[HTML][HTML] Review on smart gas sensing technology

S Feng, F Farha, Q Li, Y Wan, Y Xu, T Zhang, H Ning - Sensors, 2019‏ - mdpi.com
With the development of the Internet-of-Things (IoT) technology, the applications of gas
sensors in the fields of smart homes, wearable devices, and smart mobile terminals have …

Chemical gas sensors: Recent developments, challenges, and the potential of machine learning—A review

U Yaqoob, MI Younis - Sensors, 2021‏ - mdpi.com
Nowadays, there is increasing interest in fast, accurate, and highly sensitive smart gas
sensors with excellent selectivity boosted by the high demand for environmental safety and …

[HTML][HTML] An improved algorithm of drift compensation for olfactory sensors

S Lu, J Guo, S Liu, B Yang, M Liu, L Yin, W Zheng - Applied Sciences, 2022‏ - mdpi.com
This research mainly studies the semi-supervised learning algorithm of different domain
data in machine olfaction, also known as sensor drift compensation algorithm. Usually for …

Domain adaptation extreme learning machines for drift compensation in E-nose systems

L Zhang, D Zhang - IEEE Transactions on instrumentation and …, 2014‏ - ieeexplore.ieee.org
This paper addresses an important issue known as sensor drift, which exhibits a nonlinear
dynamic property in electronic nose (E-nose), from the viewpoint of machine learning …

Learning domain-invariant subspace using domain features and independence maximization

K Yan, L Kou, D Zhang - IEEE transactions on cybernetics, 2017‏ - ieeexplore.ieee.org
Domain adaptation algorithms are useful when the distributions of the training and the test
data are different. In this paper, we focus on the problem of instrumental variation and time …

A deformable CNN-DLSTM based transfer learning method for fault diagnosis of rolling bearing under multiple working conditions

Z Wang, Q Liu, H Chen, X Chu - International Journal of Production …, 2021‏ - Taylor & Francis
Machine learning methods are widely used for rolling bearing fault diagnosis. Most of them
are based on a basic assumption that training and testing data are adequate and follow the …

Artificial Olfaction in the 21st Century

JA Covington, S Marco, KC Persaud… - IEEE Sensors …, 2021‏ - ieeexplore.ieee.org
The human olfactory system remains one of the most challenging biological systems to
replicate. Humans use it without thinking, where it can measure offer protection from harm …

Metal oxide-based electrical/electrochemical sensors for health monitoring systems

M Taheri, IA Deen, M Packirisamy, MJ Deen - TrAC Trends in Analytical …, 2024‏ - Elsevier
There is a growing demand to develop sensors for health monitoring applications such as
wearable systems for early detection of chronic diseases signs, water and food quality …

RHINOS: A lightweight portable electronic nose for real-time odor quantification in wastewater treatment plants

J Burgués, MD Esclapez, S Doñate, S Marco - IScience, 2021‏ - cell.com
Quantification of odor emissions in wastewater treatment plants (WWTPs) is key to minimize
odor impact to surrounding communities. Odor measurements in WWTPs are usually …

Anti-drift in E-nose: A subspace projection approach with drift reduction

L Zhang, Y Liu, Z He, J Liu, P Deng, X Zhou - Sensors and Actuators B …, 2017‏ - Elsevier
Anti-drift is an emergent and challenging issue in sensor-related subjects. In this paper, we
propose to address the time-varying drift (eg electronic nose drift), which is sometimes an ill …