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In this paper, we point out a major issue of stock market regarding trending scenario of trades where data exactness, accuracy of expressing data and uncertainty of values (closing point of the day) are lacked. We use neutrosophic soft sets (NSS) consisting of three factors (True, Uncertainty and False) to deal with exact state of data in several directions. A new approach based on NSS is proposed for stock value prediction based on real data from last 7 years. It calculates the stock price based on the factors like "open", "high", "low" and "adjacent close". The highest score value retrieved from the score function is used to determine which opening price and high price decide the closing price from the above mentioned four factors.

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Robust and invisible watermarking provides a feasible solution to prove the ownership of the genuine content owner. Different watermarking algorithms have been presented by the researchers in the past but no algorithm could be termed as perfect. Proposed work puts forward a novel image-adaptive method of embedding a binary watermark in the image in a transparent manner. Discrete wavelet transform (DWT), singular value decomposition (SVD) and discrete cosine transform (DCT) are used together in the proposed hybrid watermarking scheme. Image-adaptive nature of the scheme is reflected in the usage of only high entropy [Formula: see text] blocks for the watermark embedding. Binary watermark is embedded in the DCT coefficients using a flexible strength derived from the means of the DCT coefficients. This flexible strength factor (SF) has different value for the DCT coefficients originated from different [Formula: see text] blocks. Any desired level of visual quality could be obtained by varying the adjusting parameter of the flexible SF. Side information generated in the watermark embedding is used in the detection of watermark. The presented watermarking technique shows better robustness in comparison to the three contemporary watermarking techniques.

Abstract:The idea of partitioning a host image into small nonoverlapping blocks and embedding the watermark in these blocks based upon some property of the blocks has been in use for many years and is still very popular. While most of the watermarking techniques use a constant strength factor for the whole image, in the present watermarking scheme a flexible strength factor is used, which is derived from the standard deviations of the discrete wavelet transform coefficients of the selected high entropy nonoverlapping blocks. The presented watermarking scheme explains the reverse relationship between imperceptibility and robustness by various plots involving adjusting the parameter of strength factor. A watermarked image of any desired peak signal to noise ratio can be prepared very easily by using this scheme.Three versions of the proposed watermarking scheme are presented here. In the first version the host image is partitioned into 8 × 8 nonoverlapping blocks and these blocks are used in the watermarking. Similarly, in the second and third versions, the host image is partitioned into 16 × 16 and 32 × 32 blocks respectively for their use in watermarking. We compare the results of these three versions with other watermarking schemes and illustrate the greater robustness of all versions of our watermarking scheme. The novelty of the scheme lies in the use of three sizes of nonoverlapping blocks and the flexible strength factor for every block of the image.