Publications by authors named "Kunpeng Mao"

Article Synopsis
  • - A new 4D hyperchaotic system has been developed from a modified 3D Lorenz system, characterized by a single equilibrium point, and its stability and dynamic properties were thoroughly analyzed using MATLAB simulations.
  • - The system exhibits hyperchaotic behavior across various parameter ranges and transitions through multiple states, and its behavior has been validated with STM32 embedded hardware for accuracy in reproducing chaotic attractors.
  • - The hyperchaotic system is applied to a new image encryption method that passes rigorous security tests and demonstrates effectiveness in various fields like audio/video encryption, IoT security, and medical data protection.
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In recent years, deep convolutional neural network-based segmentation methods have achieved state-of-the-art performance for many medical analysis tasks. However, most of these approaches rely on optimizing the U-Net structure or adding new functional modules, which overlooks the complementation and fusion of coarse-grained and fine-grained semantic information. To address these issues, we propose a 2D medical image segmentation framework called Progressive Learning Network (PL-Net), which comprises Internal Progressive Learning (IPL) and External Progressive Learning (EPL).

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Osmotic power, a clean energy source, can be harvested from the salinity difference between seawater and river water. However, the output power densities are hampered by the trade-off between ion selectivity and ion permeability. Here we propose an effective strategy of double angstrom-scale confinement (DAC) to design ion-permselective channels with enhanced ion selectivity and permeability simultaneously.

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