Today, with the rapid development of the Internet, improving image security becomes more and more important. To improve image encryption efficiency, a novel region of interest (ROI) encryption algorithm based on a chaotic system was proposed. First, a new 1D eλ-cos-cot (1D-ECC) with better chaotic performance than the traditional chaotic system is proposed. Second, the chaotic system is used to generate a plaintext-relate keystream based on the label information of a medical image DICOM (Digital Imaging and Communications in Medicine) file, the medical image is segmented using an adaptive threshold, and the segmented region of interest is encrypted. The encryption process is divided into two stages: scrambling and diffusion. In the scrambling stage, helical scanning and index scrambling are combined to scramble. In the diffusion stage, two-dimensional bi-directional diffusion is adopted, that is, the image is bi-directionally diffused row by column to make image security better. The algorithm offers good encryption speed and security performance, according to simulation results and security analysis.
The dynamic splitting tensile tests of five kinds of concrete with different content of carbon nanofibers were carried out by split Hopkinson pressure bar (SHPB) device. The dynamic splitting tensile mechanical properties of carbon nanofibers reinforced concrete (CNFC) are analyzed in terms of the relationships between the stress-time curve, dynamic splitting tensile strength, dynamic splitting tensile increase factor (DTF) and the content of carbon nanofibers as well as strain rate. The results show that: the dynamic splitting tensile strength of concrete is enhanced by carbon nanofibers; at the same strain rate level, with the increase of the content of carbon nanofibers, the dynamic splitting tensile strength of concrete shows a trend of first increasing and then decreasing; when the content of carbon nanofibers is the same, as the strain rate increases, the dynamic splitting tensile strength of concrete continues to increase.
Flow resistance, velocity distribution, and turbulence intensity are significantly influenced by aquatic vegetations (AV) in riparian zones. Understanding the hydraulics of flow with planted floodplains is of great significance for determining the velocity distribution profile and supporting the fluvial processes management. However, the traditional flume experiment method is inefficient. Therefore, the multigroup simultaneous flume test method was carried out to describe the flow patterns affected by emerged rigid (reed and wooden stick) and submerged flexible vegetations (grass and chlorella). The Acoustic Doppler Velocimeter (ADV) was utilized to measure the velocity at one point for different experimental conditions. The results showed that hydraulic features were influenced by different types of vegetation. Furthermore, the relative depth (z/h) was a determining factor of those variations. In addition, the time-averaged velocity distributions of planted floodplains are not logarithmic. Instead, they represented “s-shape” profiles. In detail, for the vegetated floodplains, reed and wood followed an s-shape profile, but for grass and chlorella, they followed reverse s-shape profile. For all cases, turbulence is not isotropic and the change law of turbulence intensity is different in different sections. The flow resistance, turbulence intensities, and Reynold stresses influenced by different types of vegetation were also analyzed.
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