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The world is facing problems, such as uneven distribution of medical resources, the growing chronic diseases, and the increasing medical expenses. Blending the latest information technology into the healthcare system will greatly mitigate the problems. This paper presents the big health application system based on the health Internet of Things and big data. The system architecture, key technologies,...
With the highly demanded requirements for manipulating large scientific datasets, scientists are in need of flexible cluster-level software to execute fast scientific data analysis. In this paper, we discuss whether the Apache Spark framework is suitable for scientific data management. We present our system SparkArray, which extends Spark with a multidimensional array data model and a set of common...
Currently the research of face recognition mostly aim on little internal face of simple environment and carried out on single computer, which limited the application of face recognition. The emergence of big data technology make parallel compute more easy, which make big scale compute work could be accomplished in very short time. An dynamic face recognition system was put forward in this paper. The...
Words and texts are particularly important big data sources for intelligent transportation systems. There is relevance between the traffic condition and the text content which people published in the internet within a period of time. In order to predict traffic condition by the text content we need to analysis these words and texts for all kinds of means. Many traditional researches on neuro linguistic...
Current major big data analytical stacks often consist of a general purpose, multi-staged computation framework (e.g. Hadoop) and an SQL query system (e.g. Hive) on its top. A key factor of query performance is the efficiency of data shuffling between two execution stages (e.g. Map/Reduce). In current data shuffling, various useful information about the shuffled data and the query on the data is simply...
Data center is the infrastructure in big data processing, which constructs computing platform by distributed computer. The paper aims to investigate the analytical model by adopting queueing theory in data center of big data. The new queueing model developed fits the MapReduce programming model accurately and discovers the nature of the programming model. The utilizations and mean waiting times of...
Equi-join is heavily used in MapReduce-based log processing. With the rapid growth of dataset sizes, join methods on MapReduce are extensively studied recently. We find that existing join methods usually cannot get high query performance and affordable storage consumption at the same time when faced with a huge amount of log data. They either only optimize one aspect but significantly sacrifice the...
With the constantly emerging of new ways to release information on the internet, together with the rise of several other technologies such as cloud computing and the internet of things, data is explosively growing at an unprecedented speed, manifesting the coming of the era of big data. Facing the challenge of large-scale, demand diversity and real-time processing for big data, the efficient processing...
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