scholarly journals Field Demonstration of a Distributed Microsensor Network for Chemical Detection

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5424
Author(s):  
Jeffrey S. Erickson ◽  
Brandy J. Johnson ◽  
Anthony P. Malanoski
Keyword(s):  
Data Analysis ◽  
Vapor Phase ◽  
Methyl Salicylate ◽  
Field Trials ◽  
Time Data ◽  
Laptop Computer ◽  
Autonomous Operation ◽  
Real Time Data ◽  
Open Housing ◽  
Housing Options

We have developed the ABEAM-15, a custom-built multiplexed reflectance device for the detection of vapor phase and aerosolized chemical plumes. The instrument incorporates fifteen individual sensing elements, has wireless communications, offers support for a battery pack, and is capable of both live and fully autonomous operation. Two housing options have been fabricated: a compact open housing for indoor use and a larger weather-sealed housing for outdoor use. Previously developed six-plex analysis algorithms are extended to 15-plex format and implemented on a laptop computer. We report the results of recent outdoor field trials with this instrument in Denver, CO in a stadium security scenario. Through software, the wireless modules on each instrument were configured to form a six-instrument, star-point topology, distributed microsensor network with live reporting and real-time data analysis. The network was tested with aerosols of methyl salicylate.

scholarly journals Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks

2018 ◽  
Vol 19 (S18) ◽  
Author(s):  
Ahmed Sanaullah ◽  
Chen Yang ◽  
Yuri Alexeev ◽  
Kazutomo Yoshii ◽  
Martin C. Herbordt
Keyword(s):  
Neural Networks ◽  
Data Analysis ◽  
Real Time ◽  
Medical Diagnosis ◽  
Time Data ◽  
Real Time Data

A Systematic Review About Prediction of Academic Behavior Through Data Mining Techniques

2020 ◽  
Vol 17 (11) ◽  
pp. 5162-5166
Author(s):  
Puninder Kaur ◽  
Amandeep Kaur ◽  
Rajwinder Kaur
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Data Analysis ◽  
Educational Data Mining ◽  
Prediction Methods ◽  
Time Data ◽  
Academic Behavior ◽  
Data Mining Techniques ◽  
Real Time Data ◽  
Extract Information

In the IT world, predicting the academic performance of the huge student population poses a big challenge. Educational data mining techniques significantly contribute in providing solution to this problem. There are several prediction methods available for data classification and clustering, to extract information and provide accurate results. In this paper, different prediction methodologies are highlighted for the prediction of real-time data analysis of dynamic academic behavior of the students. The main focus is to provide brief knowledge about all data mining techniques and highlight dissimilarities among various methods in order to provide the best results for the students.

Real-time data analysis using a machine learning model significantly improves prediction of successful vaginal deliveries

2020 ◽  
Vol 223 (3) ◽  
pp. 437.e1-437.e15
Author(s):  
Joshua Guedalia ◽  
Michal Lipschuetz ◽  
Michal Novoselsky-Persky ◽  
Sarah M. Cohen ◽  
Amihai Rottenstreich ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Real Time ◽  
Learning Model ◽  
Time Data ◽  
Machine Learning Model ◽  
Vaginal Deliveries ◽  
Real Time Data
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