Advanced Materials Research Vols. 268-270

Abstract: Due to the exceptionally desirable properties, Chebyshev polynomials have been recently proposed for designing public key cryptosystems. However, some proposed schemes were pointed out to be insecure and unpractical. In this paper, we analyze their defects, discretize the Chebyshev maps, generalize properties of Chebyshev polynomials and design an improved scheme. Theoretical analysis shows that it possesses higher security than RSA and experimental results shows it can be implemented easily.

Abstract: Semi-supervised Support Vector Data Description multi-classification algorithm is presented, in order to solve less labeled data learning, difficulties in the implementation and poor results of semi-supervised multi-classification, which full use the distribution of information in of non-target samples. S3VDD-MC algorithm defines the degree of membership of non-target samples, in order to get the non-target samples’ accepted labels or refused labels, on this basis, several super-spheres constructed, a k-classification problem is transformed into k SVDDs problem. Finally, the simulation results verify the effectiveness of the algorithm.

Abstract: The denoising principal of the anisotropic diffusion equation is studied. Adaptive filtering of image is realized by combining the improved image structural similarity algorithm and the anisotropic diffusion equation. This algorithm is applied to medical image segmentation. Experimental results show that the improved algorithm has good robustness and advantages in the application of adaptive medical image filtering and segmentation.

Abstract: On the base of researching currently popular text topic extraction technologies, a new text topic automatic abstracting method is proposed based on rough set theory and rough similarity. Firstly it separated a text into words and sentences to complete information segmentation, and then constructed a similarity matrix by computing the rough similarity between different words to realize the text clustering, finally extracted representative sentences from each class to generate the text topic. The experiment shows that the method is feasible and effective.

Abstract: Lossless digital watermarking algorithm based on attribute information has been presented based on the location information and coordinate information of vertex in vector maps. With the knowledge of data structure and file structure of digital vector maps, its attribute information has been presented in detail and a lossless scheme with zero-bit dynamical extension has been proposed. On the basis of this, space clustering analysis with grid density was used to increase robustness of the scheme.

Abstract: This paper concerns an improved adaptive genetic algorithm, and the method is applied to the Maximum Entropy Template Selection Algorithm image registration. This method includes adjusting the probability of crossover and mutation in the evolutionary process. The method can overcome the disadvantage of traditional genetic algorithm that is easy to get into a local optimum answer. Results show our method is insensitive to the ordering, rotation and scale of the input images so it can be used in image stitching and retrieval of images & videos.

Abstract: This paper proposes a novel breadth-first search algorithm and deals with the problem of duplicate web pages removing and page ranking by the principle of Small World phenomena. The features of algorithm in this paper are as follows: 1) it proposes the Unit Tree-based Breadth-First Search Algorithm and performs a qualitative analysis and simulated calculation of the performance, with the results demonstrating that the algorithm in this paper reduces the number of neighboring nodes to which messages shall be forwarded and redundant messages as compared with traditional Breath-First Search algorithm and Random Breath-First Search algorithm; 2) it proposes a solution to the problem of duplicate web pages removing and page ranking by Small World phenomena, with the results demonstrating that the method in this paper can effectively bring processing workload, waiting time and the pointless network bandwidth consumption of source node searching into balance.

Abstract: Based on operation computation of signal chip MSC1214, Output signal processing of air level posture sensor is carried on, including temperature –zero voltage compensation, temperature-sensitive voltage. The results show that the change quantity of sensitivity drops to ≤1%; the operating temperature scope expands from the normal temperature to 30°C; in this temperature range, the change quantity of zero voltage drops from ≤0.23V to ≤0.01V, depressing the influence caused by temperature and improving the measurement accuracy of air level posture sensor.

Abstract: one improved finite volume method is proposed, expatiating on the basic idea and integrating the partial derivative equation for the secondary spary water dynamic cooling control model. The semi-discrete equation for derivative of time is obtained.Combinating with an introducted slab continuous casting production line in some steel mill, according to the Q235 actual parameters, what is obtained is surface temperature distribution, the changing of surface temperature and the water flow rate because of the varying of casting speed. The results of simulations performed using the mathematical model are validated against the measured values and a good agreement is observed, Verifing the validity of the model.The model occupies less computer memory, solving simple

Abstract: With the LiangShui forestry centre as study area, high-density LiDAR data and to synchronously processed high-resolution digital image are taken as data source to extract Individual Tree Height. The LiDAR data of the study area is filtered and classified, using TIN Filter to extract the ground echo points and trees echo points. Then these ground echo points generate Digital Elevation Model (DEM), and these trees echo points generate Digital Surface Model (DSM). Then the DEM and DSM are Taken as a subtraction to obtain Canopy Height Model (CHM), then the object-oriented approach is used to segment air digital image. Through multi-scale and canopy-model which create image objects and class division level, with the nearest neighbor distance and member function, the image objects are classified, and re-segmentation is based on classification results. And the edge is optimized to accurately identify individual tree. The canopy polygon obtained after image segmentation and CHM were superimposed to calculate polygon maximum elevation difference from LiDAR data as a tree height. Associated with the measured height analysis, the accuracy is 92.04%.