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In the meantime, they're working on the pilot of a proposed NBC comedy based on the film. If it flies, the sitcom will expand the movie's premise by locating the call center in urban Bangalore, then populating it with a fully multi-national cast. Picture Australians and Filipinos and Germans working cubicle-by-cubicle alongside Indians and Americans, all trying to make sense of our melting-pot 21st-century marketplace realities. "It will be a global comedy," asserts Jeffcoat.

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Starting on Sunday, May 1, the arts network will also highlight diverse cultures and traditions, connecting with the people of Asia and the Pacific Islands, in a curated on-demand programming lineup. All titles below will be available during the month of May, free to all, on the Ovation NOW app and at the Ovation TV Watch website. The Ovation NOW app is free to download and is available on Roku, Android, Apple TV and iOS devices.

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Real datasets Our bucketization approach can work with any graph. As real datasets, we have chosen two scale-free networks, the Actor network [23] and the Web network [26], and one non-scale-free network, the Citation network [25]. Barabási and Albert [2] have proven that the Actor and the Web network are scale-free. The Actor network contains 1,048,575 edges and 1,137,725 nodes, 89,150 nodes represent actors, and 1,048,575 nodes represent movies. An edge connects a movie with an actor who has played in it. The Actor network exhibits the preferential attachment feature. Namely, if an actor has played in more movies, a casting director is more familiar with his or her skills. Then an actor with a higher degree has higher chances to be considered for a new role. The growth parameter m of the Actor network is 4. The Web network contains 2,381,903 nodes and 2,312,497 edges, and its growth parameter m is 5. The nodes in the Web network are web pages, and the edges represent hyperlinks between them. The Citation network contains 27,770 nodes and 3,52,807 edges. The nodes in the Citation network are articles, an edge is created between articles a and b if article a cites b.

We can see from the analysis of \(P_\textitSQprocessing\), \(P_\textitCQprocessing\) and \(P_\textitTQprocessing\) that the best value to set maxEdges in scale-free networks is the growth parameter m. In scale-free networks, most nodes have a degree equal to m, so most buckets will be full after initialization. For non-scale-free networks, we observe that the best value to set maxEdges is the average degree of the network. For the last experimental results, \(P_RQprocessing\), we set maxEdges to the best option, i.e., \(maxEdges=m\) for the scale-free networks and \(maxEdges=12\), average degree, for the non-scale-free network.


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