Identification of binary gases’ mixtures from time-series resistance fluctuations: A sensitivity-controllable SnO2 gas sensor-based approach using 1D-CNN-Reference-Cited by-同舟云学术

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Identification of binary gases’ mixtures from time-series resistance fluctuations: A sensitivity-controllable SnO2 gas sensor-based approach using 1D-CNN

Published:2023-01 Issue: Volume:349 Page:114070
ISSN:0924-4247
Container-title:Sensors and Actuators A: Physical
language:en
Short-container-title:Sensors and Actuators A: Physical

Author:

Li Xuesi,Hu Xianyin,Li Ang,Kometani Reo,Yamada Ichiro,Sashida Kazuyuki,Noma Makiko,Nakanishi Katsufumi,Fukuda Yusuke,Takemori Toshiyuki,Maehara Kenichi,Ikeda Katsuya,Yoshida Kenichi,Mita Yoshio,Warisawa Shin'ichi

Funder

Otsuka Toshimi Scholarship Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Metals and Alloys,Surfaces, Coatings and Films,Condensed Matter Physics,Instrumentation,Electronic, Optical and Magnetic Materials

Reference44 articles.

1. World Health Organization, Health Topic of Diabetes. 〈https://www.who.int/health-topics/diabetes#tab=tab_1/〉, 2022 (accessed 25 May 2022).

2. Non-invasive glucose monitoring technology in diabetes management: a review;Vashist;Anal. Chim. Acta,2012

3. Review of non-invasive glucose sensing techniques: optical, electrical and breath acetone;Shokrekhodaei;Sens,2020

4. The progress of glucose monitoring- a review of invasive to minimally and non-invasive techniques, devices and sensors;Villena Gonzales;Sensors,2019

5. Non-invasive blood glucose monitoring technology: a review;Tang;Sensors,2020

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