In December 2001, the authors started two kinds of experiments on the meteor burst communication (MBC) in Antarctica to study the ability of MBC as a communication medium for data collection systems in that region. In the first experiment, a continuous tone signal is transmitted from Zhongshan Station. The signal received at Syowa Station (about 1,400 km apart) is recorded and analyzed. This experiment is aimed to study basic properties of the meteor burst channel in that high latitude region. On the other hand, the second experiment is designed to estimate data throughput of a commercial MBC system in that region. A remote station at Zhongshan Station tries to transfer data packets each consisting of 10 data words to the master station at Syowa Station. Data packets are generated with five minutes interval. In this paper, we explain the experiments, briefly examine the results of the first year (from April 2002 to March 2003), and put forward the plan for the experiments in the second and third year. From the data available thus far, we can see that 1) the sinusoidal daily variation in the meteor activity typical in middle and low latitude regions can not be clearly seen, 2) non-meteoric propagations frequently dominate the channel especially during night hours, 3) about 60% of the generated data packets are successfully transferred to the master station within two hours delay even though we are now operating the data transfer system only for five minutes in each ten minutes interval, etc.

Social networks often demonstrate hierarchical community structure with communities embedded in other ones. Most existing hierarchical community detection methods need one or more tunable parameters to control the resolution levels, and the obtained dendrograms, a tree describing the hierarchical community structure, are extremely complex to understand and analyze. In the paper, we propose a parameter-free hierarchical community detection method based on micro-community and minimum spanning tree. The proposed method first identifies micro-communities based on link strength between adjacent vertices, and then, it constructs minimum spanning tree by successively linking these micro-communities one by one. The hierarchical community structure of social networks can be intuitively revealed from the merging order of these micro-communities. Experimental results on synthetic and real-world networks show that our proposed method exhibits good accuracy and efficiency performance and outperforms other state-of-the-art methods. In addition, our proposed method does not require any pre-defined parameters, and the output dendrogram is simple and meaningful for understanding and analyzing the hierarchical community structure of social networks.