An Adaptive Temporal Convolutional Network Autoencoder for Malicious Data Detection in Mobile Crowd Sensing.

Mobile crowdsensing (MCS) systems rely on the collective contribution of sensor data from numerous mobile devices carried by participants. However, the open and participatory nature of MCS renders these systems vulnerable to adversarial attacks or data poisoning attempts where threat actors can inject malicious data into the system. There is a need for a detection system that mitigates malicious sensor data to maintain the integrity and reliability of the collected information.

Optimization of Glutaraldehyde Vapor Treatment for Electrospun Collagen/Silk Tissue Engineering Scaffolds.

Freestanding fibrous matrices with proper protein composition and desirable mechanical properties, stability, and biocompatibility are in high demand for tissue engineering. Electrospun (E-spun) collagen-silk composite fibers are promising tissue engineering scaffolds. However, as-spun fibers are mechanically weak and unstable.