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The research discusses the different dosages of pristine carbon nanotubes that can be added for the strength enhancement of cement composites. Carbon nanotubes dispersion in the cement composite was aided using silica fume particles. Addition of silica fume was found to be helpful in strength increment by improving the bond between the nanotubes and cement matrix. The experimental results showed an increase in compressive strength up to 4.2% and 19% at 7 and 28 days testing for the CNTs dosages of 0.05%, 0.075% and 0.10% (by weight of binder) compared the reference specimen. This strength increment is due to improved microstructure formed by the addition of nanotubes.

Approximation of the geometric features is an essential step in point cloud segmentation and surface reconstruction. Often, the planar surfaces are estimated using principal component analysis (PCA), which is sensitive to noise and smooths the sharp features. Hence, the segmentation results into unreliable reconstructed surfaces. This article presents a point cloud segmentation method for building detection and roof plane extraction. It uses PCA for saliency feature estimation including surface curvature and point normal. However, the point normals around the anisotropic surfaces are approximated using a consistent isotropic sub-neighbourhood by Low-Rank Subspace with prior Knowledge (LRSCPK). The developed segmentation technique is tested using two real-world samples and two benchmark datasets. Per-object and per-area completeness and correctness results indicate the robustness of the approach and the quality of the reconstructed surfaces and extracted buildings.

Encryption is used to disguise data making it unintelligible to unauthorized observers. Providing such security is especially important when data is being transmitted across open networks such as the Internet. Since, image data have special features such as bulk capacity, high redundancy and high correlation among pixels that imposes special requirements on any encryption technique. In this paper, an extension is proposed to the block-based image encryption algorithm (BBIE) scheme that works in combination with Blowfish encryption algorithm [16]. Whereas BBIE is meant for 256-color bitmap images, the proposed technique also handles RGB color images and, for the cases studied, improves the security of digital images. In this enhanced technique, which we call the enhanced block based image encryption technique (EBBIE) the digital image is decomposed into blocks, then two consecutive operations - rotating each 3D true color image block by 90deg followed by flipping row-wise down - are performed to complicated the relationship between original and processed image. These rendered blocks are then scrambled to form a transformed confused image followed by Blowfish cryptosystem that finally encrypts the image with secret key. Experimental results show that correlation between adjacent pixels is decreased in all color components and entropy is increased for the cases studied.