Preface: Special Issue On Nlp Approaches To Offensive Content Online,
2023
George Mason University
Preface: Special Issue On Nlp Approaches To Offensive Content Online, Marcos Zampieri, Isabelle Augenstein, Siddharth Krishnan, Joshua Melton, Preslav Nakov
Natural Language Processing Faculty Publications
No abstract provided.
Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration,
2023
Harvard University
Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Disease Informed Neural Network And Mathematical Modeling Of Covid-19 With Human Intervention,
2023
Inter American University of Puerto Rico-San German
Disease Informed Neural Network And Mathematical Modeling Of Covid-19 With Human Intervention, Jeremis Morales-Morales, Alonso Gabriel Ogueda, Carmen Caiseda, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Smart Street Light Control: A Review On Methods, Innovations, And Extended Applications,
2023
École Nationale Supérieure d’Electricité et de Mécanique
Smart Street Light Control: A Review On Methods, Innovations, And Extended Applications, Fouad Agramelal, Mohamed Sadik, Youssef Moubarak, Saad Abouzahir
Computer Vision Faculty Publications
As urbanization increases, streetlights have become significant consumers of electrical power, making it imperative to develop effective control methods for sustainability. This paper offers a comprehensive review on control methods of smart streetlight systems, setting itself apart by introducing a novel light scheme framework that provides a structured classification of various light control patterns, thus filling an existing gap in the literature. Unlike previous studies, this work dives into the technical specifics of individual research papers and methodologies, ranging from basic to advanced control methods like computer vision and deep learning, while also assessing the energy consumption associated with each …
Limitations And Possibilities Of Digital Restoration Techniques Using Generative Ai Tools: Reconstituting Antoine François Callet’S Achilles Dragging Hector’S Body Past The Walls Of Troy,
2023
The University of Alabama in Huntsville
Limitations And Possibilities Of Digital Restoration Techniques Using Generative Ai Tools: Reconstituting Antoine François Callet’S Achilles Dragging Hector’S Body Past The Walls Of Troy, Charles O'Brien, James Hutson, Trent Olsen, Jay Ratican
Faculty Scholarship
Digital restoration offers new avenues for conserving historical artworks, yet presents unique challenges. This research delves into the balance between traditional restoration methods and the use of generative artificial intelligence (AI) tools, using Antoine François Callet’s portrayal of Achilles Dragging Hector’s Body Past the Walls of Troy as a case study. The application of Easy Diffusion and Stable Diffusion 2.1 technologies provides insights into AI-driven restoration methods such as inpainting and colorization. Results indicate that while AI can streamline the restoration process, repeated inpainting can compromise the painting’s color quality and detailed features. Furthermore, the AI approach occasionally introduces unintended …
Novus Ex Machina: Realise Your Organisation’S Creative Potential With Ai,
2023
Singapore Management University
Novus Ex Machina: Realise Your Organisation’S Creative Potential With Ai, Adam Tatarynowicz, Utz Claassen
Asian Management Insights
Innovation managers must learn how to harness AI’s transformative potential.
Healthaichain: Improving Security And Safety Using Blockchain Technology Applications In Ai-Based Healthcare Systems,
2023
Emporia State University
Healthaichain: Improving Security And Safety Using Blockchain Technology Applications In Ai-Based Healthcare Systems, Naresh Kshetri, James Hutson, Revathy G
Faculty Scholarship
Blockchain as a digital ledger for keeping records of digital transactions and other information, it is secure and decentralized technology. The globally growing number of digital population every day possesses a significant threat to online data including the medical and patients’ data. After bitcoin, blockchain technology has emerged into a general-purpose technology with applications in medical industries and healthcare. Blockchain can promote highly configurable openness while retaining the highest security standards for critical data of medical patients. Referred to as distributed record keeping for healthcare systems which makes digital assets unalterable and transparent via a cryptographic hash and decentralized network. …
Smartphone Based Object Detection For Shark Spotting,
2023
California Polytechnic State University, San Luis Obispo
Smartphone Based Object Detection For Shark Spotting, Darrick W. Oliver
Master's Theses
Given concern over shark attacks in coastal regions, the recent use of unmanned aerial vehicles (UAVs), or drones, has increased to ensure the safety of beachgoers. However, much of city officials' process remains manual, with drone operation and review of footage still playing a significant role. In pursuit of a more automated solution, researchers have turned to the usage of neural networks to perform detection of sharks and other marine life. For on-device solutions, this has historically required assembling individual hardware components to form an embedded system to utilize the machine learning model. This means that the camera, neural processing …
The Impact Of Generative Ai In The Financial Sector [El Impacto De La Inteligencia Artificial Generativa En El Sector Financiero],
2023
Singapore Management University
The Impact Of Generative Ai In The Financial Sector [El Impacto De La Inteligencia Artificial Generativa En El Sector Financiero], Nydia Remolina Leon
Research Collection Yong Pung How School Of Law
No abstract provided.
