On-line, real time monitoring of exhaled trace gases by SIFT-MS in the perioperative setting: a feasibility study

The Analyst ◽  
2011 ◽  
Vol 136 (16) ◽  
pp. 3233 ◽  
Author(s):  
Piers R. Boshier ◽  
Julia R. Cushnir ◽  
Vikash Mistry ◽  
Alison Knaggs ◽  
Patrik Španěl ◽  
...  
Keyword(s):  
Real Time ◽  
Feasibility Study ◽  
Trace Gases ◽  
Real Time Monitoring ◽  
On Line

Magnetoelastic Viscosity Sensor for Lubricant Oil Condition Monitoring

2011 ◽  
Vol 495 ◽  
pp. 71-74
Author(s):  
I. Bravo-Imaz ◽  
A. García-Arribas ◽  
E. Gorritxategi ◽  
M. Hernaiz ◽  
A. Arnaiz ◽  
...  
Keyword(s):  
Real Time ◽  
Condition Monitoring ◽  
Environmental Issues ◽  
Real Time Monitoring ◽  
Oil Viscosity ◽  
Lubricant Oil ◽  
On Line ◽  
Magnetoelastic Materials ◽  
Working Device

Actual trends in machinery maintenance point to the necessity of an on-line real-time monitoring of the condition of the lubricant oil. Excessive delay in replacing the lubricant oil can have catastrophic results, whereas doing it too early produces evident economic and environmental issues. Magnetoelastic materials offer a good sensing principle for assessing lubricant oil viscosity; which is one of the most important properties to assure its proper lubricant capacity. Among others, one of the most remarkable properties of this sensing principle is the capability of being used through a wide viscosity range. In this work, we describe the experiments performed to evaluate the usefulness of this technology for testing the viscosity of different test oils in order to develop a working device for on-line, real-time monitoring the quality of lubricant oils.

scholarly journals Remote daily real-time monitoring in patients with COPD – A feasibility study using a novel device

2009 ◽  
Vol 103 (9) ◽  
pp. 1320-1328 ◽  
Author(s):  
Z.M. Sund ◽  
T. Powell ◽  
R. Greenwood ◽  
N.A. Jarad
Keyword(s):  
Real Time ◽  
Feasibility Study ◽  
Real Time Monitoring ◽  
Novel Device

Development and Application of On-Line Monitor for the ZLW-1 Axis Cracks

2014 ◽  
Vol 709 ◽  
pp. 469-472
Author(s):  
Jian Guo Jin ◽  
Zhan Zhou Wang
Keyword(s):  
Acoustic Emission ◽  
Real Time ◽  
Pressure Vessels ◽  
Automatic Recording ◽  
Real Time Monitoring ◽  
On Line

This article mainly introduces a method that uses acoustic emission techniques to achieve on-line monitor for the shaft cracks and crack growth.According to this method,axis crack monitor is produced by acoustic emission techniques.This instrument can apply to all the pressure vessels,pipelines and rotor machines that can bear buckling load.It has the online real-time monitoring,automatic recording,printing,sound and light alarm,collecting crack information function.After a series of tests in both laboratory and field,it shows that this instrument is very versatile and possesses broad prospects of development and application.

Real-Time Monitoring Visualization Through On-Line Simulation

2008 ◽  
Author(s):  
Azzedine Boukerche ◽  
Regina B. Araujo ◽  
Fabio M. Iwasaki ◽  
Ednaldo Pizzolato
Keyword(s):  
Real Time ◽  
Real Time Monitoring ◽  
On Line

IoT-based Flood Depth Sensors in Artificial Intelligent Urban Flood Warning Systems

2020 ◽  
Author(s):  
Li-Chiu Chang ◽  
Fi-John Chang
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Value Added ◽  
Flood Forecasting ◽  
Flood Inundation ◽  
Disaster Prevention ◽  
Real Time Monitoring ◽  
Flood Depth ◽  
Flood Warning ◽  
On Line

<p>In the face of increasingly flood disasters, on-line regional flood inundation forecasting in urban areas is vital for city flood management, while it remains a significant challenge because of the complex interactions and disruptions associated with highly uncertain hydro-meteorological variables and the lack of high-resolution hydro-geomorphological data. Effective on-line flood forecasting models through the rapid dissemination of inundation information regarding threatened areas deserve to develop appropriate technologies for early warning and disaster prevention. Artificial Intelligence (AI) becomes one of the popular techniques in the study of flood forecasts in the last decades. We apply the AI techniques with the newly implemented IoT-based real-time monitoring flood depth data to build an urban AI flood warning system. The AI system integrates the self-organizing feature mapping networks (SOM) with the recurrent nonlinear autoregressive with exogenous inputs network (R-NARX) for modelling the regional flooding prediction. The proposed AI model with the IoT-based real-time monitoring flood depth datasets can increase the value-added application of diversified disaster prevention information and improve the accuracy of flood forecasting. We develop an on-line correction algorithm for continuously learning and correcting model’s parameters, automatic operation modules, forecast results output modules, and web page display interface. The proposed AI system can provide the smart early flooding warnings in the urban area and help the Water Resources Agency to promote the intelligent water disaster prevention services.</p><p>Keywords:</p><p>Artificial Intelligence (AI); Artificial Neural Networks (ANN); Internet of Things (IoT); Regional flood inundation forecast; Spatial-temporal distribution</p>

Optimisation of SFE method on-line coupled to FT-IR spectroscopy for the real-time monitoring of the extraction of tagitinin C in T. diversifolia

2007 ◽  
Vol 40 (3) ◽  
pp. 368-375 ◽  
Author(s):  
E. Ziemons ◽  
N. Wandji Mbakop ◽  
E. Rozet ◽  
R. Lejeune ◽  
L. Angenot ◽  
...  
Keyword(s):  
Ir Spectroscopy ◽  
Real Time ◽  
Real Time Monitoring ◽  
The Real ◽  
On Line ◽  
Ft Ir ◽  
Ft Ir Spectroscopy
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