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Full-Text Articles in Engineering

Digital Fabrication Of A Small Diameter Polymer Optical Waveguide, Venkat Rama Bhethanabotla, Thomas M. Weller, Roger Brandon Tipton, John Townsend Bentley, Eduardo Antonio Rojas Dec 2020

Digital Fabrication Of A Small Diameter Polymer Optical Waveguide, Venkat Rama Bhethanabotla, Thomas M. Weller, Roger Brandon Tipton, John Townsend Bentley, Eduardo Antonio Rojas

Publications

A novel polymer optical waveguide and method of manu­facturing is presented herein. A digitally manufactured pro­cess is described which utilizes a micro-dispensed UV optical adhesive as the contour guiding cladding, a fused deposition modeling technology for creating a core, addi­tional optical adhesive to complete the cladding and a subtractive laser process to finish the two ends of the optical interconnect.


Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming Aug 2020

Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming

Publications

The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to the existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ cryptographic signatures to verify the trustworthiness of received information. In prevalent IoT, secret keys for cryptography can potentially be disclosed and disable the verification mechanism. Noncryptographic device verification is needed to ensure trustworthy IoT. In this article, we propose an enhanced deep learning framework …


Performance Testing Of Aero-Naut Camfolding Propellers, Or D. Dantsker, Robert W. Deters, Marco Caccamo, Michael S. Selig Jun 2020

Performance Testing Of Aero-Naut Camfolding Propellers, Or D. Dantsker, Robert W. Deters, Marco Caccamo, Michael S. Selig

Publications

The increase in popularity of unmanned aerial vehicles (UAVs) has been driven by their use in civilian, education, government, and military applications. However, limited on-board energy storage significantly limits flight time and ultimately usability. The propulsion system plays a critical part in the overall energy consumption of the UAV; therefore, it is necessary to determine the most optimal combination of possible propulsion system components for a given mission profile, i.e. propellers, motors, and electronic speed controllers (ESC). Hundreds of options are available for the different components with little performance specifications available for most of them. By examining a variety of …


Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang Jan 2020

Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang

Publications

Deep learning is increasingly applied to safety-critical application domains such as autonomous cars and medical devices. It is of significant importance to ensure their reliability and robustness. In this paper, we propose DLFuzz, the coverage guided differential adversarial testing framework to guide deep learing systems exposing incorrect behaviors. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. We also design multiple novel strategies for neuron selection to improve the neuron coverage. The …