Development of New Sensor and Sensing Technique by Electrolytic Polymerization with Utilizing a Magnetic Field and MCF Rubber on Robotics

Shimada, Kunio

doi:10.14243/jsaem.25.28

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…e current new MCF rubber vulcanization method is efficient enough to be widely used in tactile sensors in robotics and engineering applications [2]. Miao et al believe that new sensor technologies such as near-infrared spectroscopy, chemical imaging, electronic nose, and electronic tongue play an important role in the quality evaluation of traditional Chinese medicine and have prospects and opportunities for future research [3].…”

Section: Related Workmentioning

confidence: 99%

“…Shimada proposes that, with the application of magnetic fields and magnetically responsive fluids such as magnetic composite fluids (MCFs) as fillers, the effect of electrolytic polymerization on NR-latex such as plastic-type polymer solutions is enhanced. The current new MCF rubber vulcanization method is efficient enough to be widely used in tactile sensors in robotics and engineering applications [ 2 ]. Miao et al believe that new sensor technologies such as near-infrared spectroscopy, chemical imaging, electronic nose, and electronic tongue play an important role in the quality evaluation of traditional Chinese medicine and have prospects and opportunities for future research [ 3 ].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era

Feng

2022

Computational Intelligence and Neuroscience

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In recent years, with the rapid development of emerging Internet of Things technology and short-range wireless communication technology, smart healthcare monitoring network technology has become a research hotspot. It provides convenience for people and enhances the development of people’s own healthcare awareness. This paper aims to study how to make its application in the field of smart healthcare education more applicable through the use of related technologies in the Internet of Things era and few-shot learning. For this reason, this paper proposes to optimize and improve the new sensor technology and the algorithm of few-shot learning, and to adjust some parameters as a whole. At the same time, related experiments and analysis are designed for the improved algorithm to study and understand its performance. The experimental results in this paper show that the improved algorithm improves its application effect by 36.9% and is relatively more applicable than the unimproved algorithm.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%