Improvement of Web Performance Using Optimized Prediction Algorithm and Dynamic Webpage Content Updation in Proxy Cache

Author(s):  
K. Shyamala ◽  
S. Kalaivani
2019 ◽  
Vol 8 (3) ◽  
pp. 7791-7796

Improving web performance is becoming more hectic in recent days. This paperelucidates the combination of many ideas to improve web performance and given as a framework. The entire framework depicts various aspects in improving web access performance which includes website reorganization, webpage prediction and prefetching, optimized way of accessing prediction algorithm in webserver and finally improvements in a proxy cache at the time of accessing dynamic content. Each portion of the framework has been successfully proposed and implemented. The various algorithms have been introduced in each portion of the implementation. This research work not only introduced new algorithms but also create scope for further research works in terms of improving web performance.


2018 ◽  
Author(s):  
Annice Kim ◽  
Robert Chew ◽  
Michael Wenger ◽  
Margaret Cress ◽  
Thomas Bukowski ◽  
...  

BACKGROUND JUUL is an electronic nicotine delivery system (ENDS) resembling a USB device that has become rapidly popular among youth. Recent studies suggest that social media may be contributing to its popularity. JUUL company claims their products are targeted for adult current smokers but recent surveillance suggests youth may be exposed to JUUL products online. To date, there has been little attention on restricting youth exposure to age restricted products on social media. OBJECTIVE The objective of this study was to utilize a computational age prediction algorithm to determine the extent to which underage youth are being exposed to JUUL’s marketing practices on Twitter. METHODS We examined all of @JUULvapor’s Twitter followers in April 2018. For followers with a public account, we obtained their metadata and last 200 tweets using the Twitter application programming interface. We ran a series of classification models to predict whether the account following @JUULvapor was an underage youth or an adult. RESULTS Out of 9,077 individuals following @JUULvapor Twitter account, a three-age category model predicted that 44.9% are 13 to 17 years old (N=4,078), 43.6% are 18 to 24 years old (N=3,957), and 11.5% are 25 years old or older (N=1,042); and a two-age category model predicted that 80.6% (N=7,313) are under 21 years old. CONCLUSIONS Despite a disclaimer that followers must be of legal age to purchase tobacco products, the majority of JUUL followers on Twitter are under age. This suggests that ENDS brands and social media networks need to implement more stringent age-verification methods to protect youth from age-restricted content.


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