Digital Commons Network^™

Pulling Up Stakes: Migrating Digital Collections From Contentdm To Digital Commons, Adam C. Northam

Velma K. Waters Library Faculty Publications

No abstract provided.

Neutrosophic Model For Measuring And Evaluating The Role Of Digital Transformation In Improving Sustainable Performance Using The Balanced Scorecard In Egyptian Universities, A. A. Salama, Osama Mohamed Mobarez, Mohamed Hamed Elfar, Rafif Alhabib

Neutrosophic Systems with Applications

This paper proposes a neutrosophic model for measuring and evaluating the role of digital transformation in improving sustainable performance using the balanced scorecard in Egyptian universities. The model takes into account uncertainty, ambiguity, and incompleteness in the data. The model first calculates the neutrosophic measures of digital transformation and sustainable performance for each university. Then, it uses neutrosophic logic to evaluate the causal relationship between digital transformation and sustainable performance. The results of the analysis can used to identify the digital transformation indicators that have the greatest impact on sustainable performance. This information can then be used to develop strategies …

Satirical Deepfakes, Surreal Dreamscapes & Nostalgic Pixels: The Rapid Evolution And Cultural Commentary Of Ai-Aesthetics, Andrew Smith, James Hutson

Faculty Scholarship

The rapid evolution of visual aesthetics driven by AI, shared globally through the internet and social media, has dramatically accelerated what once took centuries to develop. This article explores the unique visual tropes emerging from AI-generated content, characterized by surreal, uncanny, and often unsettling imagery. Examples range from the Dor Brothers' stylized narrative videos to horrifying depictions of transformations, such as people morphing into motorcycles. The article contextualizes this aesthetic within historical developments in creative experimentation, drawing parallels with David Bowie's unconventional approach to sound creation in the 1970s. It also considers how AI-driven art, free from copyright constraints in …

Ai Satire And Digital Dystopia: The Dor Brothers Crafting Imperfection And Political Commentary In Contemporary Video Art, James Hutson, Andrew Smith

Faculty Scholarship

The Dor Brothers' AI-generated video content exemplifies an inflection point in digital creativity, where technological limitations are repurposed as aesthetic tools. Drawing on recent interviews with Yonatan Dor, this article explores the innovative techniques of the brothers, such as masking visual imperfections with retro filters and embracing the unpredictability of AI outputs. Through generating numerous clips and meticulously editing selections, they create a unique aesthetic that juxtaposes surrealism with a gritty realism, often reminiscent of early CCTV or VHS footage. Their work not only transcends the typical "morphing face" trope of AI videos but also engages in satire, using deepfake-like …

Enabling Emg-Based Silent Speech Transcription Through Speech-To-Text Transfer Learning, Alexander T. Garcia

Master's Theses

In recent years, advances in deep learning have allowed various forms of electrographic signals, such as electroencephalography (EEG) and electromyography (EMG), to be used as a viable form of input in artificial intelligence applications, particularly for applications in the medical field. One such topic that EMG inputs have been used is in silent speech interfaces, or devices capable of processing speech without an audio-based input. The goal of this thesis is to explore a novel method of training a machine learning model to be used for silent speech interface development: using transfer learning to leverage a pre-trained speech recognition model …

An Artificial Intelligence Report Card For Judicial Review, Zoe E. Niesel

Michigan Journal of Environmental & Administrative Law

The rapid advancement of technology, including artificial intelligence (AI), is creating new challenges for judicial review under the Administrative Procedure Act (APA). In late 2023, federal administrative agencies publicly disclosed over 700 use cases of AI that employ sophisticated techniques like machine learning and natural language processing. While the APA's flexible judicial review framework certainly allows agencies to utilize new technologies, the APA also requires explainability of agency decisions; thus, agencies must be able to articulate the reasoning and methodology behind AI-enabled decisions for the purpose of judicial review. This Article examines APA judicial review as it applies to agency …

Quantum-Enhanced Simulation-Based Optimization For Newsvendor Problems, Monit Sharma, Hoong Chuin Lau, Rudy Raymond

