scholarly journals Estimation and prediction of weather variables from surveillance data using spatio-temporal Kriging

Author(s):  
Ramon Dalmau ◽  
Marc Perez-Batlle ◽  
Xavier Prats
2012 ◽  
Vol 3 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Stephen G. Jones ◽  
William Conner ◽  
Bo Song ◽  
David Gordon ◽  
Anand Jayakaran

PLoS ONE ◽  
2017 ◽  
Vol 12 (2) ◽  
pp. e0170658 ◽  
Author(s):  
Pierre Bougnères ◽  
Sophie Le Fur ◽  
Sophie Valtat ◽  
Yoichiro Kamatani ◽  
Mark Lathrop ◽  
...  

PLoS Medicine ◽  
2016 ◽  
Vol 13 (10) ◽  
pp. e1002140 ◽  
Author(s):  
Margarita Pons-Salort ◽  
Natalie A. Molodecky ◽  
Kathleen M. O’Reilly ◽  
Mufti Zubair Wadood ◽  
Rana M. Safdar ◽  
...  

2015 ◽  
Vol 57 (1) ◽  
Author(s):  
Pattreeya Tanisaro ◽  
Julius Schöning ◽  
Kuno Kurzhals ◽  
Gunther Heidemann ◽  
Daniel Weiskopf

AbstractIn this article, we describe the concept of video visual analytics with a special focus on the reasoning process in the sensemaking loop. To illustrate this concept with real application scenarios, two visual analytics (VA) tools are discussed in detail that cover the sensemaking process: (i) for video surveillance, and (ii) for eye-tracking data analysis. Surveillance data (i) allow discussion of key VA topics such as browsing and playback, situational awareness, and the deduction of reasoning. Using example (ii) – eye tracking data from persons watching video – we review application features such as the spatio-temporal visualization along with clustering, and identification of attentional synchrony between participants. We examine how these features can support the VA process. Based on this, open challenges in video VA will be discussed.


2013 ◽  
Vol 142 (8) ◽  
pp. 1614-1624 ◽  
Author(s):  
A. R. DOMINGUES ◽  
A. R. VIEIRA ◽  
R. S. HENDRIKSEN ◽  
C. PULSRIKARN ◽  
F. M. AARESTRUP

SUMMARYThis study evaluates the usefulness of spatio-temporal statistical tools to detect outbreaks using routine surveillance data where limited epidemiological information is available. A dataset from 2002 to 2007 containing information regarding date, origin, source and serotype of 29 586 Salmonella isolates from Thailand was analysed. Data was grouped into human and non-human categories and the analysis was performed for the top five occurring serovars for each year of the study period. A total 91 human and 39 non-human significant spatio-temporal clusters were observed, accounting for 11% and 16% of the isolates, respectively. Serovar-specific associations between human and non-human clusters were also evaluated. Results show that these statistical tools can provide information for use in outbreak prevention and detection, in countries where only limited data is available. Moreover, it is suggested that monitoring non-human reservoirs can be relevant in predicting future Salmonella human cases.


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