Real-Time Data Analysis Using a Smartphone Mobile Application

2018 ◽  
pp. 221-240 ◽  
Author(s):  
Sumudu Hasala Marakkalage ◽  
Billy Pik Lik Lau ◽  
Sanjana Kadaba Viswanath ◽  
Chau Yuen ◽  
Belinda Yuen
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Mobile Application ◽  
Time Data ◽  
Real Time Data

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

scholarly journals Research on Security Framework of Mobile Application in Dispatch and Control Domain of Power Grid

2018 ◽  
Vol 173 ◽  
pp. 02029
Author(s):  
XU Jiahui ◽  
YU Hongyuan ◽  
WANG Gang ◽  
WANG Zi ◽  
BAI Jingjie ◽  
...  
Keyword(s):  
Real Time ◽  
Mobile Application ◽  
Power Grid ◽  
Rapid Development ◽  
Mobile Internet ◽  
Internet Technology ◽  
Security Framework ◽  
Time Data ◽  
Real Time Data ◽  
And Control

The rapid development of mobile Internet technology and the wide spread of smart terminals have brought opportunities for the transformation of power grid business model. Compared to the non-real-time information, the real-time and running data of dispatch and control domain is easy to be intercepted and cracked. To solve this problem, this paper presents a new approach to mobile application security framework for the power grid control field. It is to realize secondary encryption by using the method of MD5+AES mixed encryption algorithm and combining the time stamp in real-time data transmission process. At the same time it is to prevent cross-border operations and brute force by using Token authentication and Session technology. China EPRI safety test results show that the application of the framework significantly improves the integrity, safety and reliability of real-time data in power grid control.

scholarly journals Real Time Data Analysis With the ATLAS Trigger at the LHC in Run-2

2020 ◽  
Vol 67 (9) ◽  
pp. 2128-2135
Author(s):  
Pierre-Hugues Beauchemin
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Time Data ◽  
Real Time Data

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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