Digital Commons Network^™

Extending The Convolution In Graph Neural Networks To Solve Materials Science And Node Classification Problems, Steph-Yves Mike Louis

Theses and Dissertations

The usage of graph to represent one's data in machine learning has grown in popularity in both academia and the industry due to its inherent benefits. With its flexible nature and immediate translation to real life observed objects, graph representation had a considerable contribution in advancing the state-of-the-art performance of machine learning in materials.

In this dissertation proposal, we discuss how machines can learn from graph encoded data and provide excellent results through graph neural networks (GNN). Notably, we focus our adaptation of graph neural networks on three tasks: predicting crystal materials properties, nullifying the negative impact of inferior graph …

An Artificial Intelligence Approach To Fatigue Crack Length Estimation From Acoustic Emission Signals, Shane T. Ennis

Theses and Dissertations

As in service aircraft begin to age and fatigue, a method for evaluating the operational life they are currently operating under and have remaining comes into question. Structural health monitoring is (SHM) is a popular method of structural analysis with growing interest in the aerospace industry. SHM is capable of damage assessment and structural life estimations.

The ultimate goal of the research presented in this thesis is to develop a methodology of classifying the length of a fatigue crack though the use of machine learning. The thesis has three major chapters as described below.

The first chapter deals with the …

Exploring Trustworthiness Issues About Disaster-Related Information Generated By Artificial Intelligence, Xin Tao

Theses and Dissertations

This thesis tested the degree of trustworthiness of disaster-related information generated by artificial intelligence among American people and Chinese people, and explored the causes of people's attitudes towards trust or distrust. The thesis used OpenAI's GPT-3 model to generate stories based on real disaster events by artificial intelligence, and tested the degree of trustworthiness in semi-structured interview. The study showed that it was promising to use AI technology to publicize disaster-related news to audience. To increase readers' trust in AI-generated disaster-related information, news organizations should maintain a high level of transparency about the identity of the AI author, use the …

Classification Of Acoustic Emission Data Into Load Steps Using An Artificial Neural Network, Allen Ross

Theses and Dissertations

The average age of bridges in South Carolina is approaching 40 years, very close to the 50-year service life. Almost 11% of the bridges in South Carolina are rated as structurally deficient, greater than the national average of 7.5% (South 2021). Health monitoring is the concept that in-situ sensors can continuously monitor civil structures and send real time signals of damage. This process allows for automation and could save time and money on the inspection and load rating of bridges. Health monitoring requires sensors that provide uninterrupted data without sacrificing the functionality of the bridge. A prime candidate for this …

Alexa, Should I Trust You? A Theory Of Trustworthiness For Artificial Intelligence, Elizabeth K. Stewart

Theses and Dissertations

As people turn to AI driven technologies for help with everything from meal planning to choosing a mate, it is increasingly important for individuals to gauge the trustworthiness of available technologies. However, most philosophical theories of trustworthiness focus on interpersonal trust and are inappropriate for non-agents. What, then, does it mean for non-agents such as AI driven technologies to be trustworthy? I distinguish two different forms of trustworthiness: naive trustworthiness and robust trustworthiness. An agent is naively trustworthy to the extent that it would be likely to meet the truster’s expectations with respect to a given domain. An agent is …

Simulation-Based And Data-Driven Approaches To Industrial Digital Twinning Towards Autonomous Smart Manufacturing Systems, Kaishu Xia

Theses and Dissertations

A manufacturing paradigm shift from conventional control pyramids to decentralized, service-oriented, and cyber-physical systems (CPSs) is taking place in today’s Industry 4.0 revolution. Generally accepted roles and implementation recipes of cyber systems are expected to be standardized in the future of manufacturing industry. Developing affordable and customizable cyber-physical production system (CPPS) and digital twin implementations infuses new vitality for current Industry 4.0 and Smart Manufacturing initiatives. Specially, Smart Manufacturing systems are currently looking for methods to connect factories to control processes in a more dynamic and open environment by filling the gaps between virtual and physical systems.

The work presented …

Artificial Intelligence Approaches For Structural Health Monitoring Of Aerospace Structures, Kimberly A. Cardillo

Theses and Dissertations

Structural health monitoring (SHM) and non-destructive evaluation (NDE) have been a significant research topic to help with damage detection in aerospace structures. SHM and NDE techniques are based on extracting damage sensitive features to determine the criticality of damage and lifetime of a structure. Acoustic emission (AE) signal detection is an important technique in SHM and NDE especially for fatigue crack growth. AE signals for thin aerospace structures consist of ultrasonic guided Lamb waves that propagate through the structure. This thesis focuses on AE signal repeatability, load at which AE signals occur, feature extraction, artificial intelligence and electro-mechanical impedance of …

From Cellular To Holistic: Development Of Algorithms To Study Human Health And Diseases, Casey Anne Cole

Theses and Dissertations

The development of theoretical computational methods and their application has become widespread in the world today. In this dissertation, I present my work in the creation of models to detect and describe complex biological and health related problems. The first major part of my work centers around the creation and enhancement of methods to calculate protein structure and dynamics. To this end, substantial enhancement has been made to the software package REDCRAFT to better facilitate its usage in protein structure calculation. The enhancements have led to an overall increase in its ability to characterize proteins under difficult conditions such as …

Assessing Social Media For Themes Of Trisomy 18 And 13, Falecia Metcalf

Theses and Dissertations

Themes within virtual communities have been explored examining topics such as prenatal diagnosis and termination for fetal anomalies, and it is known that when receiving a diagnosis of trisomy 18 or 13 parents may turn to online resources for information and emotional support. Knowledge of what content patients may encounter on various social media platforms about prenatal testing for trisomy 18 and 13 at large has not yet been established. However, this information would aid healthcare professionals in providing anticipatory guidance for patients using social media.

This study is a preliminary scan of social media to identify content areas and …