Research Collection School Of Computing and Information Systems

Simulation-based optimization is a widely used method to solve stochastic optimization problems. This method aims to identify an optimal solution by maximizing the expected value of the objective function. However, due to its computational complexity, the function cannot be accurately evaluated directly, hence it is estimated through simulation. Exploiting the enhanced efficiency of Quantum Amplitude Estimation (QAE) compared to classical Monte Carlo simulation, it frequently outpaces classical simulation-based optimization, resulting in notable performance enhancements in various scenarios. In this work, we make use of a quantum-enhanced algorithm for simulation-based optimization and apply it to solve a variant of the classical …

Technoculture And Language Models In Archaeology: Reconstructing And Preserving Cultural Narratives Through Digital Humanities, James Hutson

Faculty Scholarship

Technoculture, which examines the intersection of culture and technology, has increasingly permeated archaeological practice, transforming both scholarly research and public engagement [1-3]. The introduction of digital tools such as virtual reality (VR), geographic information systems (GIS), and large language models (LLMs) has democratized access to archaeological knowledge, enabling communities to engage more actively with their cultural heritage [4-6]. This short article explores the mutual influence of technocultural studies and AI technologies on archaeology, with a focus on the preservation and reconstruction of cultural narratives through digital means.

The first aspect of this intersection lies in how technocultural tools are creating …

Diabetes Technology Meeting 2023, Tiffany Tian, Rachel E Aaron, Ashley Y Dunova, Johan H Jendle, David Kerr, Eda Cengiz, Andjela Drincic, John C Pickup, Kong Y Chen, Naomi Schwartz, Douglas B Muchmore, Halis K Akturk, Carol J Levy, Signe Schmidt, Riccardo Bellazzi, Alan H B Wu, Elias K Spanakis, Bijan Najafi, James Geoffrey Chase, Jane Jeffrie Seley, David C Klonoff

Center on Aging Staff Publications

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

Developing Empathetic Ai: Exploring The Potential Of Artificial Intelligence To Understand And Simulate Family Dynamics And Cultural Identity, Emily Barnes, James Hutson

Faculty Scholarship

The rapid advancement of Artificial Intelligence (AI) has significantly impacted various domains. Yet, the exploration of AI's potential to develop a deep understanding of family culture and identity remains underexplored. This study introduces the concept of "a love of grandma and apple pie" to symbolize the potential of various AI to internalize and appreciate familial relationships, cultural traditions, and personal identity. The proposed study would investigate how an advanced deep learning model, trained on diverse unstructured datasets—including multimedia data from 100 families-could learn and reflect human-like emotions, values, and cultural understanding. Utilizing Convolutional Neural Networks (CNNs) for visual data processing …

Unraveling The Dynamics Of Stable And Curious Audiences In Web Systems, Rodrigo Alves, Antoine Ledent, Renato Assunção, Pedro Vaz-De-Melo, Marius Kloft

Research Collection School Of Computing and Information Systems

We propose the Burst-Induced Poisson Process (BPoP), a model designed to analyze time series data such as feeds or search queries. BPoP can distinguish between the slowly-varying regular activity of a stable audience and the bursty activity of a curious audience, often seen in viral threads. Our model consists of two hidden, interacting processes: a self-feeding process (SFP) that generates bursty behavior related to viral threads, and a non-homogeneous Poisson process (NHPP) with step function intensity that is influenced by the bursts from the SFP. The NHPP models the normal background behavior, driven solely by the overall popularity of the …

Probing Effects Of Contextual Bias On Number Magnitude Estimation, Xuehao Du, Ping Ji, Wei Qin, Lei Wang, Yunshi Lan

Research Collection School Of Computing and Information Systems

The semantic understanding of numbers requires association with context. However, powerful neural networks overfit spurious correlations between context and numbers in training corpus can lead to the occurrence of contextual bias, which may affect the network's accurate estimation of number magnitude when making inferences in real-world data. To investigate the resilience of current methodologies against contextual bias, we introduce a novel out-of- distribution (OOD) numerical question-answering (QA) dataset that features specific correlations between context and numbers in the training data, which are not present in the OOD test data. We evaluate the robustness of different numerical encoding and decoding methods …

Developer Reactions To Protestware In Open Source Software: The Cases Of Color.Js And Es5.Ext, Youmei Fan, Dong Wang, Supatsara Wattanakriengkrai, Hathaichanok Damrongsiri, Christoph Treude, Hideaki Hata, Raula Gaikovina Kula

