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Articles 1 - 30 of 173
Full-Text Articles in Computer Engineering
Saas As The Backbone Of Digital Transformation: How Ai Turned Cloud Software Into Intelligent Enterprise Infrastructure, Amar Fejzić
Communications of the IIMA
Software-as-a-Service (SaaS) has become one of the most consequential infrastructures of digital transformation because it lowers the cost, time, and complexity of adopting enterprise capabilities. At the same time, artificial intelligence (AI), especially generative and conversational AI, is changing SaaS from a delivery model into an intelligent operating layer that automates workflows, personalizes customer interactions, and supports data-driven decisions. This paper develops a conceptual synthesis of academic literature and public organizational cases to examine how SaaS shaped digital transformation and how AI is reshaping SaaS itself. The analysis shows that SaaS enables scalable experimentation, faster deployment, and modular integration, while …
The Self-Aware Room: A Framework For Operational Self-Awareness In Evolvable Blended Environments, David B. Smith
The Self-Aware Room: A Framework For Operational Self-Awareness In Evolvable Blended Environments, David B. Smith
Publications and Research
The Self-Aware Room (SAR) is a room-scale research environment developed within the larger Balanced Blended Space and Blended Reality Performance System research trajectory. Rather than treating the room as a conventional “smart” environment composed of fixed automation technologies, SAR approaches it as an evolvable blended environment made from physical, virtual, conceptual, sensory, computational, and performative relationships. Its defining feature is not any particular sensor, model, or output device, but the set of transformations through which physical activity becomes structured observation, bounded representation, interpreted state, governed decision, and mediated response.
This paper develops the conceptual and methodological foundations of SAR as …
Ai Cyber First Responders: Bottleneck Analysis Of Heterogeneous Cpu–Gpu Pipelines For Security Operations Center Triage, Christine Pierce
Ai Cyber First Responders: Bottleneck Analysis Of Heterogeneous Cpu–Gpu Pipelines For Security Operations Center Triage, Christine Pierce
Harrisburg University Other Works
Abstract — Modern Security Operations Centers (SOCs) must continuously process massive volumes of heterogeneous security telemetry while meeting stringent throughput, latency, and operational continuity requirements. Although transformer-based artificial intelligence has significantly improved threat detection and alert prioritization, most cybersecurity research evaluates model accuracy rather than the end-to-end behavior of AI-enabled operational pipelines. Consequently, relatively little is known about how heterogeneous CPU–GPU coordination, scheduling overhead, memory movement, and synchronization collectively influence operational SOC performance. This paper presents the AI Cyber First Responder, a heterogeneous SOC triage architecture that integrates GPU-accelerated transformer inference with CPU-based doctrine-driven reasoning to investigate end-to-end pipeline behavior …
Case Study: Feasibility Of Creating A Simulated Mobile Data Center For Cross-Disciplinary Academic Programs, Stanley Mierzwa, Christoper J. Schultz, Iassen Christov, Michael Fagioli, Thomas Ikeda, Reinaldo Jaramillo, Giolian Sanagustin
Case Study: Feasibility Of Creating A Simulated Mobile Data Center For Cross-Disciplinary Academic Programs, Stanley Mierzwa, Christoper J. Schultz, Iassen Christov, Michael Fagioli, Thomas Ikeda, Reinaldo Jaramillo, Giolian Sanagustin
Center for Cybersecurity
This case study examines the potential to envision, create, and deploy a simulated mobile micro data center solution that can be easily replicated and transported between locations and educational settings. The coined term for this solution is the Mobile AI-Centered Data Center (Mobile ACDC), which provides students with a platform to construct, in a hands-on fashion, such a solution and navigate the product to gain greater competencies and understanding of the components found in a data center. Instructor and student feedback assessments from the pilot classroom modules and laboratory experiential learning activities indicate that such a solution helps to improve …
An Intelligent System For Managing High-Priority Vehicle Routing In Smart Cities Using Artificial Intelligence And Spatial Data Analytics, Bahjat Abdulelah Madhloom
An Intelligent System For Managing High-Priority Vehicle Routing In Smart Cities Using Artificial Intelligence And Spatial Data Analytics, Bahjat Abdulelah Madhloom
Al-Esraa University College Journal for Engineering Sciences
In developing metropolises, there is a risk to public safety in addition to the usual traffic jams. Traffic delays can have life-altering effects every second that fire trucks and ambulances are delayed. Large cities like Baghdad, which suffer from haphazard road sealing and incompetent traffic management, are especially affected, creating daily emergency crisis problems. We create a new intelligent routing system for these top priority vehicles in order to solve this life-or-death problem. Our method uses a trained model with real-time spatial information instead of outdated static maps. A Long Short-Term Memory (LSTM) neural network at its core constantly forecasts …
Integrating Sustainability Into Engineering Education, Riley R. Moller
Integrating Sustainability Into Engineering Education, Riley R. Moller
Master's Theses
Engineering decisions shape lasting technology that affects environmental integrity, public safety, economic stability, and social equity. As global challenges such as climate change, infrastructure vulnerability, and rapid technological advancement intensify, the responsibilities placed on engineers continue to expand. Sustainability provides a framework for addressing these interconnected pressures through systems-based design and long-term thinking. Yet, sustainability education within engineering programs remains unevenly integrated, often positioned as elective or peripheral rather than as a foundational component of professional preparation.
