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Article
Publication date: 5 May 2015

Bo Zhao, Nan Wang and Guohua Jiang

– The purpose of this paper is to arrange zinc oxide (ZnO) nanowires into an appropriate position on electrodes and to research the properties of ZnO nanowires.

Abstract

Purpose

The purpose of this paper is to arrange zinc oxide (ZnO) nanowires into an appropriate position on electrodes and to research the properties of ZnO nanowires.

Design/methodology/approach

In this paper, dielectrophoresis (DEP) was used to fabricate ZnO nanowire devices, and the responses to temperature, ultraviolet (UV) light and breath of the device were studied.

Findings

The number of the bridged nanowires is increased with alternating current voltage. ZnO nanowires demonstrate a good photoconductivity illuminated by 365-nm UV light, and show a stable performance in monitoring unnatural breath of high frequency and low strength.

Originality/value

In this paper, DEP is a promising method for controllable assembly of ZnO nanowires. ZnO nanowires demonstrate a good response to 365-nm UV light and exhaled breath, which show great potential application in UV detector and medical monitor.

Details

Microelectronics International, vol. 32 no. 2
Type: Research Article
ISSN: 1356-5362

Keywords

Article
Publication date: 3 June 2021

Fashu Xu, Rui Huang, Hong Cheng, Min Fan and Jing Qiu

This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications…

Abstract

Purpose

This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment.

Design/methodology/approach

According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state.

Findings

These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use.

Originality/value

This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.

Details

Assembly Automation, vol. 41 no. 3
Type: Research Article
ISSN: 0144-5154

Keywords

Abstract

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 4 no. 1
Type: Research Article
ISSN: 2633-6596

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