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With the application and popularity of social software, online social networks have become crucial for group security research. The social network community detection algorithm can divide the target group into different sub-communities according to the attributes and structure of the group members. Based on the ego network community detection algorithm, this paper adopts the method suitable for graph structure, and integrates the idea of cluster validity index with the community detection algorithm to complete the selection of the optimal number of communities. And compared three kinds of cluster validity indexes, this paper solves the problem that the number of communities needs to be artificially specified, and improves the accuracy of the community detection algorithm. Thus, targeted social network community detection becomes more practical.

It has become clear that on-chip storage is criticalfor most applications on FPGAs. In order to utilize onchip storage efficiently, scholars have done some researches on implementing user memory models with embedded single-port and dual-port arrays. Their work is based on the assumption that user memory models are either single-port or dual-port. However, in some applications, user memory models require 3 or more than 3 ports. Thus, we propose a novel mapping technique in this paper. The principle of this mapping technique is to interleave dual-port arrays to create Nport memory mapping. Data in different arrays can be accessed simultaneously while accessing the same array at the same time will cause conflict. In order to reduce conflict, we use block access mode in our design. Besides, port importance hierarchy is proposed for flexible conflict handling. Experiment results that,compared to the use of distributed rams, our design is a better choice to implement N-port memory.