scholarly journals Signal detection based on time‐to‐onset: extending a new method from spontaneous reports to observational studies

2014 ◽  
Vol 23 (8) ◽  
pp. 849-858 ◽  
Author(s):  
Lionel Van Holle ◽  
Fernanda Tavares Da Silva ◽  
Vincent Bauchau
Keyword(s):  
Signal Detection ◽  
Observational Studies ◽  
New Method ◽  
Spontaneous Reports ◽  
Time To Onset

Brand new method for magneto-optical signal detection with ultraresolution

1995 ◽  
Author(s):  
Hideyoshi Horimai ◽  
Katsuhiro Seo ◽  
Kiyoshi Toyota ◽  
Kimihiro Saito
Keyword(s):  
Signal Detection ◽  
Optical Signal ◽  
New Method

Detection of Network Intrusion Signal in Deep Camouflage Based on Chaotic Synchronization

2013 ◽  
Vol 380-384 ◽  
pp. 2695-2698
Author(s):  
Cai Tian Zhang ◽  
Yi Bo Zhang
Keyword(s):  
Signal Detection ◽  
Expectation Maximization ◽  
Detection Method ◽  
Expectation Maximization Algorithm ◽  
Gaussian Mixture ◽  
Chaotic Synchronization ◽  
New Method ◽  
Network Data ◽  
Network Intrusion ◽  
Better Than

For detecting the network intrusion signal in deep camouflage precisely and effectively, a new detection method based chaotic synchronization is proposed in this paper. The Gaussian mixture model of the network data combined with expectation maximization algorithm is established firstly for the afterwards detection, the chaotic synchronization concept is proposed to detect the intrusion signals. According to the simulation result, the new method which this paper proposed shows good performance of detection the intrusion signals. The detection ROC is plotted for the chaotic synchronization detection method and traditional ARMA method, and it shows that the detection performance of the chaotic synchronization algorithm is much better than the traditional ARMA detection method. It shows good application prospect of the new method in the network intrusion signal detection.

Data-Driven Sizing Specification Utilizing Consumer Text Reviews

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Rushtin Chaklader ◽  
Matthew B. Parkinson
Keyword(s):  
Data Mining ◽  
Observational Studies ◽  
New Method ◽  
Preliminary Design ◽  
Specific Product ◽  
Consumer Reviews ◽  
Design Specifications ◽  
Product Features ◽  
Large Numbers ◽  
Automated Tool

The objective of this work is to introduce a new method for determining preliminary design specifications related to human-artifact interaction. This new method uses data mining of large numbers of consumer reviews. User opinion on specific product features can be time-consuming or expensive to obtain through traditional methods including surveys, experiments, and observational studies. Data mining review text of already released products may be a potentially less time consuming and costly method. Previously established methods of determining design for human variability information from consumer reviews, such as the frequency and accuracy summation (FAS) number and subsequent manual analysis, are explored. The weighted phrase rating (WPR), a new metric which can be an automated tool to quickly analyze consumer reviews, is also introduced. It does not require manual parsing of the reviews, which extends its applicability to larger review pools. This new method is shown to quickly and economically provide information useful to the establishment of design specifications.

Sign in / Sign up

Export Citation Format

Share Document