Prior research shows that sustainability is most frequently addressed through stand-alone courses rather than embedded across required curricula, reflecting disciplinary structures that prioritize …
Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen
Honors College Theses
This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …
Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy
Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy
Turkish Journal of Electrical Engineering and Computer Sciences
This research proposes an end-to-end procedure for arrhythmia detection based on electrocardiogram (ECG) signals using complex-valued convolutional neural network (CVCNN) incorporated with time-frequency representation. The proposed model leverages complex numbers to capture amplitude and phase information that enhances the ability of the model for detecting time-frequency variation in cardiac signals. First, signal preprocessing techniques---including normalization, wavelet denoising, and R-peak detection---are applied. Subsequently, the model extracts complex features from raw ECG data by employing the Hilbert transform to derive the analytic signal and the short-time Fourier transform (STFT) to generate a time–frequency representation. The proposed CVCNN framework effectively learns spatial-temporal features …
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Publications
As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …
The Developing Role Of Ai In Modern Engineering Research, Rianna Pais
The Developing Role Of Ai In Modern Engineering Research, Rianna Pais
The Cardinal Edge
No abstract provided.
Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification, Keita Sakurai
Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification, Keita Sakurai
Master's Theses or Doctor of Nursing Practice
Accurate classification of blood cell types is a critical task in automated hematological analysis. This study presents a comparative evaluation of three deep learning architectures, ResNet18, MiniVGG, and YOLOv8, for five-class blood cell image classification. To ensure a fair comparison, all models were trained under standardized conditions, including a consistent 90:10 training–validation split, controlled dataset size, and fixed training epochs. ResNet18 was trained to establish a baseline using residual learning. MiniVGG employed a compact VGG-inspired design with regularization to balance efficiency and accuracy, while YOLOv8 leveraged a lightweight, pretrained classification backbone with integrated data augmentation. Experimental results demonstrate a clear …
Artificial Intelligence In Cybersecurity: Applications, Threats, And Implications, Brandon A. Rodriguez
Artificial Intelligence In Cybersecurity: Applications, Threats, And Implications, Brandon A. Rodriguez
Honors Undergraduate Theses
The point of this thesis is to analyze the growth of artificial intelligence in the world of cyber security, highlighting the specific impacts it has in the use of defense and offensive misuse. The way that this research was done was by using three main methods, those being interviewing cybersecurity specialists, testing the uses of public AI models and by reviewing peer-reviewed studies. Some of the findings that were discovered with the research were that AI can be a great asset in supporting defensive systems with such things as assisting in the creation of scripts, but there are also negatives …
Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber
Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber
Al-Esraa University College Journal for Engineering Sciences
Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …
Trustworthy Ai: Prohibited Practices, Ethical Principles, And The Identification Of Problems, Anna Karmańska
Trustworthy Ai: Prohibited Practices, Ethical Principles, And The Identification Of Problems, Anna Karmańska
Journal of Global Awareness
The following considerations arise from the study of texts of documents of a legal nature and from the author’s judgments. They do not present the results of the author’s own empirical research; however, they constitute a factual study that is important for their undertaking in the next step. Having given concern but also hopes for AI, the author focuses her attention on issues that, not only in her opinion, have a strong bearing on the preservation of humanity in a digital environment and at the same time with technocratic features. These issues (prohibited practices, high-risk systems, and ethics) related to …
The Role Of Artificial Intelligence In Reducing Internet Crimes Against Children, Malyssa Shaw
The Role Of Artificial Intelligence In Reducing Internet Crimes Against Children, Malyssa Shaw
Student Scholar Symposium Abstracts and Posters
When generative artificial intelligence (AI) first surfaced and broke into the public sphere, my immediate concern was in its development, implementation, and harmful applications. I was not surprised when deepfake technology rapidly advanced alongside these new developments and impacted women and children worldwide. Disproportionately, they have been made victims of intimate media forgery as early as the 1990s, with an unprecedented uptick in recent years as a direct result of these developments. In response, I wrote "Deepfake, Real Harm: Protecting Children in the Age of AI", analyzing data specifically regarding child sexual abuse material (CSAM) created with artificial intelligence while …