Typesqueezer: When Static Recovery Of Function Signatures For Binary Executables Meets Dynamic Analysis,
2023
Singapore Management University
Typesqueezer: When Static Recovery Of Function Signatures For Binary Executables Meets Dynamic Analysis, Ziyi Lin, Jinku Li, Bowen Li, Haoyu Ma, Debin Gao, Jianfeng Ma
Research Collection School Of Computing and Information Systems
Control-Flow Integrity (CFI) is considered a promising solutionin thwarting advanced code-reuse attacks. While the problem ofbackward-edge protection in CFI is nearly closed, effective forward-edge protection is still a major challenge. The keystone of protecting the forward edge is to resolve indirect call targets, which although can be done quite accurately using type-based solutionsgiven the program source code, it faces difficulties when carriedout at the binary level. Since the actual type information is unavailable in COTS binaries, type-based indirect call target matching typically resorts to approximate function signatures inferredusing the arity and argument width of indirect callsites and calltargets. Doing so …
A Review Of Cyber Attacks On Sensors And Perception Systems In Autonomous Vehicle,
2023
The University of Texas Rio Grande Valley
A Review Of Cyber Attacks On Sensors And Perception Systems In Autonomous Vehicle, Taminul Islam, Md. Alif Sheakh, Anjuman Naher Jui, Omar Sharif, Md Zobaer Hasan
School of Mathematical & Statistical Sciences Faculty Publications
Vehicle automation has been in the works for a long time now. Automatic brakes, cruise control, GPS satellite navigation, etc. are all common features seen in today's automobiles. Automation and artificial intelligence breakthroughs are likely to lead to an increase in the usage of automation technologies in cars. Because of this, mankind will be more reliant on computer-controlled equipment and car systems in our daily lives. All major corporations have begun investing in the development of self-driving cars because of the rapid advancement of advanced driver support technologies. However, the level of safety and trustworthiness is still questionable. Imagine what …
Examining The Externalities Of Highway Capacity Expansions In California: An Analysis Of Land Use And Land Cover (Lulc) Using Remote Sensing Technology,
2023
San Jose State University
Examining The Externalities Of Highway Capacity Expansions In California: An Analysis Of Land Use And Land Cover (Lulc) Using Remote Sensing Technology, Serena E. Alexander, Bo Yang, Owen Hussey, Derek Hicks
Mineta Transportation Institute
There are over 590,000 bridges dispersed across the roadway network that stretches across the United States alone. Each bridge with a length of 20 feet or greater must be inspected at least once every 24 months, according to the Federal Highway Act (FHWA) of 1968. This research developed an artificial intelligence (AI)-based framework for bridge and road inspection using drones with multiple sensors collecting capabilities. It is not sufficient to conduct inspections of bridges and roads using cameras alone, so the research team utilized an infrared (IR) camera along with a high-resolution optical camera. In many instances, the IR camera …
Optimized Uncertainty Estimation For Vision Transformers: Enhancing Adversarial Robustness And Performance Using Selective Classification,
2023
Loyola University Chicago
Optimized Uncertainty Estimation For Vision Transformers: Enhancing Adversarial Robustness And Performance Using Selective Classification, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja
Computer Science: Faculty Publications and Other Works
Deep Learning models often exhibit undue confidence when encountering out-of-distribution (OOD) inputs, misclassifying with high confidence. The ideal outcome, in these cases, would be an "I do not know" verdict. We enhance the trustworthiness of our models through selective classification, allowing the model to abstain from making predictions when facing uncertainty. Rather than a singular prediction, the model offers a prediction distribution, enabling users to gauge the model’s trustworthiness and determine the need for human intervention. We assess uncertainty in two baseline models: a Convolutional Neural Network (CNN) and a Vision Transformer (ViT). By leveraging these uncertainty values, we minimize …
Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures,
2023
Loyola University Chicago
Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja
Computer Science: Faculty Publications and Other Works
Deep Learning (DL) methods have shown substantial efficacy in computer vision (CV) and natural language processing (NLP). Despite their proficiency, the inconsistency in input data distributions can compromise prediction reliability. This study mitigates this issue by introducing uncertainty evaluations in DL models, thereby enhancing dependability through a distribution of predictions. Our focus lies on the Vision Transformer (ViT), a DL model that harmonizes both local and global behavior. We conduct extensive experiments on the ImageNet-1K dataset, a vast resource with over a million images across 1,000 categories. ViTs, while competitive, are vulnerable to adversarial attacks, making uncertainty estimation crucial for …
