• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.148-153
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• 2022

In keeping with the fourth industrial revolution, IoT-based environments are being implemented everywhere, and as a result, there is an increasing number of cases in which various types of sensed data are utilized efficiently. In particular, the number of multimedia application cases using smart devices is increasing, and there is an increasing number of cases in which large amounts of data are used as fast and convenient as small amounts of data. Given the increasing size of files used in smart devices, the study designed a modified Htree based on journaling meta data management in Ext4-based smart devices and analyzed performance through experiments of various methods. Performance evaluation analysis using IOZone and Hdread shows that the data size of 100Mbyte compared to the data input / output of existing htree is 10% or more, and that of the super large capacity file of 500Mbyte or more is 5% or more.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.279-286
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• 2005

The objective of this study is to suggest a credit scoring model of a capital company's customers by integration of multiple classifiers using genetic algorithm. For this purpose , an integrated model is derived in two phases. In first phase, three types of classifiers MLP (Multi-Layered Perceptron), RBF (Radial Basis Function) and linear models - are trained, in which each type has three ones respectively so htat we have nine classifiers totally. In second phase, genetic algorithm is applied twice for integration of classifiers. That is, after htree models are derived from each group, a final one is from these three, In result, our suggested model shows a superior accuracy to any single ones.