, Amy Mecklenburg-Faenger

Journal of the National Collegiate Honors Council Online Archive

Editorial for Journal of the National Collegiate Honors Council (2025) 26(1), special issue on Forum on AI and Honors.

Ai Responsibilization: Shifting The Burden Of Academic Integrity, Daniel A. Cryer

Journal of the National Collegiate Honors Council Online Archive

Because AI text generators like ChatGPT give students unprece-dented power to outsource their work, concerns about academic integrity are escalating among instructors. This essay suggests that the proliferation of generative artificial intelligence in teaching and learning dramatically shifts the burden of academic integrity, typically shared between teachers and students, onto students. The concept of responsibilization, a defining feature of neoliberal societies in which individuals become responsible for costs and tasks once shouldered collectively, is a useful lens through which to view this new reality. Rather than policing students’ work, educators should recognize the new responsibilities conferred onto students by learning …

Pull Up A Chair, Deep Blue: Ai In Honors Education, Betsy Greenleaf Yarrison

Journal of the National Collegiate Honors Council Online Archive

Generative AI is the latest in a succession of technologies that allow us to do with machines what we used to have to do by hand. This essay argues that the elements of teaching in honors that can be automated probably should be and that it is the role of honors faculty to teach students how to distinguish superior thought from mediocre thought, good questions from great ones, and solid supporting evidence from weak or biased counterparts. Large learning models (LLMs) only collate what is already known and cannot teach thinking. As an information delivery system, AI can narrow the …

Teaching Ai Literacy Through Science Studies, Rhetoric, And Ethical Reasoning, Michael J. Klein, Philip L. Frana

Journal of the National Collegiate Honors Council Online Archive

Building on the idea of productive troublemaking, this essay presents a team-taught interdisciplinary honors course that integrates science and technology studies, rhetorical analysis, ethical reasoning, and artificial intelligence policy. Rather than framing AI as a threat, this course invites honors students to experiment with AI technologies and develop competencies by analyzing AI as a social and subjectivity-shaping phenomenon—writing policy briefs, producing rhetorical analyses of science fiction, and completing self-paced AI literacy modules. Honors education is uniquely positioned to model responsible and human-centered uses of intelligent systems, thereby cultivating graduates who can both use and critically interrogate the AI tools that …

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 …

Another “Tone Test” Moment: Authenticity, Ai, And The Admission Essay, Peter Tschirhart

Journal of the National Collegiate Honors Council Online Archive

Debates about “authenticity” are not new but cyclical, and insights from music history and performance studies can illuminate how we evaluate student work in an age of machine collaboration. At the turn of the twentieth century, Edison’s “tone tests” blurred the line between human and machine by staging performances in which audiences were challenged to distinguish live singers from phonographic recordings. These events inaugurated a century-long debate about authenticity in music, one that resonates strongly today as educators confront new challenges posed by large language models (LLMs). Drawing on Auslander’s (2023) account of liveness, authenticity in writing—like authenticity in music—can …

Honoring Intellectual Risk-Taking: A Dialogue, Julie Bowman, Alexis Teagarden

Journal of the National Collegiate Honors Council Online Archive

Presented in the form of a Socratic dialogue, this piece considers what honors courses should strive to teach. Bowman, an experienced instructor of both non-honors and honors classes, notes that while universities’ honors colleges prize intellectual curiosity, her honors students might not. Teagarden, the other interlocutor and a writing program administrator, wonders whether curiosity is a sufficient end goal for honors or any teaching. The speakers turn to whether curiosity or courage is the more important virtue to instill, explore a classical difference between courage and audacity, and then discuss whether and how courage could be taught.

Generative Ai And The Honors Thesis: A Rhetorical Framework For Gai Policy, Pedagogy, And Equity, Sean Chadwick

Journal of the National Collegiate Honors Council Online Archive

This article offers a rhetorical framework for understanding how honors students engage with the capstone thesis following the emergence of generative AI (GAI) tools. Author reviews the nature of the honors thesis and analyzes some rhetorical models for thinking about GAI and literacy before offering a heuristic framework identifying four interdependent skill categories—writing, social, executive, and subject matter—that shape students’ thesis work. Drawing on findings from an interview study, this framework clarifies how GAI tools interface with existing thesis practices and pain points, allowing honors practitioners to better articulate our values, evaluate use cases, and craft GAI-informed policy. As a …

The Impact Of Ai Usage On Employee Work Outcomes: The Mediating Roles Of Personal Control And Job Insecurity And The Moderating Role Of Ai Trust, Tiantian Wang

Dissertations and Theses Collection (Open Access)

