Applied Mechanics and Materials Vols. 182-183

Abstract: A probability associated with population fitness is theoretically derived and used as a parameter in the Genetic Algorithm (GA) to switch the operation modes between the population regeneration, and the genetic operation of crossover and mutation in order to effectively prevent the prematurity and reduce the number of function evaluations. The proposed genetic algorithm using the bimodal operation is employed to search for the global optima of five objective functions, whose results are compared to the conventional GAs using a single operation mode. The simulation results demonstrate that the proposed GA can achieve a better convergence performance than the conventional ones when multimodal objective functions are searched for their global optima.

Abstract: The visual secret sharing for multiple secrets (VSSM) technique allows for the encryption of more than one secret images in a given image area. Previous research on VSSM schemes has a pixel expansion problem that limits the capability to increase the capacity of secret image encryption. Moreover, the VSSM schemes focus on sharing binary images to date. These drawbacks limit the applicability of existing VSSM schemes. In this study, we propose a novel encryption algorithm to address these problems. The proposed algorithm adopts a visual cryptography (VC)–based encryption method that can eliminate the pixel expansion problem and is applicable to halftone secret images. The experimental results demonstrate that the proposed approach not only can increase the capacity of VSSM schemes, but also can maintain an excellent level of display quality in the recovered secret images.

Abstract: Brain Magnetic Resonance Imaging (MRI) has become a widely used modality because it produces multispectral image sequences that provide information of free water, proteinaceous fluid, soft tissue and other tissues with a variety of contrast. The abundance fractions of tissue signatures provided by multispectral images can be very useful for medical diagnosis compared to other modalities. Multiple Sclerosis (MS) is thought to be a disease in which the patient immune system damages the isolating layer of myelin around the nerve fibers. This nerve damage is visible in Magnetic Resonance (MR) scans of the brain. Manual segmentation is extremely time-consuming and tedious. Therefore, fully automated MS detection methods are being developed which can classify large amounts of MR data, and do not suffer from inter observer variability. In this paper we use standard fuzzy c-means algorithm (FCM) for multi-spectral images to segment patient MRI data. Geodesic Active Contours of Caselles level set is another method we implement to do the brain image segmentation jobs. And then we implement anther modified Fuzzy C-Means algorithm, where we call Bias-Corrected FCM as BCFCM, for bias field estimation for the same thing. Experimental results show the success of all these intelligent techniques for brain medical image segmentation.

Abstract: In this paper, we introduce a novel technique for mining fuzzy association rules in quantitative databases. Unlike other data mining techniques who can only discover association rules in discrete values, the algorithm reveals the relationships among different quantitative values by traversing through the partition grids and produces the corresponding Fuzzy Association Rules. Fuzzy Association Rules employs linguistic terms to represent the revealed regularities and exceptions in quantitative databases. After the fuzzy rule base is built, we utilize the definition of Support Degree in data mining to reduce the rule number and save the useful rules. Throughout this paper, we will use a set of real data from a wine database to demonstrate the ideas and test the models.

Abstract: With the development of streaming media technology, its application area enlarges gradually. Using streaming media technology for remote online video conferencing has great practical value. In this paper, streaming video conferencing system based on P2P technology is researched and realized.

Abstract: Node localization is one of the key technologies in wireless sensor network. This paper proposed an improved RBDMCL algorithm based on traditional MCL algorithm, which can reduce the sampling areas and improve the positioning accuracy by building a node motion model. Then concludes by simulation analysis and comparison that RBDMCL has higher positioning accuracy than MCL in the anchor node density and node velocity.

Abstract: Basing on the research of structure and management technology for Satellite Integrated Information Network, logical architecture for satellite network based on service is designed, the working principle of which is analyzed too, and the realization of the system is also given. Tests show that service-based network management has good feasibility, the efficiency and intelligence of which is improved.

Abstract: The main objective of this study framework is to help the user to management the interesting video images from the huge storage device. The study can be divided into three main steps is listing as follows: shot boundary detection, key frame selection and evaluation method are designed by analyzing the video content. In this paper we proposed a novel algorithm for shot boundary detection. First, transform the RGB color model into LUV color model according our experimental results. The useful features of each frame are extracted from sequence images by the automatically computation of their color moment-preserving and matching 64-predefined bit planes in order to detect the shot boundary. The excellent shot boundary detection will result in the good key frames selection. Second, the key frame selection is proceed by applying the geometric invariant moments which successful be used in target tracing, pattern recognition, and facial recognition. In our experiments we used five test sequences that belong to five different program categories: movies, advertising, sport game, news, and commercial documentary. The experimental results showed that our method is feasible, effective, and is better than the former approaches.

Abstract: In this study, we will discuss a fast spatial indexing structure called QR*-tree based on R*-tree and quad-tree. Now, R*-tree and R-tree are widely used in spatial database as a spatial indexing structure, But for each algorithm alone, it is not suitable for the huge data volume. The hybrid structure that we proposed is composed of many R*-trees based on space partitioned by quad-tree. Although it demands more storage space than R*-tree or quad-tree, it gains better performance in insertion, deletion, and searching especially, and the more the amount of spatial data is, the better performance the hybrid-tree has.

Abstract: This text have further discussed the audio frequency compression based on wavelet packet decomposition and optimize the choice of optimum wavelet packet and proposed a optimized self-adaptive wavelet packet decomposition and adopted zerotree coding based on psycho-acoustic model, which makes this system have a higher compression ratio than audio signal and can keep good real-time and objective recovery signal to noise ratio. Computer simulation test is made for the calculation proposed with Matlab,and this simulation test has proved the point that is mentioned in this text.