Digital Commons Network^™

Artificial Intelligence In Health Care: Business Opportunities And Ethical Challenges, Ankita Srivastava, Marco Marabelli, Jeffrey Moriarty

Philosophy Faculty Publications

Artificial intelligence (AI), and in particular generative AI (GAI), are making incredible progress toward automation. The pervasive and invasive nature of these technologies are affecting every industry, and health care is no exception. This paper summarizes insights derived from a panel that the Hoffman Center for Business Ethics and the Center for Health and Business at Bentley University hosted in March 2024. The panel invited three qualified health care professionals: Evan Carey, Susan Persky and John Torous. The panelists are all active in multiple aspects of AI in health care but represent a focus on the key areas of policy …

Navigating Artificial Intelligence: How Traditional Midwestern Four-Year Higher Education Institution Distance Learning Programs Are Addressing Artificial Intelligence, Eric Samaritoni

Theses, Dissertations and Capstones

AI's rapid evolution and integration into society has had and will continue to influence how distance education programs teach their students profoundly. This study aimed to explore the opinions of higher education distance education Provost administrators, program managers, directors, department chairs, and other subject matter experts on the perceived impact of AI in the classroom. This study used a qualitative, phenomenological approach to examine how AI impacts students, faculty, program delivery, institutional policies, and university budgets. Semistructured interviews were conducted with 13 faculty members meeting the criteria to answer research questions based on their experience or observations. The study used …

Successfully Navigating The Disruption Ai Will Bring To Survey Research, David M. Rothschild, Trent D. Buskirk, Stephanie Eckman, D. Sunshine Hillygus, Frauke Kreuter, David Lazer

Information Technology & Decision Sciences Faculty Publications

Surveys are a core methodological tool in government, industry, and academia, providing essential data for theory development and evidence-based decision-making. As artificial intelligence continues its rapid advancement, it stands to fundamentally transform the entire survey lifecycle - from design and administration to analytics and reporting. Previous transitions to new technologies, such as telephone, internet, and non-probability surveys, led to divisions within the survey research community with real consequences for both the trajectory of research and trust in the industry. We believe the survey community should take proactive steps now to avoid similar challenges with AI integration. Specifically, our paper examines …

Demand Characterization For Real-Time Cyber-Physical Systems: Algorithms, Analysis, And Applications To Control Systems, Aaron Thomas Willcock

Wayne State University Dissertations

This work adds novel co-design, demand characterization, and utilization bounding tools to the real-time community toolbox for the effective deployment of real-time, safety-critical cyber-physical systems. Specifically, this work exploits system dynamics for improved real-time analysis in: software-based short circuit detection, intelligent power distribution systems (IPDSes), robotic arm motion, and internal combustion engines (ICEs). In short detection, inductor sub-saturation back-EMF is exploited to link circuit size and task utilization. In the IPDS, sub-maximal loading is used to bound system utilization for variable-frequency current monitoring tasks. For the robotic arm, repeated motion and error-dependent worst-case execution time are leveraged for faster schedulability …

The Influence Of Generative Artificial Intelligence On Leadership: An Exploration Of Technology Professionals' Perceptions Regarding Leadership, Adaptation, And Organizational Culture In The Digital Age, Paul Thomas Herdman

Theses, Dissertations and Capstones

The emergence of generative artificial intelligence (GenAI) has introduced new complexities for organizational leadership, requiring technology professionals to adapt in real time to evolving digital tools, strategic demands, and cultural dynamics. Although prior research has examined AI’s broad influence on business processes, few studies have explored how technology leaders experience and interpret the leadership challenges and opportunities arising from GenAI. This qualitative dissertation addressed that gap by investigating the perceptions of senior technology professionals regarding GenAI’s influence on leadership roles, competencies, decision making, and organizational culture. Using Lanigan’s (1977) phenomenological method of human science, this study explored the lived experiences …

Machine Learning-Driven Music Genre Recognition, Redeate Kidanue

All Undergraduate Theses and Capstone Projects

Music is a tool that has been integrated into society for thousands of years; it has influenced social aspects of life and has also aided in communication. Today we have various uses for music that go past our traditional uses for entertainment and self-expression. For example, music therapy has been seen to show improvements in patients with Alzheimer’s disease, depression, and PTSD. Additionally, music has played a role in political movements, demonstrating its emotional power. Social media relies heavily on the music industry as many social media posts include music either in the background, or as the forefront of posts. …

