AIMC Topic: Electronic Nose

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Identification of Similar Chinese Congou Black Teas Using an Electronic Tongue Combined with Pattern Recognition.

Molecules (Basel, Switzerland) Dec 12, 2019
It is very difficult for humans to distinguish between two kinds of black tea obtained with similar processing technology. In this paper, an electronic tongue was used to discriminate samples of seven different grades of two types of Chinese Congou b...
Camellia sinensis Tea Electronic Nose Humans Neural Networks, Computer Support Vector Machine
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Fuzzy controller based E-nose classification of Sitophilus oryzae infestation in stored rice grain.

Food chemistry Jan 19, 2019
Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. o...
Plant Proteins Animals Weevils Metals Electronic Nose Principal Component Analysis Fuzzy Logic Oryza Oxides Uric Acid Edible Grain Linear Models
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Detection of bitterness and astringency of green tea with different taste by electronic nose and tongue.

PloS one Dec 31, 2018
An electronic nose was used to evaluate the bitterness and astringency of green tea, and the possible application of the sensor was assessed for the evaluation of different tasting green tea samples. Three different grades of green tea were measured ...
Tea Neural Networks, Computer Taste Electronic Nose
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Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection.

Sensors (Basel, Switzerland) Oct 7, 2017
For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning comb...
Machine Learning Reproducibility of Results Benzene Acetone Wound Infection Electronic Nose Ethanol Formaldehyde Discriminant Analysis Diagnostic Equipment
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Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Journal of breath research Aug 21, 2017
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis...
Breath Tests Exhalation Electronic Nose Middle Aged Case-Control Studies Lung Neoplasms Support Vector Machine Neoplasm Staging Healthy Volunteers Adult Pulmonary Disease, Chronic Obstructive Male Female Aged Humans
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An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

Food research international (Ottawa, Ont.) May 20, 2017
Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authenticatio...
Reproducibility of Results Bacteria Spectroscopy, Fourier Transform Infrared Metabolomics Models, Statistical Food Microbiology Machine Learning Pattern Recognition, Automated Food Preservation Data Mining Optical Imaging Red Meat Gas Chromatography-Mass Spectrometry Principal Component Analysis Electronic Nose Automation Least-Squares Analysis Chromatography, High Pressure Liquid
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A Novel Semi-Supervised Method of Electronic Nose for Indoor Pollution Detection Trained by M-S4VMs.

Sensors (Basel, Switzerland) Sep 10, 2016
Electronic nose (E-nose), as a device intended to detect odors or flavors, has been widely used in many fields. Many labeled samples are needed to gain an ideal E-nose classification model. However, the labeled samples are not easy to obtain and ther...
Databases as Topic Electronic Nose Support Vector Machine Air Pollution, Indoor
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Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose.

Sensors (Basel, Switzerland) Jul 13, 2016
In the application of electronic noses (E-noses), probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used t...
Probability Panax Electronic Nose Support Vector Machine
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Performance Comparison of Fuzzy ARTMAP and LDA in Qualitative Classification of Iranian Rosa damascena Essential Oils by an Electronic Nose.

Sensors (Basel, Switzerland) May 4, 2016
Quality control of essential oils is an important topic in industrial processing of medicinal and aromatic plants. In this paper, the performance of Fuzzy Adaptive Resonant Theory Map (ARTMAP) and linear discriminant analysis (LDA) algorithms are com...
Oils, Volatile Fuzzy Logic Iran Rosa Electronic Nose
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Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system.

Bioinspiration & biomimetics Feb 18, 2016
In many application domains, conventional e-noses are frequently outperformed in both speed and accuracy by their biological counterparts. Exploring potential bio-inspired improvements, we note a number of neuronal network models have demonstrated so...
Equipment Failure Analysis Equipment Design Signal Processing, Computer-Assisted Electronic Nose Biomimetics Receptors, Odorant Insecta Animals Smell Neural Networks, Computer Computer Systems Nerve Net Computer Simulation Models, Neurological
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