Research Collection School Of Computing and Information Systems

There is growing concern about maintainers self-sabotaging their work in order to take political or economic stances, a practice referred to as “protestware”. Our objective is to understand the discourse around discussions on such an attack, how it is received by the community, and whether developers respond to the attack in a timely manner. We study two notable protestware cases i.e., colors.js and es5-ext. Results indicate that protestware discussions are spread more quickly on the GitHub platform, while security vulnerabilities are faster on social media. By establishing a taxonomy of protestware discussions, we identify posts that express stances and provide …

Putting Gpt-4o To The Sword: A Comprehensive Evaluation Of Language, Vision, Speech, And Multimodal Proficiency, Sakib Shahriar, Brady D. Lund, Nishith Reddy Mannuru, Muhammad Arbab Arshad, Kadhim Hayawi, Ravi Varma Kumar Bevara, Aashrith Mannuru, Laiba Batool

All Works

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and multimodal capabilities of GPT-4o. The study employs standardized exam questions, reasoning tasks, and translation assessments to assess the model’s language capability. Additionally, GPT-4o’s vision and speech capabilities are tested through image classification and object-recognition tasks, as well as accent classification. The multimodal evaluation assesses the model’s performance in integrating visual and linguistic data. Our findings reveal that GPT-4o demonstrates high accuracy and efficiency across multiple domains in language and reasoning …

Exploring The Potential Of Neutrosophic Topological Spaces In Computer Science, A. A. Salama, Huda E. Khalid, Ahmed K. Essa, Ahmed G. Mabrouk

Neutrosophic Systems with Applications

Neutrosophic topological spaces (NTS) offer a novel framework for uncertainty modeling by incorporating degrees of truth, indeterminacy, and falsity. This paper investigates the potential applications of NTS in computer science. We provide background on neutrosophic sets and their extension to topological spaces. We then explore how NTS could be used for uncertainty modeling in data analysis (e.g., handling noisy data in sensor networks), pattern recognition (e.g., improving image classification with imprecise features), and information retrieval (e.g., enhancing search results by considering relevance uncertainty). We discuss the challenges associated with applying NTS and highlight promising areas for future research, such as …

Advancing Affective Computing: Emotion Recognition And Tracking Across Diverse Contexts (Varied Environments), Shao Liu

Dissertations, Theses, and Capstone Projects

Affective Computing (AC) is an interdisciplinary field that recognizes, interprets, and processes human emotions. Emotions are complex, involving consciousness, physical sensations, and behavioral expressions, and are significant in various domains like mental health, human-computer interaction, and social security. Real-world applications of AC include monitoring drivers’ emotional states to improve road safety and understanding the emotions expressed by artists in visual arts. Traditional methods relying on facial expressions often fall short due to the nuanced nature of emotions, which vary across individuals, cultures, and contexts. Accurate AC systems require sophisticated, multimodal models to handle these variations and external factors like noise …

Neutrosophic Model For Measuring And Evaluating The Role Of Digital Transformation In Improving Sustainable Performance Using The Balanced Scorecard In Egyptian Universities, A. A. Salama, Osama Mohamed Mobarez, Mohamed Hamed Elfar, Rafif Alhabib

Neutrosophic Systems with Applications

This paper proposes a neutrosophic model for measuring and evaluating the role of digital transformation in improving sustainable performance using the balanced scorecard in Egyptian universities. The model takes into account uncertainty, ambiguity, and incompleteness in the data. The model first calculates the neutrosophic measures of digital transformation and sustainable performance for each university. Then, it uses neutrosophic logic to evaluate the causal relationship between digital transformation and sustainable performance. The results of the analysis can used to identify the digital transformation indicators that have the greatest impact on sustainable performance. This information can then be used to develop strategies …

Enhancing Stance Classification On Social Media Using Quantified Moral Foundations, Hong Zhang, Quoc-Nam Nguyen, Prasanta Bhattacharya, Wei Gao, Liang Ze Wong, Brandon Siyuan Loh, Joseph J. P. Simons, Jisun An

Research Collection School Of Computing and Information Systems

This study enhances stance detection on social media by incorporating deeper psychological attributes, specifically individuals’ moral foundations. These theoretically-derived dimensions aim to provide an interpretable profile of an individual’s moral concerns which, in recent work, has been linked to behaviour in a range of domains including society, politics, health, and the environment. In this paper, we investigate how moral foundation dimensions can contribute to detecting an individual’s stance on a given target. Specifically, we incorporate moral foundation features extracted from text, along with semantic features, to classify stances at both message-and user-levels using traditional machine learning and Large Language Models …

