scholarly journals A multiyear dust devil vortex survey using an automated search of pressure time series

2015 ◽  
Vol 120 (3) ◽  
pp. 401-412 ◽  
Author(s):  
Brian Jackson ◽  
Ralph Lorenz
Keyword(s):  
Time Series ◽  
Dust Devil ◽  
Pressure Time ◽  
Automated Search

DYNAMICS UNDERLYING PATIENT-VENTILATOR INTERACTIONS DURING NOCTURNAL NONINVASIVE VENTILATION

2012 ◽  
Vol 22 (02) ◽  
pp. 1250030 ◽  
Author(s):  
R. NAECK ◽  
D. BOUNOIARE ◽  
U. S. FREITAS ◽  
H. RABARIMANANTSOA ◽  
A. PORTMANN ◽  
...  
Keyword(s):  
Time Series ◽  
Respiratory Failure ◽  
Shannon Entropy ◽  
Noninvasive Ventilation ◽  
Spontaneous Breathing ◽  
Sleep Stages ◽  
Common Procedure ◽  
Pressure Time ◽  
Ventilatory Assistance

Noninvasive ventilation is a common procedure for managing patients having chronic respiratory failure. The success of this ventilatory assistance is often linked with patient's tolerance that is known to be related to the quality of the synchronization between patient's spontaneous breathing cycles and ventilatory cycles delivered by the ventilator. Thirty-four sleep sessions (more than 5000 ventilatory cycles each) were automatically investigated using a specific algorithm processing airflow and pressure time series. Four groups of patients were defined according to the interplay between asynchrony events and leaks. Different mechanisms that depend on sleep stages were thus evidenced. A Shannon entropy was also proposed as a new sleep fragmentation quantification methodology.

Differences in regression, classification, and multi-task deep learning on pressure time series for range and seabed type

2020 ◽  
Vol 148 (4) ◽  
pp. 2727-2727
Author(s):  
David F. Van Komen ◽  
Kira Howarth ◽  
Tracianne B. Neilsen ◽  
David P. Knobles
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Pressure Time
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