AIMC Topic: Smoke

Clear Filters Showing 11 to 18 of 18 articles

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...
Neural Networks, Computer Electronic Nose Smoke Gas Chromatography-Mass Spectrometry Odorants Volatile Organic Compounds Multivariate Analysis Wine Vitis Machine Learning Principal Component Analysis
View on PubMed DOI

Co-occurrence balanced time series classification for the semi-supervised recognition of surgical smoke.

International journal of computer assisted radiology and surgery May 25, 2021
PURPOSE: Automatic recognition and removal of smoke in surgical procedures can reduce risks to the patient by supporting the surgeon. Surgical smoke changes its visibility over time, impacting the vision depending on its amount and the volume of the ...
Algorithms Smoke Humans Neural Networks, Computer
View on PubMed DOI

Ensemble-based deep learning for estimating PM over California with multisource big data including wildfire smoke.

Environment international Sep 24, 2020
INTRODUCTION: Estimating PM concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in nat...
California Smoke Particulate Matter Wildfires Big Data Environmental Monitoring Air Pollutants Air Pollution Deep Learning
View on PubMed DOI

A deep learning approach to identify smoke plumes in satellite imagery in near-real time for health risk communication.

Journal of exposure science & environmental epidemiology Jul 27, 2020
BACKGROUND: Wildland fire (wildfire; bushfire) pollution contributes to poor air quality, a risk factor for premature death. The frequency and intensity of wildfires are expected to increase; improved tools for estimating exposure to fire smoke are v...
Humans Smoke Fires Communication Satellite Imagery Deep Learning Australia Air Pollutants
View on PubMed DOI

Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach.

Sensors (Basel, Switzerland) Jul 30, 2019
Bushfires are becoming more frequent and intensive due to changing climate. Those that occur close to vineyards can cause smoke contamination of grapevines and grapes, which can affect wines, producing smoke-taint. At present, there are no available ...
Spectroscopy, Near-Infrared Smartphone Biosensing Techniques Humans Fruit Vitis Machine Learning Wine Smoke Fires
View on PubMed DOI

Machine Learning-Based Integration of High-Resolution Wildfire Smoke Simulations and Observations for Regional Health Impact Assessment.

International journal of environmental research and public health Jun 17, 2019
Large wildfires are an increasing threat to the western U.S. In the 2017 fire season, extensive wildfires occurred across the Pacific Northwest (PNW). To evaluate public health impacts of wildfire smoke, we integrated numerical simulations and observ...
Northwestern United States Air Pollutants Algorithms Wildfires Smoke Air Pollution Humans Health Impact Assessment Environmental Monitoring Machine Learning
View on PubMed DOI

Screening of oxidative stress components of cigarette smoke based on machine learning model integration.

Toxicology and applied pharmacology Jul 1, 2025
Cigarette smoke, a complex mixture of more than 7000 chemicals, poses a significant threat to human health, with oxidative stress being an important mechanism in its associated diseases. Traditional methods for assessing the toxicity of cigarette smo...
Humans Cigarette Smoking Machine Learning Oxidative Stress Tobacco Products Reactive Oxygen Species Smoke
View on PubMed DOI

A Comparison of SVM and CNN-LSTM Based Approach for Detecting Smoke Inhalations from Respiratory signal.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Wearable sensors have successfully been used in recent studies to monitor cigarette smoking events and analyze people's smoking behavior. Respiratory inductive plethysmography (RIP) has been employed to track breathing and to identify characteristic ...
Plethysmography Humans Smoke Neural Networks, Computer Wearable Electronic Devices Machine Learning Support Vector Machine Algorithms Smoking
View on PubMed DOI
Popular Topics
Recent Journals