Low/No-Code And Traditional Code Integration In Digital Banking, Kim Siang Yeo, Alan @ Ali Madjelisi Megargel

Research Collection School Of Computing and Information Systems

This paper seeks to combine the merits of Low/No-Code Programming (LNCP) with Traditional Programming (TP) systems to achieve true “agility” when creating banking infrastructure. While it is easy to fall prey to Shiny Object Syndrome in today’s dynamic and fast-paced banking technology world, it is not easy to pick out the right technology for today and tomorrow’s financial industry. Instead, LNCPs allow us to hedge all bets by equally lowering the technical entry barriers for each technology. The added integration of TP, when needed, also rounds out the faults related to sole LNCP use and provides any bank with a …

Image-Guided Patient-Specific Optimization Of Catheter Placement For Convection-Enhanced Nanoparticle Delivery In Recurrent Glioblastoma, Chengyue Wu, David A Hormuth, Chase D Christenson, Ryan T Woodall, Michael R A Abdelmalik, William T Phillips, Thomas J R Hughes, Andrew J Brenner, Thomas E Yankeelov

Faculty, Staff and Student Publications

Background: Proper catheter placement for convection-enhanced delivery (CED) is required to maximize tumor coverage and minimize exposure to healthy tissue. We developed an image-based model to patient-specifically optimize the catheter placement for rhenium-186 (186Re)-nanoliposomes (RNL) delivery to treat recurrent glioblastoma (rGBM).

Methods: The model consists of the 1) fluid fields generated via catheter infusion, 2) dynamic transport of RNL, and 3) transforming RNL concentration to the SPECT signal. Patient-specific tissue geometries were assigned from pre-delivery MRIs. Model parameters were personalized with either 1) individual-based calibration with longitudinal SPECT images, or 2) population-based assignment via leave-one-out cross-validation. The concordance correlation coefficient …

A Comparison Of Four Approaches To Modeling Information Insufficiency, Pengya Ai, Sonny Rosenthal

Research Collection College of Integrative Studies

Information insufficiency, or the disparity between the level of knowledge needed to confidently judge an issue and the perceived level of current knowledge, is a key motivator of risk information seeking and processing. This study compared 4 approaches to modeling information insufficiency within the planned risk information seeking model. These approaches included the raw difference score, regression approach, partial variance score, and direct measure. Statistical modeling used data from large samples in Singapore (n = 2,124) and the United States (n = 2,125). The results of ordinary least squares regression analysis and structural equation modeling pointed to several issues. First, …

The Impact Of Data Recovery Criteria, Data Backup Schedule And Data Backup Prosses On The Efficiency Of Data Recovery Management In Data Centers, Maen T. Alrashdan, Mutaz Abdel Wahed, Emran Aljarrah, Mohammad Tubishat, Malek Alzaqebah, Nader Aljawarneh

All Works

A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale cloud data centers still have high failure rates. These mistakes can have a substantial impact on cloud service dependability and need a large resource allocation to recover from failures. Therefore, it is important to have an efficient management of data recovery to protect organizations data from loss. This paper aims to study some factors that may improve the management of data recovery by …

Health Benefits And Adverse Effects Of Kratom: A Social Media Text-Mining Approach, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Tareq Nasralah, Ahmed El Noshokaty

All Faculty Scholarship (Archived)

Background: Kratom is a substance that alters one’s mental state and is used for pain relief, mood enhancement, and opioid withdrawal, despite potential health risks. In this study, we aim to analyze the social media discourse about kratom to provide more insights about kratom’s benefits and adverse effects. Also, we aim to demonstrate how algorithmic machine learning approaches, qualitative methods, and data visualization techniques can complement each other to discern diverse reactions to kratom’s effects, thereby complementing traditional quantitative and qualitative methods. Methods: Social media data were analyzed using the latent Dirichlet allocation (LDA) algorithm, PyLDAVis, and t-distributed stochastic neighbor …

Advancing Endovascular Neurosurgery Training With Extended Reality: Opportunities And Obstacles For The Next Decade, Shray Patel, Michael Covell, Saarang Patel, Sandeep Kandregula, Sai Krishna Palepu, Avi Gajjar, Oleg Shekhtman, Georgios Sioutas, Ali Dhanaliwala, Terence Gade, Jan-Karl Burkhardt, Visish Srinivasan

