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This paper presents a super-resolution (SR) technique for enhancement of infrared (IR) images. The suggested technique relies on the image acquisition model, which benefits from the sparse representations of low-resolution (LR) and high-resolution (HR) patches of the IR images. It uses bicubic interpolation and minimum mean square error (MMSE) estimation in the prediction of the HR image with a scheme that can be interpreted as a feed-forward neural network. The suggested algorithm to overcome the problem of having only LR images due to hardware limitations is represented with a big data processing model. The performance of the suggested technique is compared with that of the standard regularized image interpolation technique as well as an adaptive block-by-block least-squares (LS) interpolation technique from the peak signal-to-noise ratio (PSNR) perspective. Numerical results reveal the superiority of the proposed SR technique.

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The aim of this work is to investigate the fatigue behavior of a new class of nanostructured,low-temperature bainitic steels,where rotating bending fatigue tests were conducted on samples isothermally transformed at 300,250,and200 °C,after which,fracture surfaces were examined using scanning electron microscopy.Results showed that,fatigue limits of about 820,945,and 1,005 MPa were achieved for the samples transformed at each transformation temperature,respectively.Moreover,according to the SEM micrographs,secondary crack initiation was observed in the high carbon retained austenite blocks for samples transformed at 300 °C and at the interface of blocky austenite-bainitic ferrite for samples transformed at 250 and 200 °C.  相似文献   
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Silicon - Magnetic materials grafted with acetic acid (Fe3O4@SiO2COOH MNPs) were successfully prepared from the incorporation of bromoacetic acid as a functional group on the surface of magnetite...  相似文献   
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