Cybersecurity And Business Analytics: Strengthening Financial And Governmental Digital Defenses, Bushra F. Malik, Ravindar Reddy Gopireddy

Accounting, Business Analytics, Economics, and Finance Department Faculty Articles

The rapid digitization of financial services and federal operations has significantly increased cybersecurity risks. Cybercriminals are continuously evolving their attack methodologies, targeting financial institutions and government agencies to exploit vulnerabilities in digital infrastructures. Business analytics has emerged as a powerful tool in combating these threats by leveraging artificial intelligence (AI), machine learning (ML), and big data analytics to detect, analyze, and prevent cyber threats in real time. This paper explores the convergence of cybersecurity and business analytics, emphasizing their combined role in strengthening threat intelligence, fraud detection, incident response, and regulatory compliance. The research provides insights into emerging security trends, …

Modeling Trust And Deception In Multi-Agent Reinforcement Learning Using The Werewolf Game, Pathikkumar Dharmeshbhai Patel

Computer Science and Engineering Theses - Archive

This thesis explores the emergence of trust, deception, and adaptive strategy in multi-agent reinforcement learning (MARL) environments using the social deduction game Werewolf as a simulation framework. In this environment, agents operate with hidden roles, incomplete information, and the need to reason about others’ intentions- mirroring the complexities of real-world social interactions. We present and evaluate two agent architectures: Agent vA, a symbolic, heuristic-based agent with probabilistic trust modeling and scalable memory structures; and Agent vB, a modular Q-learning agent that learns phase-specific policies through reinforcement. Agent vA relies on symbolic reasoning, bounded belief updates, and generalizable heuristics, while Agent …

Centrality Algorithms For Weighted Homogeneous Multilayer Networks, Ayomide Ayowole-Obi

Computer Science and Engineering Theses - Archive

Applications need to be modeled for analyses. With the availability of many alternate data Models, choosing one needs to be done carefully by considering the complexity of data to be modeled and its analyses requirements. Social networks and other newer applications are primarily relationship-oriented and also have multiple types of entities and relationships. Although simple and attributed graphs have been used historically for modeling these applications, recently, multilayer networks (or MLNs) have been shown to be more effective in preserving the semantics of the application better and further provide flexibility of analyses. However, choice of MLN as a data model …

Technology-Facilitated Abuse (Tfa): Analyzing Trends, Tactics, And Victim Responses On Reddit, Solomon G. Dandekar

Computer Science and Engineering Theses - Archive

The increasing integration of technology into daily life has provided numerous benefits but also significant risks, particularly when exploited by malicious actors in cases of technology facilitated abuse (TFA). Per- petrators can misuse technology to monitor, control, and intimidate their partners, random strangers, etc. exacerbating cycles of abuse. From location tracking and cellphone surveillance to smart device manipula- tion, spyware, and doxing, digital tools have become powerful instruments for coercion and control. This research project investigates the role of technology in stalking and harassment by analyzing discussions on a relevant subreddit where victims share their experiences, strategies for coping, and …

The Impact Of Llms Usage On Learning Outcomes For Software Development Students: A Focus On Prompt Engineering, Mohammed Owaidh Aljohani

CGU Theses & Dissertations

This study investigates the impact of large language model (LLM) usage, specifically ChatGPT, on student learning outcomes in programming education. The research adopts a mixed-methods approach, combining quantitative survey data from students and qualitative interviews with instructors. The study addresses three research questions: (1) the effect of LLM usage on undergraduate students' learning outcomes, (2) the influence of prompt engineering skills on this relationship, and (3) instructors' perceptions on these relationships. Quantitative data were collected from 159 students across two Saudi universities using a structured online survey with sections covering demographic information, LLM usage, self-reported programming understanding, and prompt engineering …

Artificial Intelligence In Health Care: Business Opportunities And Ethical Challenges, Ankita Srivastava, Marco Marabelli, Jeffrey Moriarty

