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Graph-processing platforms are increasingly used in a variety of domains. Although both industry and academia are developing and tuning graph-processing algorithms and platforms, the performance of graph-processing platforms has never been explored or compared in-depth. Thus, users face the daunting challenge of selecting an appropriate platform for their(More)
We are only starting to understand how people behave when they are part of a crowd. This article presents a novel approach for the study and management of crowds. The approach comprises of a device to be worn by individuals, an infrastructure to collect the information from the devices, a set of algorithms for recognizing crowd dynamics, and a set of(More)
Mining large-scale graphs is increasingly important, as it provides a powerful way of extracting useful information from real-world data. Efficient processing of that volume of information requires partitioning the graph across multiple nodes in a distributed system. However, traversing edges across distributed partitions results in significant performance(More)
Processing graphs, especially at large scale, is an increasingly useful activity in a variety of business, engineering, and scientific domains. Already, there are tens of graph-processing platforms, such as Hadoop, Giraph, GraphLab, etc., each with a different design and functionality. For graph-processing to continue to evolve, users have to find it easy(More)
Many real-world systems, such as social networks, rely on mining efficiently large graphs, with hundreds of millions of vertices and edges. This volume of information requires partitioning the graph across multiple nodes in a distributed system. This has a deep effect on performance, as traversing edges cut between partitions incurs a significant(More)
Understanding the social dynamics of a group of people can give new insights into social behavior. Physical proximity between individuals results from the interactions between them. Hence, measuring physical proximity is an important step towards a better understanding of social behavior. We discuss a novel approach to sense proximity from within the social(More)
In this paper, we present an approach to understand the response of an audience to a live dance performance by the processing of mobile sensor data. We argue that exploiting sensing capabilities already available in smart phones enables a potentially large scale measurement of an audience's implicit response to a performance. In this work, we leverage both(More)
Here we report the experimental observation of circular dichroism in the second-harmonic field (800-400 nm conversion) generated by self-organized gold nanowire arrays with subwavelength periodicity (160 nm). Such circular dichroism, raised by a nonlinear optical extrinsic chirality, is the evident signature of the sample morphology. It arises from the(More)