Engineering Commons^™

Enhancing Art History Education With Ai: Accessibility, Engagement, And Skill Development, Analisa Soverns-Reed

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

The integration of Artificial Intelligence (AI) in the art history classroom offers transformative opportunities for students through accessibility, engagement, and skill development. This paper explores how AI can democratize access to art history education by providing cost-effective tools that eliminate traditional barriers, such as expensive textbooks, inaccessible archives, or costly field trips. AI-powered platforms like visual recognition software and adaptive learning tools enable students to engage with material more deeply, allowing for personalized learning pathways and interactive explorations of art and its contexts. Beyond content delivery, incorporating AI fosters critical digital literacy, equipping students with the skills to navigate and …

Painting With Ai: Enhancing Creativity And Understanding In The Arts Classroom, Erica Blum

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

In the context of contemporary art and design education, the rapid advancement of generative artificial intelligence has introduced profound shifts in both creative practice and pedagogical responsibility. Art and design professors now encounter students who approach AIdriven tools with a mixture of skepticism and curiosity, often perceiving such technologies as antithetical to authentic artistic development or as expedient alternatives to disciplined practice. This article articulates an instructional approach that leverages Adobe Photoshop’s generative capabilities—specifically neural filters, generative fill, and the manipulation of alpha channels— to position artificial intelligence as a collaborative, rather than substitutive, element within digital art-making. The 2025 …

Bridging Tradition And Technology: Ai As A Catalyst For Heritage Preservation And Humanities Research, Kholoud Ghaith

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

It is an empirical study examining how AI can be the driving force for cultural heritage and humanities conservation. As the AI tools that digitize, analyze, and conserve cultural resources have become in recent years, they have led to digital transformations in machine learning, digital twinning, and natural language processing. These technologies answer the industry's most challenging problems, such as the loss of historical material, access restrictions to heritage sites, and the labor-intensive nature of traditional conservation techniques. In implementing AI in heritage, institutions can document more accurately, keep records predictively, and offer more interesting public experiences via rich digital …

Writing As Curation: Empowering Authorial Agency In Ai-Assisted Composition Through Style Prompting And Quotation Glosses, Daniel Plate

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

As artificial intelligence writing tools become increasingly prevalent in educational settings, students often report feeling alienated from AI-generated content, describing it as lacking their "authentic voice." This article presents a pedagogical approach that addresses this challenge by repositioning students as curators of their authorial identities rather than passive consumers of AI-generated text. Through a dual curation methodology combining quotation glosses with style prompting, students develop multiple authorial voices for different rhetorical situations while maintaining agency over their writing process. The approach builds on classical rhetorical traditions while leveraging contemporary AI capabilities, creating a framework where students collaborate with AI tools …

Ai-Powered Storytelling And Interactive Timelines For Arts And Humanities Education, Bhavya Raoulji

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

The integration of artificial intelligence (AI) in education has opened avenues for transformative teaching and learning experiences, particularly in the arts and humanities. This submission explores the development of two AI-driven classroom tools: Chabot and interactive timelines. These tools immerse students in storytelling and historical exploration, fostering critical thinking, creativity, and interdisciplinary collaboration. The Chabot simulates conversations with historical figures or cultural narrators, providing AI-generated responses enriched with contextual details and multimedia content. The interactive timeline offers dynamic visualizations of historical events, enhanced by AI-generated summaries, audio clips, and visual aids. These tools integrate project-based learning methodologies, promoting critical thinking, …

Forward: Special Issue - Future Of Ai In Arts And Humanities Education, James Hutson

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

A link to a video of Dr. Hutson's Symposium introduction can be found below in the Additional Files section.

