AIMC Topic: Odorants

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Robust Moth-Inspired Algorithm for Odor Source Localization Using Multimodal Information.

Sensors (Basel, Switzerland) Jan 28, 2023
Odor-source localization, by which one finds the source of an odor by detecting the odor itself, is an important ability to possess in order to search for leaking gases, explosives, and disaster survivors. Although many animals possess this ability, ...
Female Animals Male Algorithms Smell Moths Bombyx Robotics Odorants
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Breath odor-based individual authentication by an artificial olfactory sensor system and machine learning.

Chemical communications (Cambridge, England) May 30, 2022
Breath odor sensing-based individual authentication was conducted for the first time using an artificial olfactory sensor system. Using a 16-channel chemiresistive sensor array and machine learning, a mean accuracy of >97% was successfully achieved. ...
Odorants Machine Learning Reproducibility of Results
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A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments.

Nature communications Jan 10, 2022
Object recognition is among the basic survival skills of human beings and other animals. To date, artificial intelligence (AI) assisted high-performance object recognition is primarily visual-based, empowered by the rapid development of sensing and c...
Humans Machine Learning Pattern Recognition, Physiological Electronic Nose Odorants Moles Pattern Recognition, Automated Animals Simulation Training Fires
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Quantitative analysis of fragrance allergens in various matrixes of cosmetics by liquid-liquid extraction and GC-MS.

Journal of food and drug analysis Dec 15, 2021
Fragrances are the most common chemicals in cosmetics to which people expose every day. However, the unwanted allergic reactions such as contact dermatitis caused by direct contact with fragrances may happen. In Directive 2003/15/EC of the EU, cosmet...
Odorants Cosmetics Perfume Gas Chromatography-Mass Spectrometry Humans Liquid-Liquid Extraction Allergens
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Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods.

Sensors (Basel, Switzerland) Nov 16, 2021
Machine learning methods enable the electronic nose (E-Nose) for precise odor identification with both qualitative and quantitative analysis. Advanced machine learning methods are crucial for the E-Nose to gain high performance and strengthen its cap...
Machine Learning Electronic Nose Robotics Odorants
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Sensory and flavor-aroma profiles of passion fruit juice fermented by potentially probiotic Lactiplantibacillus plantarum CCMA 0743 strain.

Food research international (Ottawa, Ont.) Sep 9, 2021
Several non-dairy probiotic beverages are already available to consumers and have been considered suitable carriers for probiotic bacteria. This study aimed to investigate the effect of Lactiplantibacillus plantarum CCMA 0743 in single and co-culture...
Fermentation Fruit and Vegetable Juices Beverages Probiotics Odorants
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Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling.

Molecules (Basel, Switzerland) Aug 23, 2021
Wine aroma is an important quality trait in wine, influenced by its volatile compounds. Many factors can affect the composition and levels (concentration) of volatile aromatic compounds, including the water status of grapevines, canopy management, an...
Electronic Nose Smoke Volatile Organic Compounds Multivariate Analysis Principal Component Analysis Wine Gas Chromatography-Mass Spectrometry Odorants Vitis Neural Networks, Computer Machine Learning
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An Ensemble Learning Method for Robot Electronic Nose with Active Perception.

Sensors (Basel, Switzerland) Jun 7, 2021
The electronic nose is the olfactory organ of the robot, which is composed of a large number of sensors to perceive the smell of objects through free diffusion. Traditionally, it is difficult to realize the active perception function, and it is diffi...
Nose Perception Electronic Nose Machine Learning Odorants Smell Robotics
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DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection.

Communications biology Jan 29, 2021
In general, animal behavior can be described as the neuronal-driven sequence of reoccurring postures through time. Most of the available current technologies focus on offline pose estimation with high spatiotemporal resolution. However, to correlate ...
Light Odorants Smell Behavior, Animal Video Recording Mice Posture Mice, Inbred C57BL Time Factors Image Processing, Computer-Assisted Conditioning, Classical Animals Photic Stimulation Olfactory Perception Deep Learning Head Movements Thalamus Optogenetics
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Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Techniques.

Sensors (Basel, Switzerland) Dec 27, 2020
Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor s...
Humans Odorants Neural Networks, Computer Environmental Monitoring Algorithms Electronics
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