Artificial Intelligence In Higher Education: Opportunities And Challenges, Maytha Al-Ali, Adam Marks, Jasur Umirzokov, Noura Metawa
Artificial Intelligence In Higher Education: Opportunities And Challenges, Maytha Al-Ali, Adam Marks, Jasur Umirzokov, Noura Metawa
Iraqi Journal for Computer Science and Mathematics
While AI is often presented as a panacea for the challenges facing higher education, there is limited empirical evidence supporting its effectiveness in improving student learning and institutional performance. This gap between expectation and reality emphasizes the need for rigorous research, realistic goal-setting, and careful planning to ensure that AI technologies deliver on their promises in higher education. This study contrasts the potential utilization of AI technologies in Higher Education from the literature, against actual utilization in universities. The study also investigates the key barriers of AI implementation in higher education. This study uses a mixed-research methods approach, including case …
The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden
The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden
Milne Open Textbooks
Artificial Intelligence (AI) is no longer a futuristic concept—it is the reality of the present. From the algorithms shaping our social media feeds to the generative tools transforming our workplaces, AI has permeated every aspect of modern life. The Future is Now moves beyond the hype to provide a comprehensive roadmap for understanding, navigating, and shaping this technological revolution.
Demystifying the Machine
This textbook serves as a user-friendly guide to the “black box” of AI. It breaks down complex technical concepts—from machine learning and neural networks to large language models—making them accessible to students across all disciplines. By establishing a …
Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng
Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng
Journal of System Simulation
Abstract: Digital testing and evaluation (DTE) represents a novel paradigm in the evolution of testing and evaluation methodologies within the digital era. It is achieved through the integration of multiple digital theories and technologies to conduct testing and evaluations in the digital domain. This paper analyzed the characteristics of test objects across different historical periods, reviewed the core features of testing and evaluation techniques in each stage, and unveiled the paradigm shifts within the testing and evaluation technology system. Building upon this foundation, it explored the new demands placed on testing by test objects in the information age, clarifying the …
Depaul Digest
DePaul Magazine
College of Communication faculty Matthew Ragas and Ron Culp mentor students on gaining access to executive-level administration. News briefs on exciting developments at DePaul University’s 10 colleges and schools, from nursing students studying public health protocols in Prague to a new DePaul-hosted conference exploring AI in filmmaking. DePaul alumni volunteers share their experiences spreading the Vincentian mission nationwide.
Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala
Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala
School of Computing: Dissertations, Theses, and Student Research
Multi-agent systems (MAS) possess significant potential for modeling real-world scenarios requiring coordinated actions (like wildfire fighting or ridesharing) among autonomous entities or agents (e.g., wildfire fighting agents) in complex, dynamic environments. Effective decision-theoretic planning (where each agent must carefully consider both the immediate and the future situations or states, and coordinate with the other agents (neighbors) to evaluate what needs to be done at present) within MAS, especially multiagent planning, where the planning agent directly models its neighbors in order to estimate their optimal actions, is critical, yet challenged by factors like partial observability, openness, and diverse agent types with …
Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang
Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang
Journal of System Simulation
Abstract: With the rapid advancement of artificial intelligence and computing technologies, simulation technologies have leapfrogged, propelling the discipline of simulation toward greater maturity. Research progress in computer simulation technologies both in China and abroad was reviewed, and the definition and connotation of simulation were clarified. It was proposed that the Chinese terms "仿真" "仿效"and " 模拟" be unified under a single term " 仿真" with corresponding "Simulation" "Emulation" and "Analog" in English translated uniformly as "Simulation". Simulation science and engineering discipline was delineated, which was grounded in three core theoretical foundations: analogical theory,computational theory, and model validation theory. The first-level …
Analysis Of Vision Transformers And Domain Adaptation In Long-Range Facial Recognition, Zachary Michael Swanson
Analysis Of Vision Transformers And Domain Adaptation In Long-Range Facial Recognition, Zachary Michael Swanson
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Atmospheric turbulence presents a significant barrier to long-range facial recognition, introducing severe geometric distortions and blur that degrade image quality. This thesis investigates deep learning approaches for mitigating these effects, with a focus on transformer based architectures and domain adaptation strategies.