Computer Information Systems Faculty Publications

Artificial intelligence (AI), and in particular generative AI (GAI), are making incredible progress toward automation. The pervasive and invasive nature of these technologies are affecting every industry, and health care is no exception. This paper summarizes insights derived from a panel that the Hoffman Center for Business Ethics and the Center for Health and Business at Bentley University hosted in March 2024. The panel invited three qualified health care professionals: Evan Carey, Susan Persky and John Torous. The panelists are all active in multiple aspects of AI in health care but represent a focus on the key areas of policy …

Generative Artificial Intelligence: Legal Ethics Issues, Kincaid Brown

Law Librarian Scholarship

Generative artificial intelligence (GenAI) is transforming nearly every sector of society including the practice of law. Legal professionals are increasingly using AI tools for research, drafting, contract review, and even predicting judicial outcomes with as many as one third of respondents to a survey using GenAI daily. But with this rapid adoption come questions that go beyond efficiency and instead point to the core of legal ethics including issues such as competence, confidentiality, and professional judgment.

Implementing Rsa Accumulators For Asynchronous And Permissionless Reliable Broadcasting, Eric Webb

CCAC Theses and Dissertations

Asynchronous consensus protocols are essential for decentralized and trustless environments such as decentralized finance (DeFi), supply chain management, and voting systems. These protocols eliminate centralized authority and timing assumptions while improving resilience and security. However, as network sizes increase the communication overhead in these systems becomes a bottleneck that limits scalability and efficiency. One notable example is the Aleph protocol, which stands out as one of the first consensus protocols to be both asynchronous and permissionless while providing Byzantine Fault Tolerance. Unlike many existing asynchronous consensus mechanisms, Aleph is permissionless in nature and does not rely on a trusted dealer …

Rotary Operations Management & Automation Platform (Romap): Modernizing Attendance Tracking And Data Submission For Rotary Clubs, Zaineel Mithani

2025 Fall Honors Capstones Projects - Archive

As Technical Lead of the Rotary Operations Management & Automation Platform (ROMAP), my Honors contribution focused on developing a Bluetooth Low Energy proximity-based attendance system enabling automatic, hands-free member check-ins. I researched and selected beacon hardware, designed RSSI-based distance calculation algorithms, and implemented platform-specific background processing for iOS and Android, achieving 97% detection accuracy. Beyond this Honors component, I architected the complete backend infrastructure including a Node.js API with 20+ endpoints, PostgreSQL database with Prisma ORM, and JWT authentication. I also developed a novel GPT-4 Vision automation system that intelligently populates web forms through computer vision, achieving 95% success rate …

Environment And Intention Awareness For Navigation And Collaboration, Bhaskar Chandra Trivedi

Computer Science and Engineering Dissertations - Archive

Unmanned Aerial Systems (UAS) have become increasingly popular as versatile platforms for tasks such as surveillance, inspection, delivery, and maintenance. In many applications, UAS operate in environments frequented by people or containing sensitive infrastructure, which introduces physical risks in case of vehicle failure, as well as psychological and privacy concerns that may limit their acceptability. Ensuring safe and efficient operation thus requires that UAS consider these risks when planning navigation strategies. While prior information, such as city maps and building layouts, can partially inform risk assessment, such data is often incomplete, necessitating real-time augmentation of risk maps using sensor information. …

Scalable, Secure, And Adaptable Perception Systems Through Adversarial Analysis And Federated Fine-Tuning, Arkajyoti Mitra

Computer Science and Engineering Dissertations - Archive

Perception systems are fundamental to intelligent machines, enabling them to sense, understand, and interpret complex environments. However, as perception increasingly underpins critical applications such as autonomous vehicles, IoT healthcare devices, and smart trading platforms, challenges related to security, scalability, and environmental understanding have become more pressing. This work addresses three core research questions: (1) How can we identify, analyze, and mitigate adversarial vulnerabilities in perception systems to ensure reliable operation under adversarial conditions? (2.1) How can AVPS models be efficiently scaled and fine-tuned across decentralized and resource-constrained environments while preserving privacy and performance? (2.2) How can we scale generative models …

