AIMC Topic: Odorants

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[Determination of flavor compounds in foxtail millet wine by gas chromatography-mass spectrometry coupled with headspace solid phase microextraction].

Se pu = Chinese journal of chromatography Nov 8, 2017
To comprehensively understand flavor compounds and aroma characteristics of foxtail millet wine, extraction conditions were optimized with 85 μm polyacrylate (PA), 100 μm polydimethylsiloxane (PDMS), 75 μm carboxen (CAR)/PDMS and 50/30 μm divinylbenz...
Phenols Setaria Plant Wine Gas Chromatography-Mass Spectrometry Odorants Esters Taste Dimethylpolysiloxanes Solid Phase Microextraction Polyvinyls
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Niépce-Bell or Turing: how to test odour reproduction.

Journal of the Royal Society, Interface Dec 1, 2016
Decades before the existence of anything resembling an artificial intelligence system, Alan Turing raised the question of how to test whether machines can think, or, in modern terminology, whether a computer claimed to exhibit intelligence indeed doe...
Humans Artificial Intelligence Odorants Olfactory Perception
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Improving odorant chemical class prediction with multi-layer perceptrons using temporal odorant spike responses from drosophila melanogaster olfactory receptor neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
In this work, we examine the possibility of improving the prediction performance of an olfactory biosensor through the use of temporal spiking data. We present an Artificial Neural Network (ANN), in the form of an optimal hybrid Multi-Layer Perceptro...
Neural Networks, Computer Animals Time Factors Action Potentials Odorants Smell Drosophila melanogaster Receptors, Odorant Olfactory Receptor Neurons
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Automatic recognition of pleasant content of odours through ElectroEncephaloGraphic activity analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This study presents a machine learning approach applied to ElectroEnchephaloGraphic (EEG) response in a group of subjects when exposed to a controlled olfactory stimulation experiment. In the literature, in fact, there are controversial results on EE...
Humans Machine Learning Female Young Adult Adult Electroencephalography Odorants Data Accuracy Olfactory Perception
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