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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Speculative Control Mechanism of Cloud Computing Systems Based on Emergency Disaster Information Using SDN
No full textAbstractIn recent years, a Cloud computing system has been popularly used. Among them, a hybrid Cloud is focused, which combined a public Cloud operated by service providers and a private Cloud constructed inside a company. Because a private Cloud is considered to be secure and a public Cloud is scalable, it is possible to build a Cloud computing system that works effectively by combining the both types of Clouds. However, when a big disaster occurrs, huge volume of data is produced by monitoring censors and users, and flowed into such an information infrastructure. In addition, enormous number of people access to the system in such a case, thus a load of the system becomes extremely high in a short time. Therefore, it is important to change an environment dynamically among inter-Cloud and intra-Cloud to deal with the load. In this paper, bursty increasing load is predicted based on Earthquake Early Warning (EEW), and a speculative control is performed in a short time between a time of occurrence of an earthquake and a time when the system is heavily loaded actually. In addition, network traffic is controlled to give a higher priority to important data replication. The system is constructed on a Cloud computing platform using public domain software, OpenStack in this experiment. Network traffic of the system is controlled by Software Defined Network (SDN), which is controlled by the OpenFlow protocol. As a result of an evaluation, our proposed system works fine and achieves good performance
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