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Functional Verification Of Additively Manufactured Metallopolymer Structures For Structural Electronics Design, Nathan D. Singhal
Functional Verification Of Additively Manufactured Metallopolymer Structures For Structural Electronics Design, Nathan D. Singhal
Honors Undergraduate Theses
As an attempt to improve the overall cost-effectiveness and ease of structural electronics manufacturing, this study characterizes the mechanical and electrical responses of structures which are fabricated from a novel metallopolymer composite material by fused deposition modeling as they are subjected to quasi-static, uniaxial mechanical tension. Baseline values of tensile properties and electrical resistivity were first obtained via ASTM D638-22 standard testing procedures and linear sweep voltammetry (LSV), respectively. A hybrid procedure to measure in-situ mechanically dependent electrical behavior was subsequently developed and implemented. The mechanical and electromechanical testing was followed by the derivation of stochastic values for several mechanical …
Towards Explainable Ai Using Attribution Methods And Image Segmentation, Garrett J. Rocks
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 …