Gis-Based Swat Modeling For Surface Runoff Assessment To Support Urban Flood Resilience In Central Java, Indonesia, Putri Amalia Sholichah Ms., Endah Sulistyawati, Susana Paulina Dewi

Smart City

Surface runoff significantly contributes to environmental hazards such as floods in Indonesia, including in Borobudur District. Based on watershed delineation, the administrative area of Borobudur District is predominantly located within the Sileng Subwatershed. The rehabilitation zones managed by PT Adaro Indonesia are located in several specific areas within this subwatershed. This study utilizes the SWAT (Soil and Water Assessment Tool) model integrated with GIS (Geographic Information System) to simulate surface runoff quantitaively in the Sileng subwatershed, part of the Progo watershed in Central Java Province. SWAT is applied in this research to simulate surface runoff in both watershed and …

Syntax-Enhanced Boundary-Aware Named Entity Recognition Model, Chuanming Yu, Bin Deng, Zhengang Zhang

Journal of Scientific Information Research

[Purpose/significance] This study addresses the issue of inadequate perception of entity boundaries in traditional character-level modeling-based named entity recognition models by integrating syntax information containing entity boundary features into the task using a multi-head graph attention network with dense connections. This integration enhances the effectiveness of named entity recognition.

[Method/process] This study proposes a Syntax-enhanced Boundary-aware Named Entity Recognition Model (SynBNER), which utilizes BERT for text semantic representation and integrates syntax information using a dense-connected graph attention network. This integration incorporates implicit entity boundary information from syntax information into word representations, thereby enhancing the model's entity boundary perception capability.

[Result/conclusion] …

Graduate School Blog - July 2025 Volume 1, Cynthia Haynes

UofM Grad School Blog

The July 2025 UofM Graduate School Blog – Volume 1 continues the Cost of Graduate School Guide with a deep dive into hidden and variable expenses such as residency-based tuition differences, program-specific fees, and differential tuition. The blog provides practical tips for prospective students on how to ask the right financial questions when comparing programs. It also features a student spotlight on Billy Brooks, a dual MHA/MBA candidate motivated to transform healthcare access and equity. Upcoming events include a Virtual Fall 2025 Open House with Financial Aid and USBS, a Dissertation Writers Retreat, and both in-person and virtual Graduate Student …

Artificial Intelligence: The Twilight Zone And Conclusion, Sally Brown

Artificial Intelligence Exhibit

This section concludes the exhibit with an exploration of the deepfake dilemma, existential risks and societal impacts, and takeaway inquiries.

Ai Questions; "The Ai Tea", Sally Brown

Artificial Intelligence Exhibit

This section includes a series of questions related to AI and the exhibit content, as well as button designs by WVU students and Art in the Libraries committee members, a list of the exhibition sponsors, and information on the exhibition launch panel.

Navigating Perceptions: How Organizational Type And Message Source Affect Willingness To Fly In Automated Air Taxis, Cody James Sweatt

Doctoral Dissertations and Master's Theses

A new era of transportation and business is beginning to emerge. Advanced air mobility (AAM), which uses highly automated aircraft that transport passengers and cargo in the underutilized, low-altitude airspace above and around urban areas, is rapidly becoming a reality (FAA, 2023). These new companies will utilize air taxis, which are automated, electric, vertical takeoff and landing (eVTOL) aircraft and will potentially foster a revolutionary new commerce infrastructure. Unfortunately, it is not currently understood how the credibility of a message source or specific type of organization that owns and operates an automated air taxi company influences a customer’s willingness to …

The Dynamics Of Word-Of-Mouth Marketing: An Agent-Based Modeling Approach To Message Credibility And Consumer Engagement, Ali Nasirzonouzi, Carlos Gershenson

Northeast Journal of Complex Systems (NEJCS)

Word-of-mouth (WOM) marketing is a critical factor in the dissemination of information and adoption of products in social networks. This paper investigates the impact of two important factors message credibility and consumer engagement on WOM adoption dynamics using agent-based modeling (ABM). This study proposes a simple qualitative model to investigate how these factors influence adoption rates through both broadcast communication and peer-to-peer influence by simulating interactions on a spatially clustered network.

