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Automatic detection of damaged buildings from satellite remote sensing data has become an urgent problem to rescue planners and military personnel. Unfortunately damaged buildings are in different dimensions and shapes with different roofs depending on the type of the material to be painted. In this study, we present an improved Swin-Unet approach that comprises three main operations. First, improved Swin-Unet as a Unet-like pure Transformer is used for multitemporal image segmentation. Second, different multitemporal features are extracted using hyperspectral image classification algorithm. Finally, a binary change map is generated, and evaluation results are obtained. This article takes AIST building change detection scene as the example, and compared with the conventional approaches tested, overall accuracy, mean intersection over union, and separated Kappa in the proposed method were improved by at least 23.36, 0.1725, and 0.202, respectively. Furthermore, different scenes, such as Gaofen-2/Jilin-1 multitemporal optical images and satellite imagery dataset (xBD), have also come to the same conclusion. Thus, it provides advantageous capabilities for monitoring damaged buildings along coastal areas.

To reduce the heating of the Terfenol-D rod and evaluate its working efficiency, six kinds of Terfenol-D rods were designed, and the temperature field of the rods was simulated and calculated using the finite element method to obtain the temperature distribution. The results showed that the untreated rod had the highest temperature; the temperature was higher in the middle and lower at both ends; higher on the outer diameter surface; and lower on the inside. When compared to the untreated rod, the temperatures of sliced rods and slit rods decreased, and the temperature of sliced rods was lower than that of slit rods; the temperature of slit rods was higher in the middle and lower at both ends; the temperature distribution of sliced rods was more uniform relatively; the slice treatment rod had the lowest temperature and the best heat suppression effect. Three structural rods were chosen and manufactured from a total of six that were tested. It shows that the temperature of all rods was higher in the middle and lower at both ends after 30 min of operation. The actual temperature of untreated rod was 34 °C, the actual temperature of radially slit rod was 32 °C, and the actual temperature of sliced rod at both ends was 28 °C. The tested temperature distributions of three rods agreed with the calculated ones.

This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time, a region-based matching scheme is investigated by employing the Scale Invariant Feature Transform (SIFT) matching method. Finally, the finger-vein shape, orientation and SIFT features are combined to further enhance the performance. The experimental results on databases of 426 and 170 fingers demonstrate the consistent superiority of the proposed approach.

Each pixel in the hyperspectral unmixing process is modeled as a linear combination of endmembers, which can be expressed in the form of linear combinations of a number of pure spectral signatures that are known in advance. However, the limitation of Gaussian random variables on its computational complexity or sparsity affects the efficiency and accuracy. This paper proposes a novel approach for the optimization of measurement matrix in compressive sensing (CS) theory for hyperspectral unmixing. Firstly, a new Toeplitz-structured chaotic measurement matrix (TSCMM) is formed by pseudo-random chaotic elements, which can be implemented by a simple hardware; secondly, rank revealing QR factorization with eigenvalue decomposition is presented to speed up the measurement time; finally, orthogonal gradient descent method for measurement matrix optimization is used to achieve optimal incoherence. Experimental results demonstrate that the proposed approach can lead to better CS reconstruction performance with low extra computational cost in hyperspectral unmixing.