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Therefore, in this paper, we design a new modularization quality measure based on the similarity, labeled as MS, to automatically guide optimization algorithms to find a good partition of software systems which considers both global modules and edge directions.
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The Good partition contains pairs of images that are considered easy to recognize.
With subsequent iterations the modularity increased, ultimately converging to a maximum of 0.58, indicative of a good partitioning compared to the randomized network, as mentioned in [15], [20].
A good partitioning scheme is a tradeoff of some constraints, such as power, size, performance, and so on.
By assumption, high values of modularity Q indicate good partitions.
The result is a tremendously large partition solution space and a huge variety of approaches to finding good partitions.
The lack of experience many US students get with partitioning partially explains why it took many probable aTNS and ENS students multiple tries to get a good partitioning or why they did not attempt to make an accurate partitioning.
The proposed method is fast, with good partitions' accuracy determination.
Good reviews of the software are coming in.
There's a good supply of affordable software.
This can be supported by good documentation of the software.
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