In this paper, we present a packet-loss resilient 3-D graphics transmission system that is scalable with respect to both channel bandwidth and channel error characteristics. The algorithm trades off source coding effi...
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ISBN:
(纸本)0780374029
In this paper, we present a packet-loss resilient 3-D graphics transmission system that is scalable with respect to both channel bandwidth and channel error characteristics. The algorithm trades off source coding efficiency for increased bit-stream error resilience to optimize the decoded mesh quality on the client side. It uses the Compressed Progressive Mesh (cpm) algorithm to generate a hierarchical bit-stream representing different levels of details (LODs). We assign optimal for-ward error correction (FEC) code rates to protect different parts of the bit-stream differently. These optimal FEC code rates are determined theoretically via a distortion function that accounts for: the channel packet loss rate, the nature of the encoded 3-D mesh and the error protection bit-budget. We present experimental results, which show that with our unequal error protection (UEP) optimal approach, the decoded mesh quality degrades more gracefully (compared to either no error protection (NEP) or equal error protection (EEP) methods) as the packet loss rate increases.
With the rise of media like microblog, discovering community and analysing the characteristics of network in the microblog network have gradually became a hotspot of research in the field of social network analysis in...
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ISBN:
(纸本)9781479939855
With the rise of media like microblog, discovering community and analysing the characteristics of network in the microblog network have gradually became a hotspot of research in the field of social network analysis in recent years. In this paper, based on the property contents of microblog users namely users' interest, and considering the structural similarity and attribute similarity of cliques got from Clique Percolation Method (cpm algorithm), we improved the CMP algorithm from the perspective of its output by mergering the cliques. This improvement resolves the problems that the definition of clique by cpm algorithm is too strict and does not meet the reality. Then, our research analysed the topic of the communities found by the improved cpm algorithm using Fuzzy Comprehensive Evaluation Method. And we obtained communities with a higher application value finally. In the end, we verified our research using the real data crawling from Sina Weibo, a microblog site which is the most popular in China.
Graph mining is one of the significant tasks in the field of computer science. Most of the applications generate a vast amount of data which is represented with the help of a graph. Due to this graph representation, t...
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Graph mining is one of the significant tasks in the field of computer science. Most of the applications generate a vast amount of data which is represented with the help of a graph. Due to this graph representation, these applications have become complex and increased in size. Finding relevant information from that graph becomes a complicated task. For this community detection algorithms play a vital role in graph partitioning to retrieve relevant information. Finding communities in a graph reduces the complexity of the graph due to related data comes closer to forming a community. Many algorithms have been introduced in the last decade; the Clique percolation method (cpm) is the benchmark algorithm for finding an overlapping community. But in this method, some nodes remain unclassified, nodes that are not part of the clique. Paper proposed the clique-based Louvain algorithm(CBLA), which can classify the non-classified node (NCN) obtained after finding cliques in one of the communities by applying the Louvain algorithm. Louvain algorithm is used to classify the non-overlapped community, but with the help of cliques, it will also detect the overlapped nodes. This paper compared the proposed algorithm with four other benchmark algorithms. The proposed algorithm gives equal or enhanced performance among all compared algorithms.
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