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Smart meters play vital roles in the aspects of the management and operation of smart grids such as demand response, energy efficiency improvement, and electricity pricing. Massive amounts of data are being collected owing to the popularity of smart meters. Two main issues should be addressed in this context. One is the communication and storage of big data from smart meters at reduced cost. The other...
Smart meter plays a vital role in the management of smart grid. Massive electricity consumption data are being collected with the popularity of smart meters, which pushes the electricity demand side into a big data world and poses great challenges to data communication and storage. The residential electricity consumption behaviors vary with different lifestyles and family configurations. It's assumed...
Characteristics of flow describe the pattern and trend of network traffic, it helps network operator understanding network usage and user behavior, especially useful for those who concerns more about network capacity planning, traffic engineering and fault handling. Due to the large scale of datacenter network and explosive growth of traffic volume, it's hard to collect, store and analyze Internet...
Aiming to redundant candidate itemsets and repeated computing existing in presented mining algorithms, this paper proposes an algorithm of fast mining frequent itemsets based on sequence number. To fast execute double search, the algorithm adopts two methods of generating candidate itemsets, one is down search that generating subsets of non frequent itemsets, another is up search that computing their...
Registration of diffusion tensor images has attracted more and more attention in recent years. In this paper a novel affine registration algorithm for diffusion tensor (DT) MR images that enables explicit analytic optimization of tensor reorientation is presented. The objective function captures both the image similarity and tensor reorientation, which is necessary for warping DT images. The final...
A spectral clustering intrusion detection approach is presented in this paper. The basic idea of the approach is to compute the similarities between the training data points, then to construct the affinity matrix, and to get the clusters according the main eigenvector of this affinity matrix. With the classified data instances, anomaly data clusters can be easily identified by normal cluster ratio...
Dealing with imprecise data and composite measure is widely recognized to be the important problem, respectively and has received increasing attention. However, the complexity of queries required to support OLAP applications makes it difficult to implement using standard relational database technoloty. Moreover, there is currently no data model for OLAP to handle both imprecise data and composite...
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