SKMC Student Presentations and Publications

Background: Extended reality (XR) includes augmented reality (AR), virtual reality (VR), and mixed reality (MR). Endovascular neurosurgery is uniquely positioned to benefit from XR due to the complexity of cerebrovascular imaging. Given the different XR modalities available, as well as unclear clinical utility and technical capabilities, we clarify opportunities and obstacles for XR in training vascular neurosurgeons. Methods: A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted. Studies were critically appraised using ROBINS-I. Results: 19 studies were identified. 13 studies used VR, while 3 studies used MR, and 3 studies used AR. …

Hristudio: A Framework For Wizard-Of-Oz Experiments In Human-Robot Interaction Studies, Luiz Felipe Perrone, Sean O'Connor

Faculty Conference Papers and Presentations

Human-robot interaction (HRI) research plays a pivotal role in shaping how robots communicate and collaborate with humans. However, conducting HRI studies, particularly those employing the Wizard-of-Oz (WoZ) technique, can be challenging. WoZ user studies can have complexities in technical and methodological level that may render the results irreproducible. We propose to address these challenges with HRIStudio, a novel web-based platform designed to streamline the design, execution, and analysis of WoZ experiments. HRIStudio offers an intuitive interface for experiment creation, real-time control and monitoring during experimental runs, and comprehensive data logging and playback tools for analysis and reproducibility. By lowering technical …

Ai And Academic Integrity, Max Sparkman Research Instruction Librarian, Milne Library, Brandon West Head Of Research & Instruction, Milne Library

Artificial Intelligence, 2024-25

This short module introduces students to important concepts regarding the use of AI and academic integrity. Concepts covered include a brief overview of generative AI, whether or not their use is considered plagiarism, how to use generative AI tools responsibly, and potential use cases. The module ends with a quiz where students can apply concepts from the module to three scenarios.

Module: Ai And Value-Neutrality, Jonathan Auyer Ph.D., Department Of Philosophy

Artificial Intelligence, 2024-25

Artificial Intelligence is on the tips of everyone’s tongues these days – What exactly is it? What will can it be used for? What will it be used for in the future? What problems will it create or solve or exacerbate? This learning module aims to look at a specific facet of AI — the issue of value-neutrality — by having students look inward at capabilities necessary for human flourishing and then ask whether AI can cultivate (or inhibit) those capabilities. This will lead to a discussion of what values underlie AI and what this says about whether or not …

Chatgpt Can Write My Class Assignments, Right?: A Guided Classroom Activity For Teaching The Strengths And Weaknesses Of Generative-Ai Tools, Dr. Peter J. Kalenda Assistant Professor, Elementary Science & Math, School Of Education

Artificial Intelligence, 2024-25

This module is designed to support your undergraduate or graduate students with developing an understanding of:

• How to use generative-AI tools, like ChatGPT,
• The strengths and weaknesses of generative-AI tools for completing different tasks,
• How to design and revise a classroom presentation that is aligned with course topics and objectives by using generative-AI tools as a resource, and
• How to engage in prompt engineering and prompt revision for generative-AI tools.

Your students are being tasked with creating an engaging presentation they will deliver to their peers that aligns with the topics and learning objectives of your course. However, they will …

Creating A Business In 50 Minutes With Ai, Mark A. Rider Vanarsdale Chair In Entrepreneurship, School Of Business

Artificial Intelligence, 2024-25

This lesson plan explores using artificial intelligence (AI) to enhance the process of business idea generation and validation. Over a dynamic 50-minute workshop, students will engage with AI tools, particularly Microsoft's Copilot, to develop viable business concepts aligned with their personal interests and market needs.

The session begins with the Ikigai exercise, guiding students to identify their passions, strengths, and potential economic opportunities. Following this, students will use AI to engage in divergent thinking, generating a wide range of business ideas and refining them through iterative prompts until they find promising concepts.

In the validation phase, students will employ AI …

Using Ai In Higher Ed: Is It Cheating?, David Levy Associate Professor & Chair Of Philosophy

Artificial Intelligence, 2024-25

Students generate a course-based or college-wide policy regarding the use of Generative AI, based on assigned readings, discussion, practice using the tools on writing assignments.