The findings show that increased message credibility significantly boosts adoption, achieving a balance between broadcast and social mechanisms. Also, consumer engagement primarily affects the adoption mechanism, shifting the effect …

Acceptability Of The Proposed Congestion Charging System In The Central Business District Of Baguio City, Philippines, Ericka Renee A. Lanigt, Sandra S. Samantela, Ma. Catriona E. Devanadera, Casper Boongaling Agaton

CSID Journal of Infrastructure Development

The City Government of Baguio is proposing a congestion charging system in the Central Business District (CBD) to address the ongoing issue of traffic congestion in the city. Although it is an effective tool, low public acceptability hinders its implementation. This study aims to assess Baguio City residents' acceptability regarding the CBD's congestion charging system. Specifically, it seeks to (1) identify the factors that influence residents’ acceptability of the proposed system, (2) evaluate whether there is a significant difference in acceptability across different road users (private vehicles, public transportation, cycling, and walking), and (3) provide recommendations for transportation policy planning …

Director, Military Cyber Institute, Joseph Schafer

Military Cyber Affairs

No abstract provided.

Throughput Of Ascon Compared With Popular Iot Encryption Algorithms, Mitchel R. Harvey (Ryan), Andrew M. Kaiser, Garrett W. Hoiness

Military Cyber Affairs

No abstract provided.

Anomaly Detection Of Network Layer Attacks Against Cyber Physical Systems Using Machine Learning And Deep Learning Techniques, James Alger, Michael Tu

Military Cyber Affairs

This research paper presents the analysis of using machine learning and deep learning algorithms on detecting anomalous network traffic in Cyber-Physical Systems (CPS). Using a real PLC CPS-based system, normal and anomalous network traffic will be captured using Wireshark. The research analyzes a DDoS attack. The focus of the research is to identify the most effective feature combinations and evaluate them on ML and DL models. The emphasis is on enhancing detection strategies rather than exploiting device vulnerabilities. The detection of network attacks often involves handling a vast array of high-level features. Previous studies (Li & Chasaki, 2022) apply machine …

Characterizing Caldera’S Cyber Attack Emulation Capabilities, Caleb Chang, Matthew Cao, Kenyou Teoh, Ekzhin Ear, Shouhuai Xu

Military Cyber Affairs

Autonomous cyber attack emulation can aid cyber defenders to identify and remediate cyber risks. MITRE’s Caldera software is the state-of-the-practice for automated attack emulation. Yet, it has not been systematically analyzed, putting its performance and effectiveness into question. This paper systematically characterizes Caldera’s architecture, abilities and use cases, and assesses its strengths and weaknesses. It draws useful insights, such as: Caldera excels in stealthy access and execution tactics to pilfer data against Windows operating systems. It also discusses two directions for Caldera improvement: module-level automation and end-to-end attack emulation.

The Digital Battlefield: Safeguarding Military Drones Against Cyberattacks, Jason Ashong, Arun Venkitanarayanan, Benjamin Yankson

Military Cyber Affairs

The Internet of Battlefield Things (IoBT) is an advanced network of interconnected devices that significantly enhance military operations through real-time data exchange and situational awareness. While IoBT offers tactical advantages like improved surveillance, reconnaissance, and operational effectiveness, it also introduces substantial cybersecurity risks. Adversaries can exploit vulnerabilities within these networks, potentially compromising mission integrity and national security. This research examines the cybersecurity measures of commercial drone controllers and their correlation with military devices. It aims to enhance future vulnerability assessments with advanced tools and approaches to better secure critical military operations. The study highlights the need for robust security architectures …

Using Blockchain Technology To Help Secure America's Defense Critical Infrastructure, Vimal Buck, Aerin Krebs, Brynn Hillard, Jakob Gerha, Joseph Lutma, Srikar Maduposu, Ted Allen

Military Cyber Affairs

Critical water infrastructure in the United States faces increasing cybersecurity threats from state-sponsored actors, with potentially devastating consequences for national security, economic stability, and public health. (Cybersecurity and Infrastructure Security Agency, 2025). This infrastructure supports defense critical assets and is actively being targeted by various state-sponsored hacking groups, which poses a major concern for civilians and military alike. K. Herath (personal communication, February 24, 2025) reported being aware of two attacks on Ohio water systems during his tenure as Cybersecurity Strategic Advisor to Ohio Governor Mike DeWine.

