Engineering Commons^™

Advancing Winter Weather Adas: Tire Track Identification And Road Snow Coverage Estimation Using Deep Learning And Sensor Integration, Parth Kadav

Masters Theses

No abstract provided.

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Revolutionising Engineering Education: Creating Photorealistic Virtual Human Lecturers Using Artificial Intelligence And Computer Generated Images, Johannes H Moolman, Fiona Boyle, Joseph Walsh

Research Papers

The COVID-19 pandemic has disrupted traditional classroom learning, making virtual and remote education increasingly important. In this context, the use of photorealistic virtual humans, or avatars, powered by Artificial Intelligence (AI) can offer an immersive and engaging environment for delivering traditional classroom-based lectures. This paper proposes a process that combines AI and Computer-Generated Images (CGI) to create photorealistic virtual human lecturers for educational purposes.

The proposed process flow involves generating audio from text inputs, which is passed to a 3-Dimensional (3D) facial animation rig that matches lip, tongue, eye and facial movements to the audio using AI. This generates a …

Catalytic Hydrogenation Of Dimethyl Oxalate To Ethylene Glycol Using Silver Based Catalysts On Sba-15, Nicolas Edouard Gleason-Boure

Theses and Dissertations

Ethylene glycol (EG) is an important industrial chemical in the manufacturing of certain plastics. There is growing industrial interest in the production of dimethyl oxalate (DMO) from syngas, which can be hydrogenated to produce EG. Many studies have focused on the catalytic reduction of DMO using copper-based catalysts on silica supports, but fewer studies have been done on the effects of silver for this reaction. This work presents an in-depth study of silver catalysts prepared via various methods including incipient wetness impregnation, charge enhanced dry impregnation, and the use of various organic solvents. Reaction studies show that using pure methanol …

Anomaly Detection On Complex Health Information Technology Systems, Haoran Niu

Doctoral Dissertations

While modern complex computer systems provide enormous benefits to our daily lives, the increasing complexity of these large-scale systems also makes them more susceptible to unexpected software malfunctions and malicious attacks. This is especially true for Health Information Technology (HIT), which has revolutionized healthcare delivery by making it more efficient, effective, and accessible. Nevertheless, the widespread adoption of HIT has introduced new challenges related to ensuring system reliability and security. As a result, the development of novel algorithms and frameworks to detect anomalies in such systems has become increasingly important for enhancing patient safety and improving the efficiency and effectiveness …

Rebranding Originality For The Age Of Ai, Jason Gulya

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

"Originality" has been a longstanding focal point within the college classroom, with students being encouraged to embrace creativity and boldness. The traditional view of originality, relying solely on one's wit and imagination, has lost its effectiveness in the present era. The concept of learning has undergone a significant transformation, no longer resembling the isolated ivory tower of the past where individuals would immerse themselves in books, hoping to be inspired. Instead, modern learning has become more social and collaborative. Students compare and contrast class material with online resources, engaging in conversations, both in person and virtually, to solidify their understanding. …

When Ai Moves Downstream, Frances S. Grodzinsky, Keith W. Miller, Marty J. Wolf

School of Computer Science & Engineering Faculty Publications

After computing professionals design, develop, and deploy software, what is their responsibility for subsequent uses of that software “downstream” by others? Furthermore, does it matter ethically if the software in question is considered to be artificial intelligent (AI)? The authors have previously developed a model to explore downstream accountability, called the Software Responsibility Attribution System (SRAS). In this paper, we explore three recent publications relevant to downstream accountability, and focus particularly on examples of AI software. Based on our understanding of the three papers, we suggest refinements of SRAS.

Accounting And Financial Statements Auto Analysis System, Zhen Jia

Electronic Theses, Projects, and Dissertations

This project was motivated by the need to revolutionize the generation of financial statements and financial analysis process thus speeding up business decision making. The research questions were: 1) How can machine learning increase the speed of financial statement preparation and automate financial statements analysis? 2) How can businesses balance the benefits of automating financial analysis with potential concerns around privacy, data security, and bias? 3) Can the Java J2EE framework provide a reliable running environment for machine learning?

