Bulk current injection (BCI) test is adopted as an immunity testing method for automotive electronic equipment. In this letter, an analytical method for obtaining the terminal output of the transmission line excited by using the BCI probe is proposed. The test setup is analytically solved by using a circuit concept approach because it is considered to be a transmission line externally excited by an electromagnetic field. To confirm the validity of the proposed method, a single-ended transmission line loaded with the BCI probe is considered as an example. The comparison with the analytical solution and our experimental results shows a good agreement.

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Recently, IaaS services provide not only virtual machines on hypervisors but also Baremetal servers or container based virtual servers. In this paper, we measure performances and start up time of Baremetal server, container servers, virtual machines on OpenStack with virtual server number changing and evaluate quantitative performances.

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Aiming at the next generation forward error correction code (FEC) in the application layer, a RaptorQ code decoding algorithm is proposed in this paper. The proposed index-based decoder significantly reduces the decoding complexity by tabulates the indices of the non-zero entries in the sparse code generator matrix. As the number of tabulated indices is much less than the dimension of the code generator matrix, the computational complexity is up to ten times lower than direct implementation of the Raptor code decoder, the previous version of RaptorQ code. Finally, saving of up to two orders of magnitude in the required memory is also achieved by the proposed solution.

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Detecting SPIT (Spam over Internet Telephony) is an urgent demand in voice communication services. In this paper, we propose a two-stage SPIT detection scheme using BC (Betweenness Centrality) and social trust to decrease misdetection of a call from low-frequent users as SPIT. BC indicates user’s centrality in the entire network and the BC against legitimate users gradually increases with time even if users seldom call. We first use BC to identify a call request from a low-frequent user then judge the call legitimacy by using social trust. By the computer simulation, we show that our scheme improves the detection accuracy.

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