Individuality And The Collective In Ai Agents: Explorations Of Shared Consciousness And Digital Homunculi In The Metaverse For Cultural Heritage,
2023
Lindenwood University
Individuality And The Collective In Ai Agents: Explorations Of Shared Consciousness And Digital Homunculi In The Metaverse For Cultural Heritage, James Hutson, Jay Ratican
Faculty Scholarship
The confluence of extended reality (XR) technologies, including augmented and virtual reality, with large language models (LLM) marks a significant advancement in the field of digital humanities, opening uncharted avenues for the representation of cultural heritage within the burgeoning metaverse. This paper undertakes an examination of the potentialities and intricacies of such a convergence, focusing particularly on the creation of digital homunculi or changelings. These virtual beings, remarkable for their sentience and individuality, are also part of a collective consciousness, a notion explored through a thematic comparison in science fiction with the Borg and the Changelings in the Star Trek …
Digitizing The Cultural Capital: Harnessing Digital Humanities For Heritage Preservation In Bujumbura, Burundi,
2023
Lindenwood University
Digitizing The Cultural Capital: Harnessing Digital Humanities For Heritage Preservation In Bujumbura, Burundi, James Hutson, Pace Ellsworth, Matt Ellsworth, Jean Bosco Ntungirimana
Faculty Scholarship
In an era where the erosion of cultural heritage is increasingly prevalent, there exists a critical imperative to explore and implement innovative methods for the preservation and revitalization of cultural identities, as exemplified by the urgent situation in Bujumbura, Burundi. Central to this study is the exploration of innovative digital methodologies for archiving a wide spectrum of cultural artifacts, including both notable and everyday heritage elements, in Bujumbura. Traditional approaches to biographical and historical profiling have predominantly focused on official records and significant events, often neglecting the richness of personal experiences and everyday interactions that substantially shape cultural identities. To …
A Smart Chatbot System For Digitizing Service Management To Improve Business Continuity,
2023
United Arab Emirates University
A Smart Chatbot System For Digitizing Service Management To Improve Business Continuity, Asraa Mohammed Albeshr
Theses
Chatbots, also called digital systems that require a natural language-based interface for user interaction, are increasingly being integrated into our daily lives. These chatbots respond intelligently to voice and text and function as sophisticated entities. Its functioning includes the recognition of multiple human languages through the application of Natural Language Processing (NLP) techniques. These chatbots find applications in various areas such as e-commerce services, medical assistance, recommendation systems, and educational purposes. This reflects the versatility and widespread adoption of this technology. AI chatbots play a crucial role in improving IT support in IT Service Management (ITSM) for better business continuity. …
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach,
2023
Singapore Management University
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel. Chen, Nan Hu, Peng. Liang, Morgan. Swink
Research Collection School Of Computing and Information Systems
Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …
Designing Depaul,
2023
DePaul University
Designing Depaul
DePaul Magazine
DePaul’s comprehensive, collaborative plan creates a road map that positions the university for monumental impact.
Generative Ai-Based Non-Person Character (Npc) For Navigating Virtual Worlds,
2023
University of North Dakota
Generative Ai-Based Non-Person Character (Npc) For Navigating Virtual Worlds, Ananth Ramaseri-Chandra
Computer Science Posters and Presentations
An innovative approach to virtual world interactions through generative AI-based Non-person Characters (NPCs). These AI-driven NPCs significantly advance over traditional, scripted characters by providing more realistic, adaptive, and dynamic interactions in various virtual environments. The work details the development process of these NPCs, from algorithm design to data integration and iterative refinement, ensuring their seamless integration into game environments. Additionally, the poster explores the wide-ranging applications of these AI NPCs, including enhancing gaming experiences, offering realistic training environments, and facilitating personalized virtual learning experiences. This research marks a substantial leap in virtual interaction, pushing the boundaries of immersion and realism …