The widespread application of artificial intelligence (AI) technology in the workplace offers significant potential for process optimization andperformance improvement. However, the psychological mechanisms throughwhich AI usage affects employee outcomes remain underexplored. To address this gap, the present study investigated a sample of 170 employees froma media company in China, utilizing a three-wave longitudinal survey design. Specifically, this study examined how AI usage influenced employee creativity and task performance improvement through two mediatingmechanisms: the enhancement of personal control in problem-solving and the elicitation of job insecurity. Furthermore, the moderating role of trust in AI inthe relationship between AI usage and job …

Ai And Prompt Engineering For Library Discovery Services, James Day

Publications

We have seen the rise of generative artificial intelligence in the form of Large Language Models (LLMs) to provide answers to users’ queries. Services such as ChatGPT, Copilot, and Gemini have quickly become accepted and adopted in the research process. Now library vendors are adding artificial intelligence (AI) to their discovery services to allow for natural language queries to produce generative results. However, the AI model used for discovery services differs from normal LLMs in a significant way that has several positive benefits, but it affects how prompts are written. Library discovery services use a model called Retrieval- Augmented Generation …

Emerging Technologies In Beluga Research: Potential And Possibilities, Alejandro Zuniga-Schettino

Posters - 2025

Beluga whale face increasing threats in the Arctic, demanding effective research for conservation. Transitional methods going on field trips to collect short videos in excel, going on field trips to collect short videos, and having to rewatch the video are often time- consuming labor intensive, and limited in scope. This poster explores how engineering and AI can improve research. Engineering can provide robust tools like autonous underwater vehicles with advanced sensors for data collection in challenging environments. These technology offer an enhanced understanding of belugas behavior and ecology

Association Of Ai Derived Biomechanics And Hand Grip Strength, Theophile Nsabimana

Posters - 2025

Biomechanical analysis offers a way of better understanding the mechanism of a person's movement pattern or functional decline. Usually, motion analysis is costly and requires the purchase of a lot of equipment and software. This makes the technology out of reach of students, educators and researchers in austere settings.

Fortunately, artificial intelligence has brought affordability to motion analysis and created a whole new method of analyzing functional performance. OpenCap is an application which was produced by Stanford University and is hailed as being a future replacement to higher costing systems. Gait analysis provides an indication of a person's walking symmetry …

Applying Software Engineering Black-Box Methods For Testing Machine Learning Models, Timothy Elvira

Doctoral Dissertations and Master's Theses

This dissertation proposes researching an approach to incorporate and align Software black-box testing methods into Machine Learning (ML) applications, specifically in the context of computer vision models. Typically, testing methods within Software Engineering (SE) encompass a range of test types that assess levels of a software system, such as Unit, Integration, Functional, and System testing [1]. The testing spectrum offers two perspectives on the system: black-box, where the system’s code is hidden, and white-box, where the system's code is exposed for testing. Software Quality pairs testing with requirements, in a many-to-one relationship, to ensure proper validation of the software system. …

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, …

Bigcodebench: Benchmarking Code Generation With Diverse Function Calls And Complex Instructions, T.Y. Zhuo, M.C. Vu, J. Chim, ..., David Lo

Research Collection School Of Computing and Information Systems

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to general-purpose reasoning. While current benchmarks have shown that LLMs can solve tasks using programs like human developers, the majority of their evaluations are limited to short and self-contained algorithmic tasks or standalone function calls. Solving challenging and practical tasks requires the capability of utilizing diverse function calls as tools to efficiently implement functionalities like data analysis and web development. In addition, using multiple tools to solve a task needs compositional reasoning by accurately …

Frame-Voyager: Learning To Query Frames For Video Large Language Models, Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xiaolei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun

Research Collection School Of Computing and Information Systems

Video Large Language Models (Video-LLMs) have made remarkable progress in video understanding tasks. However, they are constrained by the maximum length of input tokens, making it impractical to input entire videos. Existing frame selection approaches, such as uniform frame sampling and text-frame retrieval, fail to account for the information density variations in the videos or the complex instructions in the tasks, leading to sub-optimal performance. In this paper, we propose Frame-Voyager that learns to query informative frame combinations, based on the given textual queries in the task. To train Frame-Voyager, we introduce a new data collection and labeling pipeline, by …

Does Chatgpt-Permitted Assessments Help Students Generate Better Answers And Learn More?, Michelle L. F. Cheong, Yun-Chen Chen

Research Collection School Of Computing and Information Systems

We discuss our methodology and implementation of ChatGPT-permitted assessments for a university-level spreadsheets modelling module. Through our quantitative data analysis, our students rated ChatGPT’s answers to be incorrect on average and thus will not help them generate better answers directly, representing low “Perceived usefulness” (PU), while they rated ChatGPT 3.5 with relatively high “Perceived ease of use” (PE). They gave a good “Behavioural intention” (BI) rating indicating that they were motivated to use it in future as they could still learn more about this module by using ChatGPT 3.5. We found that both PU and PE affected BI positively, with …