Water is essential to everyday life and defense and presents as a high-value …

Network And Multipath Traceroute Visualization, Cameron Makowski

Military Cyber Affairs

TraceCam introduces a new paradigm in network path analysis, leveraging GPU-accelerated WebGL visualization, advanced traceroute integrations, and AI-driven insights to transform complex routing data into actionable intelligence. Early prototypes have demonstrated significant improvements in performance, clarity, and multi-path discovery, overcoming traditional limitations in traceroute analysis. By incorporating retrieval-augmented language models and enriched metadata sources like IPinfo.io, TraceCam enables automated anomaly detection, contextual explanations, and rapid root-cause analysis, enhancing operational efficiency. The platform’s architecture ensures scalability and adaptability, supporting deeper investigations and real-time situational awareness. Future development will focus on clustering-based anomaly detection, expanded geographic visualizations, and enhanced AI-generated analysis to …

Quantifying Adversary Military Forces’ Susceptibility To Cognitive Attacks, Bonnie Rushing, Cole Nelson, Shouhuai Xu, Christofer “Raven” O’Keefe, Olga Karpoyan

Military Cyber Affairs

This paper introduces a method to quantify international populations’ susceptibility to cyber cognitive attacks using press freedom and media trust metrics. We present the Cognitive Influence Calculator, a tool that estimates susceptibility (𝑆) based on Press Freedom Scores (PFS) and media trust levels. Findings show that while authoritarian regimes are harder to reach, successful cognitive attacks have greater impacts due to higher trust in state-controlled narratives. Using U.S. wargaming data and international trust metrics, we compute susceptibility scores for the U.S., Russia, China, Iran, and North Korea. Results show an inverse relationship between PFS and media susceptibility, with local/allied …

Forward, Amy Hamilton

Military Cyber Affairs

No abstract provided.

Understanding Russia’S Cyber Policies, Strategies, And Doctrines, Bryan Hancock, Hanh Nguyen, Olga Karpoyan, Ekzhin Ear, Shouhuai Xu

Military Cyber Affairs

This study analyzes the strengths and weaknesses of Russia’s cyber policies, strategies, and doctrines through a systematic set of attributes, leading to key insights: (i) Russia has proactively adapted its cyber policies, strategies, and doctrines to its evolving environment; (ii) Russia actively conducts cognitive warfare, but remains equally vulnerable to it; and (iii) Russia’s cyber posture faces significant challenges, including a limited technological base, shortage of skilled personnel, and restrictive approach to information control, all of which undermine the effectiveness of its strategies. These insights offer valuable implications for US Cyber Command and the Department of Defense.

Characterizing Cyberattacks Against Operational Technology Infrastructures Through The Lens Of Attack Flows, Sherman Kettner, Caleb Chang, Ekzhin Ear, Shouhuai Xu

Military Cyber Affairs

Operational Technology (OT) infrastructures play a critical role in modern society and economy. However, their increasing connectivity with public networks such as the Internet has made them vulnerable to cyberattacks, much like traditional Information Technology (IT) systems. In particular, cyberattacks against OT infrastructures remain relatively underexplored and little understood. In this paper, we aim to deepen our understanding of cyberattacks against OT infrastructures. For this purpose, we propose a methodology, including novel cybersecurity metrics to analyze the attack flows of these attacks in an end-to-end fashion, which allows us to draw useful insights. We demonstrate the utility of the methodology …

