In this paper, we propose a four-step guideline to perform twitter mining based on consumer's opinion and adverse drug reaction of certain drugs. Due to advances in technology and increased use of social networks,...
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ISBN:
(纸本)9781450347747
In this paper, we propose a four-step guideline to perform twitter mining based on consumer's opinion and adverse drug reaction of certain drugs. Due to advances in technology and increased use of social networks, there has been a tremendous amount of public data which grows from terabytes to petabytes. The accessibility of this enormous amount of data offers vast research opportunities for extracting meaningful opinion data for many applications. Drug consumption is one that could be benefited, from methodical sentiment analysis techniques. In this paper we have focused on social media mining for drug related information. To clean the Twitter streaming data and to increase the accuracy of the results, a spam filter and a preprocessing procedure have been developed, to retrieve relevant information about certain drug. Processing and analysis of data were done on 1579 tweets using r-programming. The results show that Twitter mining with formed word cloud is a very useful technique to get the majority of consumer's opinion about the consumed drug. The obtained results shows that, real time streaming of social networking data could help in early detection and prediction of side effects of the drug for patient safety.
Today, triple play services may be regarded as required services in telecommunication sector. In the access network, Ethernet Passive Optical Network (EPON) is considered as one of the best solutions to provision trip...
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ISBN:
(纸本)9781538627372
Today, triple play services may be regarded as required services in telecommunication sector. In the access network, Ethernet Passive Optical Network (EPON) is considered as one of the best solutions to provision triple-play-services. In EPON, the Dynamic Bandwidth Allocation (DBA) algorithm plays a key role to meet the Quality-of-Service (QoS) requirements. Therefore, in this paper, we conduct the delay analysis of DBA so that it can provide a better understanding for the network operators when designing and implementing a DBA algorithm. We use machine learning algorithm such as random Forest, Decision Tree, kNN, and Naives Bayes and r-programming to build a prediction model and find the important factors affecting the packet delay in EPON system. We run extensive simulation scenarios to build appropriate dataset for training set and testing set. We found that the cycle time selection has a significant impact on the EF delay, AF delay and BE grant. We also found that there was a strong relationship between the EF delay and AF GrANT. Lastly, we conduct performance evaluation to justify what we found. Simulation results show that cycle time is indeed has significant effect on system performances.
Airport congestion and wait time influences passenger satisfaction levels in terms of overall travel wait time. The wait time depends on mandatory factors like security, immigration and passenger discretionary factors...
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ISBN:
(纸本)9781509010226
Airport congestion and wait time influences passenger satisfaction levels in terms of overall travel wait time. The wait time depends on mandatory factors like security, immigration and passenger discretionary factors like airport shopping, dining, and other activities. Passengers rate airport and airline on-time performance through reviews on wait time like the queue for check-in, immigration, security and customs checks, and boarding times. In this paper, we performed an exploratory analysis of airport wait times on customs, border protection data taken from Top 3 busiest airports (Atlanta, Chicago, and Los Angeles) from the United States of America which handle several million passengers every year. We have applied multiple data visualization techniques based on factors like flight arrivals, the number of passengers, booths serving passengers, time of the day, and seasonality patterns. This paper discusses the comparison on these airports with respect to various visualisation. This work can be extended to all airports and can prescribe further analytical techniques to predict wait times based on historical data.
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