An in-depth benchmarking study was performed using convolutional neural networks (CNNs) and vision transformers (ViTs) on the Husker BRIAR Research Collection from up to 500m (HBRC-500) face dataset. The results demonstrated that vision transformers, particularly hierarchical vision transformers like the shifted-window (Swin) transformer, outperform CNN-based models at long distances due to their ability to model global spatial relationships and …
Artificial Intelligence In Everyday Life, Sally Brown
Artificial Intelligence In Everyday Life, Sally Brown
Artificial Intelligence Exhibit
This section explores using AI in everyday life including decision making.
Artificial Intelligence: The Twilight Zone And Conclusion, Sally Brown
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
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.
Artificial Intelligence Introduction Section, Seth Newell, Sally Brown
Artificial Intelligence Introduction Section, Seth Newell, Sally Brown
Artificial Intelligence Exhibit
The introduction gives an overview of the exhibition, along with an explanation of AI literacy, AI vs. Google, and a basic AI timeline.
Selected Artificial Intelligence Provisions In U.S. Fiscal Year 2025 National Defense Authorization Act, Bert Chapman
Selected Artificial Intelligence Provisions In U.S. Fiscal Year 2025 National Defense Authorization Act, Bert Chapman
Libraries Faculty and Staff Presentations
The 2025 Fiscal Year National Defense Authorization Act contains multiple provisions relating to artificial intelligence (AI). These congressionally mandated provisions direct various sections of the Department of Defense (DOD) and individual U.S. armed service branches to execute congressional intent for AI policymaking. Examples of such intent include identifying and planning DOD's AI workforce, demonstrating AI biotechnology applications for national security, improving the human usability of AI systems, and establishing an AI security center. This presentation will note that reports on these initiatives must be prepared for relevant congressional oversight committees, and, in many cases, are in many cases, publicly released …
Navigating Human-Robotic Interaction Challenges In Teaching-By-Demonstration, Shakra Mehak
Navigating Human-Robotic Interaction Challenges In Teaching-By-Demonstration, Shakra Mehak
Doctoral
The advancement in interdisciplinary research domains, like robotics and HRI, presents a challenging task. It is an exception rather than the norm for research to extend beyond the boundaries of individual disciplines and encompass the challenges presented by other fields of study. This project is part of ”Collaborative Intelligence for Safety Critical Systems” (CISC), which is a Marie Curie Training Network funded by the European Commission to hire and train researchers with the expertise and skillset necessary to carry out the major tasks required to develop a Collaborative Intelligence system. The program encompasses four overarching themes: Artificial Intelligence (AI), Human …
Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi
Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi
Al-Esraa University College Journal for Engineering Sciences
The spread of wireless networks has led to an increase in serious cyber attacks due to their weak architecture. This article focuses on reevaluating cybersecurity in wireless network technology by integrating statistical information detection methods and artificial intelligence (AI) algorithms. To construct a wireless networking scenario that accurately reflects real-life conditions, we created a data fabrication that included four pre-existing anomalies as well as four newly introduced anomalies. The synthetic dataset created from these generation processes contains 20 thousand distinguishable values, which are later divided into training and validation sets. Using the strategy described before, we began to analyze the …
Enhancing Bedside Nursing Care: An Artificial Neural Network Approach To Predicting Cardiac Arrest In Hospitalized Adults, Katharine Czech, Alec Pannunzio, Maddie Anderson, Numair Khan, Jacob Lacanienta, Jonghyeok Lee, Aneesh Poddutur, Emily Rastovski, Kira Voelker, Julie Wasyliw, Sei Zou
Enhancing Bedside Nursing Care: An Artificial Neural Network Approach To Predicting Cardiac Arrest In Hospitalized Adults, Katharine Czech, Alec Pannunzio, Maddie Anderson, Numair Khan, Jacob Lacanienta, Jonghyeok Lee, Aneesh Poddutur, Emily Rastovski, Kira Voelker, Julie Wasyliw, Sei Zou
The Journal of Purdue Undergraduate Research
No abstract provided.