Parallel Algorithms For Large Scale Dynamic Graph Analysis, Arindam Khanda

Doctoral Dissertations

A complex system of interacting entities in contemporary scenarios, be it biological, technological, or social, can be represented using graphs. Dynamic graphs, unlike their static counterparts, are ones in which the underlying topology changes over time. These networks act as a model for numerous systems, from transportation to social interactions, capturing the ever-evolving nature of real-world phenomena. However, the inherent temporality of these networks presents a unique set of challenges and the traditional static graph algorithms often fall short in efficiency and applicability. In our research, we delve into the complexities presented by large dynamic networks and suggest various methodologies …

Insights In Cybersecurity Of A Smart Campus - A Review, Mircea Ţălu

Journal of Cybersecurity Education, Research and Practice

The profound impact of the Internet of Things (IoT) on various fronts, is driven by technological advancements, the ubiquitous spread of information, and the emergence of transformative events. IoT presents a diverse array of possibilities within university environments, fostering a more connected and enhanced educational experience. This research undertakes a comprehensive review of existing literature to provide context to the IoT and underscore its crucial significance in the realm of smart campuses. Additionally, the paper explores the intricate connections between IoT and key concepts such as cybersecurity and wireless sensor networks to present a holistic perspective. It delves into the …

Future Of Bse Days 2025: Growing A Regenerative Bse, Derek M. Heeren, Santosh Pitla, Jennifer R. Keshwani, Mark Stone

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

The Future of BSE Days 2025: Growing a Regenerative BSE brought together over 150 faculty, staff, students, and partners to envision the next quarter-century of the Department of Biological Systems Engineering. The event emphasized regeneration—not only of resources and ecosystems, but also of ideas, learning models, and relationships. Across seven major sessions—three Spark Talks and four Pillar Workshops—participants explored how BSE can thrive amid technological disruption, demographic change, and societal transformation.

Key Outcomes

Redefining Impact: This session challenged participants to evolve from counting outputs to valuing relationships, collaboration, and community well-being.

Adaptive Learning Models: This discussion introduced design studios, micro-credentials, …

Consequences Of Artificial Intelligence In Health Insurance: Lawsuits, Policy, And Ethics, Alyssa N. Roberts

Honors Undergraduate Theses

In recent years, the healthcare system has been burdened by a multitude of obstacles that hinder the ability to provide effective, affordable, and timely care. Among these, one of the most significant challenges is the role that health insurance plays in shaping the quality of care. Health insurance companies are designed to decrease financial strain on patients, but they have introduced inefficiencies through delayed coverage approvals, increased denials, and administrative costs. Artificial intelligence (AI) has started to play an integral role in resolving these issues for the health insurance industry. Through its quick automated claim processing, fraud screening, and reduced …

Enhancing The Accuracy Of Image Classification For Degenerative Brain Diseases With Cnn Ensemble Models Using Mel-Spectrograms, Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim

Mathematics & Statistics Faculty Publications

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are prevalent neurodegenerative disorders among the elderly, leading to cognitive decline and motor impairments. As the population ages, the prevalence of these neurodegenerative disorders is increasing, providing motivation for active research in this area. However, most studies are conducted using brain imaging, with relatively few studies utilizing voice data. Using voice data offers advantages in accessibility compared to brain imaging analysis. This study introduces a novel ensemble-based classification model that utilizes Mel spectrograms and Convolutional Neural Networks (CNNs) to distinguish between healthy individuals (NM), AD, and PD patients. A total of 700 voice …

Perceptions Of Artificial Intelligence Use To Enhance Feedback For Preservice Teachers During Field Experiences, Betsy Schamber

Dissertations and Theses

University supervisors (USs) play a key role in providing feedback for preservice teachers (PSTs). Although artificial intelligence (AI)’s use in providing feedback in educational settings had been explored, its use for feedback for PSTs’ field experience remained unknown. The first case study herein explores PSTs’ perceptions of AI-assisted feedback for field experiences. Findings highlighted PSTs’ perceptions of AI as a catalyst for new idea generation. While AI provided a starting point, the ending output still needed to reflect PSTs’ personalities. Similarly, PSTs valued the human element of feedback, noting how USs’ lived experiences provided an added value. In K–12 classrooms, …

Relational Database Schema To Support Research Profiling Studies, Natural Language Processing, And Bibliometric Analysis, Darnelle Melvin

Library Faculty Research

In this paper, a relational database schema is introduced that supports rapid prototyping, data preprocessing, and warehousing tasks associated with research profiling studies, natural language processing, and bibliometric analysis. Python scripts are leveraged for the seamless retrieval and processing of data from Semantic Scholar. This schema is tailored to efficiently analyze entities such as authors, their scientific papers, referenced papers, and cited papers. Adhering to the relational model, this schema offers a standardized approach to data storage and detailed information retrieval for scientific papers. Enhancing knowledge discovery in scientific databases, this schema provides researchers with a powerful platform for robust …

From Code To Motion: Adventures With Wall-A Robot, Simon Sarah Mampouya-Balende

A with Honors Projects

This essay is about the author's experience working on a robot and programming, and what they learned from the project.

