By N. R. Shetty, N.H. Prasad, N. Nalini
This court cases quantity covers the complaints of ERCICA 2015. ERCICA presents an interdisciplinary discussion board for researchers, specialist engineers and scientists, educators, and technologists to debate, debate and advertise learn and know-how within the upcoming components of Computing, info, conversation and their purposes. The contents of this publication hide rising learn parts in fields of Computing, info, communique and functions. it will end up precious to either researchers and working towards engineers.
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This would improve the browsing experience of the user and motivate the user to buy products online. References 1. : Using genetic algorithm for dynamic and multiple criteria web-site optimizations. Eur. J. Oper. Res. 176(3), 1767–1777 (2007) 2. : Usability testing for web sites learning for the global community. In: Seventh Annual Hypermedia ‘95 Conference, 1995 3. : Facilitating effective user navigation through website structure improvement. IEEE Trans. Knowl. Data Eng. 25(3), 571–588 (2013) 4.
1 Power Divider Power divider is used in power splitting, fault testing in transmission line and in other applications related to processing of signal. Power divider receives an input signal and gives multiple output signals. This is a passive device, which divides RF signal into different signals [5]. Power dividers properties include, equal amplitude, Zero degrees phase among the output ports, high isolation between output signals, impedance matching at ports. Typical power divider is shown in the Fig.
G. g. g. RT”), punctuations and exclamation marks. Replace all the words in the CAPs by lowercase. Do the spell corrections for slang words. Replace all the emoticons with their sentiment words. Remove all stop words. Now do the tokenization of the tweets collected. In sentiment analysis use of n-grams framework is preferable; if the number of n selected is 2 or 3 g will yield good results. But in our case we have taken 1-g framework. In this analysis the number of occurrences of the words/token in the tweet will not make a difference, as Binarized version of the algorithms perform better on single occurrences then multiple.