Abstract-For it can identify the clusters with any shape and tackle the boundary points effectively, the typical density-based method of DBSCAN was widely applied to the clustering analysis. But the algorithm still has some shortcomings, such as the high time complexity, clustering effect is very dependent on the initial value of the parameter, and the low accuracy of the boundary points tackling processes. This paper put forward GO-DBSCAN, which based on the DBSCAN and OPTICS algorithms. GO-DBSCAN improved the accuracy while processing the boundary points, that cause of it introduced the minimum acceptable distance of OPTICS. In order to reduce the time complexity of clustering processes, it also proposed the method of grid-based query while it retraverse the neighborhood. At the end of this paper, we proved that GO-DBSCAN would perform better both on the accuracy of boundary points processing and time complexity.
DC-DC converters are required to supply various levels of voltages from batteries to different systems. In order to extend the lifetime of battery, it is very important to optimize the efficiency of the DC-DC converter, especially the light load efficiency. In this paper, considerations of the efficiency variation of a PWM synchronous buck-boost converter are made to minimize the power loss. Several new techniques such as channel width regulation, variable threshold voltage, switch activation and gate charge modulation are used. Simulation results show that the efficiency can be improved by more than 15% when the converter works on its light load.Index Terms-buck-boost converter, efficiency optimization, channel width regulation, variable threshold voltage, switch activation I.
Abstract:As the rapid development of social media, microblog has arrested a lot of attention. However, the automatic information extraction task of the microblog is relatively rare because the microblog text is quite complex and irregular. In this paper, we utilized dependency trigram kernel to construct persons relations extraction model. Firstly, we described the dependency trigram kernel (DTK) for relations extraction. Secondly, we used words semantic similarity tool HowNet to improve semantic similarity of dependency trigram's words. And then we proposed "(POS,GR) (Part of Speech,Grammatical role)" pair to improve dependency trigram's words syntax similarity. Finally, we evaluated the validity of the relation extraction model by experimenting, and the results of experiment show that the F-value of our improved DTK is higher than original DTK for microblog persons relation extraction.
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