Artificial Intelligence In Society: Transformations And Ethical Paradigm, Yashoda Urmilla Itwaru

Selected Full-Text Master Theses 2021-

The recent advancement and adoption of AI (Artificial Intelligence) make it vital to study the effects it has on individuals and communities. Adopting AI into daily life changes interactions such as the decision-making process and task performance. AI algorithms can shape a user’s online experiences, influence their preferences, beliefs, and behavior. However, people raised concerns regarding privacy, autonomy, and manipulation. For these reasons, debates regarding the ethical aspects of AI arose.

AI provides society with more tools to complete tasks. AI can automate data intensive jobs and physical tasks. This brings a sense of job insecurity, which affects the mental …

Exploiting Artificial Intelligence And Optimization For Smart Agriculture, Jackson K. Butcher

Theses and Dissertations--Computer Science

Dynamic integration of Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) has become a vital component for unlocking the potential of smart agriculture. Currently, limitations such as limited computational resources, poor network connectivity, and rigid treatment strategies stifle optimal agricultural outcomes. This creates a challenge of leveraging the capabilities of modern artificial intelligence to combat the natural and artificial constraints of the smart agriculture environment. The primary contribution of this thesis is the development of frameworks to alleviate the overhead data and computational demand for AI within smart agriculture settings. The first framework, iCrop+, utilizes TinyML and LoRa to guarantee high-precision …

Teaching Object-Oriented Design Through Interactive Uml: A Dual-Approach Framework For Code-Based Generation And Direct Diagram Manipulation, Moses Kayuni

Masters Theses & Specialist Projects

This thesis introduces an interactive educational framework for teaching object-oriented design through UML class diagrams. The framework implements a dual-approach methodology: code-based generation, where students write Java code that automatically transforms into UML diagrams, and direct diagram manipulation, where students build diagrams by interacting with highlighted terms in problem descriptions. This approach addresses common challenges in teaching UML, including cognitive load difficulties, visualization problems, and the disconnect between code implementation and visual design. Built on the Mermaid diagramming framework, the system features a React frontend for diagram creation and manipulation, and a Flask backend that handles some code parsing and …

Teaming With Technology: Adaptive Automation In Joint Cognitive Systems For Industry 5.0, Jessica Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Adaptive automation enables dynamic reallocation of functions between people and autonomous agents to improve performance in complex work. This paper presents a meta-analysis of experimental and quasi-experimental studies (2000-2025) on joint cognitive systems in industrially relevant contexts, quantifying effects on task performance, safety/failure management, workload, trust, and learning. Across studies, adaptive automation reliably reduces operator workload and shows moderate gains in task performance and safety, with healthier trust dynamics when adaptations are triggered by human-state or event cues, made transparent to the user, and remain rapidly overridable. Risks emerge when performance-triggered switching is opaque or poorly timed, which can erode …

Comparative Evaluation Of Traditional Machine Learning And Deep Cnn Models For Static Hand Gesture Recognition, Anamol Khadka, Prit Desai

Computer Science and Engineering Student Research - Archive

Hand gesture recognition plays a vital role in facilitating natural and intuitive human-computer interaction, with applications ranging from sign language translation to touchless control systems. This study presents a comparative evaluation of traditional machine learning models and a deep convolutional neural network (CNN) for static hand gesture classification. The experimental dataset comprises 24,000 training images and 6,000 testing images, spanning 20 gesture classes. Traditional models, including k-Nearest Neighbors (KNN) and Support Vector Machines (SVM), utilize handcrafted features such as convex hull, convexity defects, and Hu moments. In contrast, the deep learning approach fine-tunes a ResNet18 architecture to learn features directly …