Analysis of image compression methods based on wavelet transforms for maritime applications

The purpose of the article is to develop recommendations for choosing image compression method based on wavelet transformation, depending on image type, quality and compression requirements. Among the wavelet image compression methods, Embedded Zerotree Wavelet coder (EZW) and Set Partition In Hierarchical Trees (SPIHT) are considered, and the Haar wavelet and wavelet transformation in the oriented basis with the first, third, fifth and seventh decomposition levels is used as the base wavelet transform. These compression methods were compared with each other and with the standard JPEG method on the following parameters: mean square error, maximum error, peak to noise ratio, number of bits per pixel, compression ratio, and image size. The proposed methods can be successfully applied in the transmission of seabed relief images obtained from satellites or sea buoys.

Domatically full Cartesian product graphs

The domatic number [Formula: see text] of a graph [Formula: see text] is the maximum number of disjoint dominating sets in a dominating set partition of a graph [Formula: see text]. For any graph [Formula: see text], [Formula: see text] where [Formula: see text] is the minimum degree of [Formula: see text], and [Formula: see text] is domatically full if the equality holds, i.e., [Formula: see text]. In this paper, we characterize domatically full Cartesian products of a path of order 2 and a tree of order at least 3. Moreover, we show a characterization of the Cartesian product of a longer path and a tree of order at least 3. By using these results, we also show that for any two trees of order at least 3, the Cartesian product of them is domatically full.

Product Demand Forecasting in Ecommerce Based on Nonlinear Autoregressive Neural Network

With the rapid growth of the e-commerce business scale, to meet customers' demand for efficient order processing, it is of great significance to establish an order management mechanism capable of responding quickly by accurately predicting product demand. This study used real e-commerce order demand data and established a nonlinear autoregressive neural network (NAR) model after pre-processing methods including down-sampling and data set partition to effectively forecast the demand of products in the next 13 weeks. Compared with the Prophet time series prediction framework, NAR had better generalization ability, and the prediction time was reduced by 18.54%. Finally, we summarized two methods' characteristics and gave instructions on applying our model in the real scene. After being deployed in the actual demand management, the trained artificial neural network provides a scientific reference for the data-driven e-commerce decision-making process and brings new advantages over other companies, achieving the rational allocation of resources.

An efficient low bit rate image watermarking and tamper detection for image authentication

This study presents the vulnerability of digital documents and its effective way to protect the ownership and detection of unauthorized modification of multimedia data. Watermarking is an effective way to protect vulnerable data in a digital environment. In this paper, a watermarking algorithm has been proposed based on a lossy compression algorithm to ensure authentication and detection of forgery. In this proposed method, the CDF9/7 biorthogonal wavelet is used to transform the watermark image and encoded the wavelet coefficients using Set Partition in Hierarchical Tree algorithm. Then, the encoded bits are encrypted by shuffling and encrypting using symmetric keys. After that the encrypted bits are inserted into the Least Significant Bit position of the cover image. In addition, two tamper detection bits are generated based on texture information and pixel location and inserted in the watermarked image. The proposed algorithm reconstructs the watermark and the tampering region more efficiently and achieved 56.5463 dB PSNR for STARE database. Experimental result shows that the proposed algorithm is effectively prevented different attacks and ensure the integrity of watermark bits within the watermarked image. Also finds the tampered region more efficiently compared with the existing state of art algorithms.