Papers by Author: Xiao Peng Wei

Abstract: The stiffness characteristics of a rotating cracked shaft including elliptical front edge between transverse crack and 45° slant crack have been studied here. The strain energy release rate (SERR) method has been used to calculate the stiffness matrix of two types of the crack element. Time-varying characteristics of stiffness of the straight front edge and elliptical front edge of the cracked shaft were studied in a stable rotation cycle. The analytical result of this paper shows that change of the cracked shaft stiffness raises during the increase of the crack depth. The stiffness characteristics of the rotor with slant crack having elliptical front edge vary differently from those of the rotor with transverse crack having elliptical front edge.

Abstract: Genetic algorithm (GA), a kind of global and probabilistic optimization algorithms with high performance, have been paid broad attentions by researchers world wide and plentiful achievements have been made.This paper presents a algorithm to develop the path planning into a given search space using GA in the order of full-area coverage and the obstacle avoiding automatically. Specific genetic operators (such as selection, crossover, mutation) are introduced, and especially the handling of exceptional situations is described in detail. After that, an active genetic algorithm is introduced which allows to overcome the drawbacks of the earlier version of Full-area coverage path planning algorithms.The comparison between some of the well-known algorithms and genetic algorithm is demonstrated in this paper. our path-planning genetic algorithm yields the best performance on the flexibility and the coverage. This meets the needs of polygon obstacles. For full-area coverage path-planning, a genotype that is able to address the more complicated search spaces.

Abstract: In this paper, we propose a novel algorithm for facial recognition based on features fusion in support vector machine (SVM). First, some local features and global features from pre-processed face images are obtained. The global features are obtained by making use of singular value decomposition (SVD). At the same time, the local features are obtained by utilizing principal component analysis (PCA) to extract the principal Gabor features. Finally, the feature vectors which are fused with global and local features are used to train SVM to realize the face expression recognition, and the computer simulation illustrates the effectivity of this method on the JAFFE database.

Abstract: Image encryption is one of the most important methods of image information hiding. A new image encryption method based on some techniques and knowledge of genetic engineering for image hiding is presented in this paper. This method is implemented by using modern biological techniques as tools and biological hard problems as main security basis to fully exert the special advantages. The keys are some substances of biological materials such as restriction endonuclease, polymerase and so on, the preparation flow and the experimental conditions. The analysis demonstrates that the image encryption algorithm is feasible and highly secure. Moreover, the size of the decrypted image is the same as the original image so that it can be applied for image hiding and be transmitted via the Internet.

Abstract: AES is one of the most widely used cryptographic systems. DNA computing has the high efficiency to solve some NP-problems. Therefore many scientists try to combine DNA computing with cryptography. In this paper, an algorithm is designed to simulate a plaintext encrypted by DNA biotechnology and modern cryptography. After mapping the plaintext information as DNA chain and handling the base chain with biological genetic technology, we can get the gene codes form, then using the Rijndael algorithm to deal with the biological chain with cryptography and get the final result. It makes the DNA-based cryptography more effective and more security.