In this work, we expect that device discovery uses uplink resources based on reusing the uplink transmission chain [17] Therefore, to ensure the excellent performance of device discovery, shared radio resources are suggested alternately with dedicated radio resources.
Regarding to this research branch, RST is often integrated with other traditional clustering algorithms in order to improve the detection performance of community discovery [69, 70].
We then analyze the performance of the discovery algorithms relative to their average number of hop, success rates and bandwidth consumption.
Empirical tests evaluate the performance of competing discovery operations in terms of their results when applied to the same empirical data sets.
This algorithm improves the performance of route discovery by ameliorating the cost of route establishment using a history-based Bayesian method together with the relative region information of the destination node.
However, the fact that it also achieves respectable coverage values is quite disturbing and casts certain doubts on enrichment and coverage as the only measures to assess the performance of module discovery programs.
Given that the number of the tissues (29) is much less than that of the genes (6,200) in the expression data, we first evaluated the performance of module discovery by adjusting the condition threshold (Tc = 1.0, 1.55, 1.75 1.75 and 2.0), while the gene threshold (Tg) was fixed at a somewhat arbitrary value, 3.0.
The effects of different supervised learning methods on the performance of link discovery.
2. The effect of the parameters min-support and margin on the performance of link discovery.
3. The effect of the proposed features for each concept pair, such as CFEC, Semantic-CFEC and Author-Jaccard, on the performance of link discovery.
These measures are commonly used to assess the performance of motif discovery algorithms, for example, in the studies of Hu et al. (2005) and Tompa et al. (2005).