The Evolution Of Global Gold And Copper Trade Networks, Oleksandr Hulianskyi

Northeast Journal of Complex Systems (NEJCS)

Gold and copper have emerged as two of the most vital commodities in global trade. Despite serving distinct purposes, their international trade networks reveal interconnected patterns, critical to understanding the dynamics of global economics. This paper studies these attributes and their evolution during the last 36 years for both metals and finds correlations between them. The first part of the research is focused on the sustainability of networks through efficiency and robustness indexes; the second part is dedicated to interconnectedness – the Louvain and Bayesian SBM algorithms, partition, and modularity instruments are used. Community detection algorithms provide valuable insights into …

Exploring The Potential Of Large Language Models (Llms) To Simulate Social Group Dynamics: A Case Study Using The Board Game "Secret Hitler", Kaj Hansteen Izora, Christof Teuscher

Northeast Journal of Complex Systems (NEJCS)

This study explores the capacity of large language model-powered agents to simulate human-like behavior in multi-agent social systems. Using Secret Hitler — a hidden-role board game centered on trust, deception, and strategic communication — we evaluate how LLM agents navigate dynamic group interactions. Our findings show that agents exhibit human-like behaviors, including strategic temporal adaptation, contextual reasoning, and complex social cognition such as theory of mind and implicit coordination. Notably, 85% of agent decisions factored in at least two other players’ mental states, highlighting their capacity for multi-agent mental state inference. However, they struggled with key aspects of human gameplay, …

Harnessing Generative Ai And Large Language Models For Revolutionizing Cybersecurity In The Internet Of Things: Ethical And Privacy Implications, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

Generative artificial intelligence (AI) and large language models (LLMs) have in- troduced transformative capabilities in cybersecurity, particularly in securing Internet of Things (IoT) environments. These technologies can synthesize vast datasets, support real-time anomaly detection, and generate predictive insights through simple prompts. However, their deployment also presents ethical and privacy-related concerns, including algorithmic bias, data leakage, and misuse for malicious content creation. This paper conducts a systematic literature review to evaluate how LLMs and generative AI contribute to IoT cybersecurity. We propose an ethical AI-IoT security framework, examine key challenges, and offer recommendations for integrating responsible AI governance. We aim to …

Board # 271: Nsf Iuse 2315777: Training Engineering Students To Be Better Learners: A Course-Integrated Approach, Huihui Qi, C. Pilegard, Minju Kim, Saharnaz Baghdadchi, Curt Schurgers, Alex M. Phan, Marko Lubarda

Psychology Faculty Articles and Research

Learning is a lifelong process exercised within and beyond the classroom, and a vital skill in almost all technical professions. Engineers, in particular, are impacted by rapidly evolving technologies and practices that require continuous learning and adaptation long after their training and the initial transition into their professional careers. However, despite the critical role of learning in their academic success and profession, engineering students experience academically rigorous and challenging courses with minimal emphasis or conscious focus on learning strategies that power effective learning. Often-used learning strategies such as rereading, highlighting, repetition, and memorization are intuitive for many students, yet do …

Leveraging Genai For Biometric Voice Print Authentication, Erica Brooks, Lijo Jacob, Lani Lewis, Gaurav Mittal, Shivam Negi, Faizan Javed

SMU Data Science Review

This paper presents the development of a secure voice authentication system that delivers an inclusive solution for all users, including those with disabilities. Leveraging a Text-Dependent Active Verification process, the system combines a spoken passphrase with voice biometric coefficients and audio vector embeddings for reliable user verification. A vector database is used to efficiently store data and perform similarity retrieval. Initially, the system achieves a 71% spoof detection accuracy, ensuring that only genuine samples proceed to the embedding stage, where it attains a 55.21% accuracy in vector embedding and similarity retrieval. Furthermore, this approach paves the way for user-specific voice-controlled …