AIMC Topic: Odorants

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A deep learning-based quantitative prediction model for the processing potentials of soybeans as soymilk raw materials.

Food chemistry May 14, 2024
Current technologies as correlation analysis, regression analysis and classification model, exhibited various limitations in the evaluation of soybean possessing potentials, including single, vague evaluation and failure of quantitative prediction, a...
Humans Deep Learning Food Handling Glycine max Soy Milk Odorants Taste
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Application of a generalized hybrid machine learning model for the prediction of HS and VOCs removal in a compact trickle bed bioreactor (CTBB).

Chemosphere Apr 27, 2024
This study presents a generalized hybrid model for predicting HS and VOCs removal efficiency using a machine learning model: K-NN (K - nearest neighbors) and RF (random forest). The approach adopted in this study enabled the (i) identification of odo...
Hydrogen Sulfide Odorants Volatile Organic Compounds Machine Learning Waste Disposal, Fluid Air Pollutants Bioreactors
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VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Environmental science and pollution research international Apr 26, 2024
Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing...
Neural Networks, Computer Odorants Volatile Organic Compounds Vehicle Emissions Support Vector Machine Gas Chromatography-Mass Spectrometry
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Artificial Q-Grader: Machine Learning-Enabled Intelligent Olfactory and Gustatory Sensing System.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 6, 2024
Portable and personalized artificial intelligence (AI)-driven sensors mimicking human olfactory and gustatory systems have immense potential for the large-scale deployment and autonomous monitoring systems of Internet of Things (IoT) devices. In this...
Zinc Oxide Odorants Tongue Coffee Smell Taste Machine Learning Electronic Nose Humans Principal Component Analysis Artificial Intelligence
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Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.

Food chemistry Feb 22, 2024
Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was develop...
Odorants Volatile Organic Compounds Coffee Deep Learning Algorithms Mass Spectrometry
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Data-centric artificial olfactory system based on the eigengraph.

Nature communications Feb 8, 2024
Recent studies of electronic nose system tend to waste significant amount of important data in odor identification. Until now, the sensitivity-oriented data composition has made it difficult to discover meaningful data to apply artificial intelligenc...
Smell Gases Technology Odorants Humans Artificial Intelligence
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Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective.

Molecules (Basel, Switzerland) Jan 23, 2024
Tea infusions are the most consumed beverages in the world after water; their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for the industry. Any qualification method capable of objecti...
China Tea Quality Control Humans Volatile Organic Compounds Smell Artificial Intelligence Odorants
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XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm.

Journal of biomolecular structure & dynamics Sep 18, 2023
Determining the structure-odor relationship has always been a very challenging task. The main challenge in investigating the correlation between the molecular structure and its associated odor is the ambiguous and obscure nature of verbally defined o...
Smell Quantitative Structure-Activity Relationship Models, Molecular Machine Learning Molecular Structure Algorithms 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, ...
Moths Bombyx Odorants Smell Female Algorithms Male Animals Robotics
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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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