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With the widespread use of identification systems, establishing authenticity with sensors has become an important research issue. Among the schemes for making authenticity verification based on information security possible, reversible data hiding has attracted much attention during the past few years. With its characteristics of reversibility, the scheme is required to fulfill the goals from two aspects. On the one hand, at the encoder, the secret information needs to be embedded into the original image by some algorithms, such that the output image will resemble the input one as much as possible. On the other hand, at the decoder, both the secret information and the original image must be correctly extracted and recovered, and they should be identical to their embedding counterparts. Under the requirement of reversibility, for evaluating the performance of the data hiding algorithm, the output image quality, named imperceptibility, and the number of bits for embedding, called capacity, are the two key factors to access the effectiveness of the algorithm. Besides, the size of side information for making decoding possible should also be evaluated. Here we consider using the characteristics of original images for developing our method with better performance. In this paper, we propose an algorithm that has the ability to provide more capacity than conventional algorithms, with similar output image quality after embedding, and comparable side information produced. Simulation results demonstrate the applicability and better performance of our algorithm.

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In an aging population with a changing demographic structure, the government aims to ensure that elderly people receive care. In the concept of lifelong learning, education opportunities are available to senior learners, not just children and young people. The sustainable development for senior learners becomes a very important issue because it promotes a variety of learning activities for senior learners. Many universities have started to offer education for senior learners in Taiwan. Positive experiences for senior learners in senior universities can be fostered by ensuring the sustainable development of senior education. In this paper, a study on sustainable development for senior learners is proposed. This study aims to explore potential tools or approaches in evaluating the sustainable development for senior learners for decision making. In this study, two approaches are applied to analyze the sustainable development for senior learners. The first is a statistical analysis, and the second is the random forest model. The methodology of statistical analysis focuses on three aspects such as social assistance, inspiration, and the learning fulfillment for senior learners in senior universities. The random forest model is used to generate decision rules to support decision making. The random forest in this study obtained 22 decision rules. The results suggest that the items in the questionnaire and the decision rules from random forest could provide useful information that allows decision-makers to analyze the sustainable development of senior learners.

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