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Smoke

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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
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...

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
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 ...

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

Sensors (Basel, Switzerland)
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 ...

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
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...

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

Environment international
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...

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

International journal of computer assisted radiology and surgery
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 ...

Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling.

Molecules (Basel, Switzerland)
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...