The short-term forecast of rail transit is one of the most essential issues in urban intelligent transportation system (ITS). Accurate forecast result can provide support for the forewarning of flow outburst and enables passengers to make an appropriate travel plan. Therefore, it is significant to develop a more accurate forecast model. Long short-term memory (LSTM) network has been proved to be effective on data with temporal features. However, it cannot process the correlation between time and space in rail transit. As a result, a novel forecast model combining spatio-temporal features based on LSTM network (ST-LSTM) is proposed. Different from other forecast methods, ST-LSTM network uses a new method to extract spatio-temporal features from the data and combines them together as the input. Compared with other conventional models, ST-LSTM network can achieve a better performance in experiments.
A removable visible watermarking scheme, which operates in the discrete cosine transform (DCT) domain, is proposed for combating copyright piracy. First, the original watermark image is divided into 16ϫ 16 blocks and the preprocessed watermark to be embedded is generated by performing element-by-element matrix multiplication on the DCT coefficient matrix of each block and a key-based matrix. The intention of generating the preprocessed watermark is to guarantee the infeasibility of the illegal removal of the embedded watermark by the unauthorized users. Then, adaptive scaling and embedding factors are computed for each block of the host image and the preprocessed watermark according to the features of the corresponding blocks to better match the human visual system characteristics. Finally, the significant DCT coefficients of the preprocessed watermark are adaptively added to those of the host image to yield the watermarked image. The watermarking system is robust against compression to some extent. The performance of the proposed method is verified, and the test results show that the introduced scheme succeeds in preventing the embedded watermark from illegal removal. Moreover, experimental results demonstrate that legally recovered images can achieve superior visual effects, and peak signal-to-noise ratio values of these images are Ͼ50 dB.
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