Smart windows are a promising way to modulate solar light transmittance, which is crucial for energy saving buildings. We provide an overview of the recent progress in hydrogel-based smart windows.

This paper presents a practical framework for the integration of unmanned aerial vehicle (UAV) based photogrammetry and terrestrial laser scanning (TLS) with application to open-pit mine areas, which includes UAV image and TLS point cloud acquisition, image and cloud point processing and integration, object-oriented classification and three-dimensional (3D) mapping and monitoring of open-pit mine areas. The proposed framework was tested in three open-pit mine areas in southwestern China. (1) With respect to extracting the conjugate points of the stereo pair of UAV images and those points between TLS point clouds and UAV images, some feature points were first extracted by the scale-invariant feature transform (SIFT) operator and the outliers were identified and therefore eliminated by the RANdom SAmple Consensus (RANSAC) approach; (2) With respect to improving the accuracy of geo-positioning based on UAV imagery, the ground control points (GCPs) surveyed from global positioning systems (GPS) and the feature points extracted from TLS were integrated in the bundle adjustment, and three scenarios were designed and compared; (3) With respect to monitoring and mapping the mine areas for land reclamation, an object-based image analysis approach was used for the classification of the accuracy improved UAV ortho-image. The experimental results show that by introduction of TLS derived point clouds OPEN ACCESSRemote Sens. 2015, 7 6636 as GCPs, the accuracy of geo-positioning based on UAV imagery can be improved. At the same time, the accuracy of geo-positioning based on GCPs form the TLS derived point clouds is close to that based on GCPs from the GPS survey. The results also show that the TLS derived point clouds can be used as GCPs in areas such as in mountainous or high-risk environments where it is difficult to conduct a GPS survey. The proposed framework achieved a decimeter-level accuracy for the generated digital surface model (DSM) and digital orthophoto map (DOM), and an overall accuracy of 90.67% for classification of the land covers in the open-pit mine.

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A framework for solving atomistic phonon-structure scattering problems in the frequency domain using perfectly matched layer boundaries

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Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1) The first one is based on multispectral images using parallax between two different bands in the image; (2) The second is based on stereo images using rational polynomial coefficients (RPCs); (3) The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1) The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2) The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD) viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer), LRO (Lunar Reconnaissance 3945Orbiter) and ZY-3 (ZiYuan-3) demonstrate the promising performance and feasibility of the proposed framework.

Geckos have the extraordinary ability to adhere and move across varied surfaces, while keeping their tiny high-aspect-ratio foot-hairs intact for thousands of attachment−detachment cycles. Inspired by the dry adhesive structure of gecko sole, various gecko-inspired artificial mimics have been developed, but many of them suffer from premature failures and short fatigue life. Herein, we discover that individual gecko seta is a functionally graded material. Its Young's modulus gradually decreases from base to tip, with up to 20 times of difference in magnitude. Finite element analysis indicates that this gradient design is the key to make the natural setal stalks more flexible (critical for producing large frictional adhesion on rough surfaces) and less stressed (critical for achieving high fatigue resistance) during each attachment. Inspired by these findings, we have fabricated poly(dimethylsiloxane) (PDMS)-based artificial gecko foot-hairs with a gradient distribution of magnetic nanoparticles as the reinforcements, achieving similar varying modulus/stiffness. The biomimetic hairs/pillars show enhanced fatigue resistance compared to the uniform counterparts. This work opens a door in designing dry adhesives with both high adhesive strength and long fatigue life.

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