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Electronic Nose

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Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Journal of breath research
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...

Qualitative analysis of biological tuberculosis samples by an electronic nose-based artificial neural network.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
OBJECTIVE: To apply an e-nose system for monitoring headspace volatiles in biological samples from Egyptian patients with active pulmonary tuberculosis (TB) and healthy controls (HCs) and compare them with standard sputum analysis.

A Novel Semi-Supervised Method of Electronic Nose for Indoor Pollution Detection Trained by M-S4VMs.

Sensors (Basel, Switzerland)
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...

Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose.

Sensors (Basel, Switzerland)
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...

Performance Comparison of Fuzzy ARTMAP and LDA in Qualitative Classification of Iranian Rosa damascena Essential Oils by an Electronic Nose.

Sensors (Basel, Switzerland)
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...

Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system.

Bioinspiration & biomimetics
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...

Towards biological plausibility of electronic noses: A spiking neural network based approach for tea odour classification.

Neural networks : the official journal of the International Neural Network Society
The paper presents a novel encoding scheme for neuronal code generation for odour recognition using an electronic nose (EN). This scheme is based on channel encoding using multiple Gaussian receptive fields superimposed over the temporal EN responses...