AIMC Topic: Odorants

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A neural data structure for novelty detection.

Proceedings of the National Academy of Sciences of the United States of America
Novelty detection is a fundamental biological problem that organisms must solve to determine whether a given stimulus departs from those previously experienced. In computer science, this problem is solved efficiently using a data structure called a B...

Abstract concept learning in a simple neural network inspired by the insect brain.

PLoS computational biology
The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly h...

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.

Nature neuroscience
Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis ca...

Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis.

ACS sensors
A sensing signal obtained by measuring an odor usually contains varied information that reflects an origin of the odor itself, while an effective approach is required to reasonably analyze informative data to derive the desired information. Herein, w...

Deep(er) Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptabl...

Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.

PloS one
Recent studies on machine learning technology have reported successful performances in some visual and auditory recognition tasks, while little has been reported in the field of olfaction. In this paper we report computational methods to predict the ...

A Robot Equipped with a High-Speed LSPR Gas Sensor Module for Collecting Spatial Odor Information from On-Ground Invisible Odor Sources.

ACS sensors
Improving the efficiency of detecting the spatial distribution of gas information with a mobile robot is a great challenge that requires rapid sample collection, which is basically determined by the speed of operation of gas sensors. The present work...

Sensory characterization and acceptance of coffee brews of C. arabica and C. canephora blended with steamed defective coffee.

Food research international (Ottawa, Ont.)
Steam treatment has been reported as an alternative to improve the cup quality of coffee; in this research, it was applied to C. canephora defective coffee. The aim of the study was to evaluate the sensory perception of steamed defective C. canephora...

Dual solid-phase and stir bar sorptive extraction combined with gas chromatography-mass spectrometry analysis provides a suitable tool for assaying limonene-derived mint aroma compounds in red wine.

Analytica chimica acta
A novel analytical method was developed for quantitative determination of eight limonene-derived monoterpenes responsible for the mint aroma in red wine. As these aromatic compounds are present at trace levels, a new dual extraction approach was prop...

Machine-Learning-Based Olfactometer: Prediction of Odor Perception from Physicochemical Features of Odorant Molecules.

Analytical chemistry
Gas chromatography/olfactometry (GC/O) has been used in various fields as a valuable method to identify odor-active components from a complex mixture. Since human assessors are employed as detectors to obtain the olfactory perception of separated odo...