A Weighted Algorithm for Watermarking Relational Databases

A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.

深度神经网络在阿尔兹海默病预测中的应用分析（英文）

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迁移学习在阿尔茨海默病早期诊断中的应用

阐述了迁移学习方法及其在阿尔茨海默病早期诊断研究领域中的应用.首先,对迁移学习方法在阿尔茨海默病分类诊断研究中的应用进行了分析.接着,介绍了迁移学习相关的理论知识.然后,详细介绍了基于迁移学习算法在阿尔茨海默病诊断研究中的进展,分别从基于样本的迁移、基于特征的迁移和基于模型的迁移等三方面进行了分析.最后,提出了当前迁移学习在该领域存在的问题和挑战以及未来发展趋势.