Edge Storage Management Recipe with Zero-Shot Data Compression for Road Anomaly Detection

Recent studies show edge computing-based road anomaly detection systems which may also conduct data collection simultaneously. However, the edge computers will have small data storage but we need to store the collected audio samples for a long time in order to update existing models or develop a novel method. Therefore, we should consider an approach for efficient storage management methods while preserving high-fidelity audio. A hardware-perspective approach, such as using a low-resolution microphone, is an intuitive way to reduce file size but is not recommended because it fundamentally cuts off high-frequency components. On the other hand, a computational file compression approach that encodes collected high-resolution audio into a compact code should be recommended because it also provides a corresponding decoding method. Motivated by this, we propose a way of simple yet effective pre-trained autoencoder-based data compression method. The pre-trained autoencoder is trained for the purpose of audio super-resolution so it can be utilized to encode or decode any arbitrary sampling rate. Moreover, it will reduce the communication cost for data transmission from the edge to the central server. Via the comparative experiments, we confirm that the zero-shot audio compression and decompression highly preserve anomaly detection performance while enhancing storage and transmission efficiency.Comment: 5 pages, 3 figures, 4 table

Determination of twisting angle of electrospun nanofiber bundle for continuous electrospinning system

Electrospinning continuously produced twisted nanofibers with a convergence coil and a rotating ring collector. The positively charged nozzle was used in the electrospinning process to deposit electrospun fibers of polyacrylonitrile onto a rotating ring collector. By withdrawing the electrospun fibers from the rotating ring collector, it was possible to spin the electrospun fibers yarn. In this study, theoretical approaches and numerical simulations were used to determine the twisting angle of the yarn. Using the equations developed in this study, we performed numerical simulations and compared the experimental results with the numerical simulation results. Mechanical properties of the fiber bundle were analyzed for twisting angle. It was confirmed the relationship among the winding drum, the ring collector, and flux of the fibers mass per time during electrospinning in the developed system. (c) 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 4552