2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)最新文献_第8页

Study of quality controls for stability check of the ROIs of a ketones mixture in different GC-IMS measurement campaigns 不同GC-IMS测定过程中酮类混合物roi稳定性检验的质量控制研究

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789683

C. Mallafré-Muro, Meryl Cruz, Arnau Blanco I Borrego, Luis Fernández Romero, Antonio Pardo Martínez, Santiago Marco Colás

引用次数: 0

A Modular Sensor System Design for Instrumental Odor Monitoring 一种用于仪器气味监测的模块化传感器系统设计

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789609

W. Reimringer, J. Joppich, M. Leidinger, Caroline Schultealbert, A. Schütze, T. Conrad

引用次数: 1

Transfer Learning to Significantly Reduce the Calibration Time of MOS Gas Sensors

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789596

Y. Robin, J. Amann, P. Goodarzi, A. Schütze, C. Bur

{"title":"Transfer Learning to Significantly Reduce the Calibration Time of MOS Gas Sensors","authors":"Y. Robin, J. Amann, P. Goodarzi, A. Schütze, C. Bur","doi":"10.1109/ISOEN54820.2022.9789596","DOIUrl":"https://doi.org/10.1109/ISOEN54820.2022.9789596","url":null,"abstract":"Metal oxide semiconductor (MOS) gas sensors used for indoor air quality monitoring require an intensive calibration to accurately quantify volatile organic compounds at ppb (parts per billion) level in complex gas mixtures. With the help of advances in the field of deep learning, particularly the use of convolutional neural networks together with neural architecture search, the noise of the quantification model can be reduced significantly with an uncertainty for xylene of 27 ppb. However, the calibration takes several days up to now. In this work, the concept of transfer learning is studied to reduce the required calibration time. It is shown that the calibration time of single sensors can be reduced by 96 %. The resulting uncertainty is only 21 ppb worse than the absolute best, i.e. the value for a complete individual calibration, which is sufficiently good. By slightly increasing the calibration time for transfer learning to 30 % of the initial time, an uncertainty value for xylene quantification of 36.3 ppb was achieved, and thus only 9.7 ppb worse than the best possible model.","PeriodicalId":427373,"journal":{"name":"2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124128674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Impedimetric bio-electronic tongue based on silver nanoparticles for the analysis of milk 基于纳米银纳米粒子的阻抗生物电子舌分析

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789670

C. Pérez-González, C. Salvo-Comino, J. L. Pura, F. Martín-Pedrosa, C. García-Cabezón, M. R. Méndez

引用次数: 0

Advance in electronic nose technology developed for the detection and discrimination of ethanol, ammonia, and hydrogen sulfide gases 乙醇、氨和硫化氢气体的电子鼻检测与鉴别技术进展

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789636

M. Moufid, C. Tiebe, N. E. Bari, M. Bartholmai, B. Bouchikhi

引用次数: 0

An Auditory and Olfactory Data Fusion Algorithm Based on Spiking Neural Network for Mobile Robot 基于脉冲神经网络的移动机器人听觉与嗅觉数据融合算法

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789674

Changming Chen, Yingying Xue, Yizhou Xiong, Mengxue Liu, L. Zhuang, Ping Wang

引用次数: 0

Hyper resoluted Air Quality maps in urban environment with crowdsensed data from intelligent low cost sensors 城市环境中的高分辨率空气质量地图，使用来自智能低成本传感器的众感数据

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789614

S. D. Vito, G. Fattoruso, G. D’Elia, E. Esposito, S. Ferlito, Antonio Del Giudice, E. Massera, G. Loffredo, G. Francia

引用次数: 1

Early alert system for odour management in WWTP 污水处理厂气味管理预警系统

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789637

Lidia Saúco, P. Pradas, Edurne Ibarrola, Jesús Martín, C. Lardín

引用次数: 0

Towards batch correction for GC-IMS data GC-IMS数据的批量校正

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789646

L. Fernandez, Arnau Blanco, C. Mallafré-Muro, S. Marco

{"title":"Towards batch correction for GC-IMS data","authors":"L. Fernandez, Arnau Blanco, C. Mallafré-Muro, S. Marco","doi":"10.1109/ISOEN54820.2022.9789646","DOIUrl":"https://doi.org/10.1109/ISOEN54820.2022.9789646","url":null,"abstract":"Gas Chromatography Ion Mobility Spectrometry (GC-IMS) is a fast, non-expensive analytical technique that allows obtaining relevant chemical information from vapor mixtures. However, the technique presents some difficulties that should be solved to ensure reliable and reproducible results, namely: 1) data exhibits simultaneously high dimensionality and sparsity on their chemical information content, 2) data samples must usually be corrected even within a batch because of baseline and misalignment problems, 3) additional data corrections must be performed to prevent from chemical fingerprinting variations among batches. In this work, we have acquired data from two different batches (A and B) of ketone mixtures (2-Butanone, 2-Pentanone, 2-Hexanone, and 2-Heptanone). The analytical method for batch A and B was the same, except for the value of carrier gas flow parameter, which was approximately doubled for batch B. We have addressed problems 1) and 2) independently for each batch, obtaining as a result two peak tables. 3). Common peaks present in batches A and B were found after scaling the retention time axis of batch B and perform k-medoids clustering. Using this information, test data from batch B has been corrected through a linear transformation.","PeriodicalId":427373,"journal":{"name":"2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133687133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards Gas Identification in Unknown Mixtures Using an Electronic Nose with One-Class Learning 一类学习电子鼻在未知混合气体识别中的应用

2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) Pub Date : 2022-05-29 DOI: 10.1109/ISOEN54820.2022.9789607

Han Fan, Daniel Jonsson, E. Schaffernicht, A. Lilienthal

引用次数: 0