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However, network distance and resource availability have great impact on MapReduce applications running over the Internet.
A small-world network is characterized by short network distance a high clustering coefficient.
The length from the location of VMS to the parking space is the nearest network distance.
Our findings revealed housing sales prices increased as network distance to the nearest light rail transit and streetcar station decreased.
Four models were evaluated: Euclidean distance, road network distance, road network distance via intervening markets, and a least-cost path model designed to approximate wild waterbird travel using niche modeling and circuit theory.
In addition, an extended ANN-based technique which, uses the proposed neural network distance relay as its basis is described.
The results indicate that the network distance from the UDBs did not have a significant effect on residential property value.
We study a model of network formation where the benefits from connections exhibit decreasing returns and decay with network distance.
Then considering the specialties of network distance computation problem, an efficient way supported by flow extension simulation is proposed.
Network distance calculations were performed via the networkX python library.
The information-theoretic network distance is therefore a useful macroscopic descriptor of similarity.
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