The issue of optimal placement of wireless sensor networks (WSNs) is one of the major challenges for dynamic monitoring of bridges. It should be solved based on combining the effective monitoring of the dynamic performance of a bridge with the energy consumption of WSNs. Thus, the relationship between the bridge modal and the energy consumption of wireless networks is derived. Optimizing sensor location is achieved by using the improved wavelet particle swarm algorithm, which overcomes the disadvantage of the conventional particle swarm algorithm by applying mutation operator to the selected particles with certain small probability. Based on the comparison between the ANSYS simulation results and the measured bridge data, as well as the energy distribution diagram of WSNs, the proposed method is shown to reflect the dynamic performance of the test bridge well. Moreover, the method effectively controls the energy consumption of WSNs and achieves reasonable optimization effects. Therefore, this method can be used for dynamic monitoring of wireless sensors in various bridge types.
This paper presents a new image encryption solution using the chaotic Josephus matrix. It extends the conventional Josephus traversing to a matrix form and proposes a treatment to improve the randomness of this matrix by mixing chaotic maps. It also derives the corresponding encryption primitives controlled by the chaotic Josephus matrix. In this way, it builds up an image encryption system with very high sensitivities in both encryption key and input image. Our simulation results demonstrate that an encrypted image of using this method is very random-like, that is, a uniform-like pixel histogram and very low correlations in adjacent pixels. The design idea of this method is also applicable to data encryption of other types, like audio and video.
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