Dynamic response of elastic beam to a moving pulse: finite element analysis of critical velocity

Dynamic behaviour of a semi-infinite elastic beam subjected to a moving single sinusoidal pulse was investigated by using finite element method associated with dimensionless analysis. The typical features of the equivalent stress and beam deflection were presented. It is found that the average value of maximal equivalent stress in the beam reaches its maximum value when the velocity of moving pulse is closed to a critical velocity. The critical velocity decreases as the pulse duration increases. The material, structural and load parameters influencing the critical velocity were analysed. An empirical formula of the critical velocity with respect to the speed of elastic wave, the gyration radius of the cross-section and the pulse duration was obtained

Traceable Multiauthority Attribute-Based Encryption with Outsourced Decryption and Hidden Policy for CIoT

Cloud-assisted Internet of Things (IoT) significantly facilitate IoT devices to outsource their data for high efficient management. Unfortunately, some unsettled security issues dramatically impact the popularity of IoT, such as illegal access and key escrow problem. Traditional public-key encryption can be used to guarantees data confidentiality, while it cannot achieve efficient data sharing. The attribute-based encryption (ABE) is the most promising way to ensure data security and to realize one-to-many fine-grained data sharing simultaneously. However, it cannot be well applied in the cloud-assisted IoT due to the complexity of its decryption and the decryption key leakage problem. To prevent the abuse of decryption rights, we propose a multiauthority ABE scheme with white-box traceability in this paper. Moreover, our scheme greatly lightens the overhead on devices by outsourcing the most decryption work to the cloud server. Besides, fully hidden policy is implemented to protect the privacy of the access policy. Our scheme is proved to be selectively secure against replayable chosen ciphertext attack (RCCA) under the random oracle model. Some theory analysis and simulation are described in the end

Visualization 1: Dual-color multiple-particle tracking at 50-nm localization and over 100-µm range in 3D with temporal focusing two-photon microscopy

Cafeteria swimming revised video Originally published in Biomedical Optics Express on 01 October 2016 (boe-7-10-4187

Robust Image Hashing with Low-Rank Representation and Ring Partition

Image hashing has attracted much attention of the community of multimedia security in the past years. It has been successfully used in social event detection, image authentication, copy detection, image quality assessment, and so on. This paper presents a novel image hashing with low-rank representation (LRR) and ring partition. The proposed hashing finds the saliency map by the spectral residual model and exploits it to construct the visual representation of the preprocessed image. Next, the proposed hashing calculates the low-rank recovery of the visual representation by LRR and extracts the rotation-invariant hash from the low-rank recovery by ring partition. Hash similarity is finally determined by L2 norm. Extensive experiments are done to validate effectiveness of the proposed hashing. The results demonstrate that the proposed hashing can reach a good balance between robustness and discrimination and is superior to some state-of-the-art hashing algorithms in terms of the area under the receiver operating characteristic curve

Visualization 1.avi

Temporal focusing two-photon microscopy of fluorescent microsphere

Image Encryption with Double Spiral Scans and Chaotic Maps

Image encryption is a useful technique of image content protection. In this paper, we propose a novel image encryption algorithm by jointly exploiting random overlapping block partition, double spiral scans, Henon chaotic map, and Lü chaotic map. Specifically, the input image is first divided into overlapping blocks and pixels of every block are scrambled via double spiral scans. During spiral scans, the start-point is randomly selected under the control of Henon chaotic map. Next, image content based secret keys are generated and used to control the Lü chaotic map for calculating a secret matrix with the same size of input image. Finally, the encrypted image is obtained by calculating XOR operation between the corresponding elements of the scrambled image and the secret matrix. Experimental result shows that the proposed algorithm has good encrypted results and outperforms some popular encryption algorithms

Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality