Modeling of rolling force of ultra-heavy plate accounting for gradient temperature

In this paper, the nonlinear specific plastic power of the Mises criterion is integrated analytically to establish the rolling force model of gradient temperature rolling for an ultra-heavy plate by a new method called the root vector decomposition method. Firstly, the sinusoidal velocity field is proposed in terms of the characteristics of metal flow during ultra-heavy plate rolling, which satisfies the kinematically admissible condition. Meanwhile, the characteristics of the temperature distribution along the thickness direction of the plate during the gradient temperature rolling is described mathematically. Based on the velocity field and the temperature distribution expression, the rolling energy functional is obtained by using the root vector decomposition method, and the analytical solution of rolling force is derived according to the variational principle. Through comparison and verification, the rolling force model solved by the root vector decomposition method in this paper is in good agreement with the measured one, and the maximum error of the rolling force is just 10.21%.

Spectral Graph Wavelet Based Image Steganography Using SVD and Arnold Transform

Steganography is the process of concealing sensitive information within cover medium. This study offers an efficient and safe innovative image steganography approach based on graph signal processing (GSP). To scramble the secret image, Arnold cat map transform is used, then Spectral graph wavelet is used to change the cover and scrambled secret image, followed by singular vector decomposition (SVD) of the modified cover image. To create the stego image, an alpha blending process is used. To produce the stego image, GSP-based synthesis is used. By maintaining the inter-pixel correlation, GSP improves the visual quality of the produced stego image. The effects of image processing attacks on the suggested approach are examined. The investigational results and assessment indicate that the proposed steganography scheme is more efficient and robust in terms of quality measures. The quality of stego image is evaluated in respect of PSNR, NCC, SC and AD performance metrics.

Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.