The findings were: 1) Machine learning can significantly increase the accuracy and speed of financial analysis. Using machine learning algorithms, financial …

Insider Action Research On Ai Needs Within The Eit Innoenergy Ecosystem, Inge De Waard, Albert Gonzalez, Anouk Gelan

Practice Papers

This practice paper describes an ongoing insider action research within the EIT InnoEnergy ecosystem. Its goal is to inspire teaching staff from the seven EIT InnoEnergy double degree Master of Science programmes to integrate Artificial Intelligence (AI) tools and knowledge into their courses based on joint learning. This insider action research runs from 2023 to the end of 2024. In late 2022, a problem statement of ‘AI tools for Education’ was identified by EIT InnoEnergy teachers as being crucial for their future learning and teaching processes. To align the needs of teaching staff with the complexity of emerging AI tools, …

Revised Avenues Of Assessment In Higher Education In The Presence Of Ai Generative Contents, Muhammad Iqbal

HECA Research Conference

This study explores the impact of Generative Artificial Intelligence (AI) tools on academic assessments, focusing on their efficacy in generating unique content across various domains. Dr. Muhammad Iqbal from CCT College Dublin emphasizes the increasing prevalence of AI generative tools and their potential influence on learning quality in academia. The study addresses concerns related to assessment standards in higher education and proposes the evaluation of AI-generated content reliability.

Towards Explainable Ai Using Attribution Methods And Image Segmentation, Garrett J. Rocks

Honors Undergraduate Theses

With artificial intelligence (AI) becoming ubiquitous in a broad range of application domains, the opacity of deep learning models remains an obstacle to adaptation within safety-critical systems. Explainable AI (XAI) aims to build trust in AI systems by revealing important inner mechanisms of what has been treated as a black box by human users. This thesis specifically aims to improve the transparency and trustworthiness of deep learning algorithms by combining attribution methods with image segmentation methods. This thesis has the potential to improve the trust and acceptance of AI systems, leading to more responsible and ethical AI applications. An exploratory …

Human Tracking Function For Robotic Dog, Andrew Sharkey

Williams Honors College, Honors Research Projects

With the increase the increase in automation and humans and robots working side by side, there is a need for a more organic way of controlling robots. The goal of this project is to create a control system for Boston dynamics robotic dog Spot that implements human tracking image software to follow humans using computer vision as well as using hand tracking image software to allow for control input through hand gestures.

Cook-Gen: Robust Generative Modeling Of Cooking Actions From Recipes, Revathy Venkataramanan, Kaushik Roy, Kanak Ray, Renjith Prasad, Yuxin Zi, Vignesh Narayanan, Amit Sheth

Publications

As people become more aware of their food choices, food computation models have become increasingly popular in assisting people in maintaining healthy eating habits. For example, food recommendation systems analyze recipe instructions to assess nutritional contents and provide recipe recommendations. The recent and remarkable successes of generative AI methods, such as auto-regressive large language models, can lead to robust methods for a more comprehensive understanding of recipes for healthy food recommendations beyond surface-level nutrition content assessments. In this study, we explore the use of generative AI methods to extend current food computation models, primarily involving the analysis of nutrition and …

A-Eye Tech: Framework To Evaluate An Ai Construction Visibility Platform, Ahmed Hassan, Alan V. Hore, Mark Mulville

Conference Papers

The authors present the early stages of an Irish government-funded project, A-EYE. This disruptive technology seeks to create a construction visualisation platform that enables measurable productivity advantages through passive data capture and real-time delivery of mission-critical information in an accessible form. The authors outline how they will utilise data captured during construction site operations using camera and sensor equipment to monitor construction resources and processes. Moreover, the positive impact of easy access to visualised data on collaboration between construction stakeholders is discussed. Extensive user-experience research data will be captured after deploying the technology on live projects to create interactive dashboards …

The Need For International Ai Activities Monitoring, Parviz Partow-Navid, Ludwig Slusky

Journal of International Technology and Information Management

This paper focuses primarily on the need to monitor the risks arising from the dual-use of Artificial Intelligence (AI). Dual-use AI technology capability makes it applicable for defense systems and consequently may pose significant security risks, both intentional and unintentional, with the national and international scope of effects. While domestic use of AI remains the prerogative of individual countries, the unregulated and nonmonitored use of AI with international implications presents a specific concern. An international organization tasked with monitoring potential threats of AI activities could help defuse AI-associated risks and promote global cooperation in developing and deploying AI technology. The …

Optimal Path Planning For Aerial Robots Using Genetic Algorithm, Anna Puigvert I Juan

Graduate Theses, Dissertations, and Problem Reports

This thesis presents a path optimization solution for a robot in two different constrained 3-dimensional (3D) environments. The robot is required to travel from its current position to a goal position following minimum cost paths (optimal paths). The first environment has 3D obstacles that interfere with the robot’s path. The path cost for this environment accounts for the minimum distance traveled by the robot from the start to the goal position while avoiding obstacles. The second environment is the atmosphere of Venus, specifically a flyable region of this atmosphere with characteristics similar to Earth’s. This environment has strong westward winds …