Applied Mechanics and Materials Vols. 602-605

Abstract: MAI influence, using a low computational complexity variable step size LMS algorithm based on the traditional algorithm to find the optimal weight on, and make estimates for the magnitude, thereby offsetting the presence of MAI and estimates for spread spectrum communication system struck a balance between the consideration to be paid for MAI. The improved algorithm reduces the computational complexity of each level, the simulation results also show that the method has better performance.

Abstract: In this paper come up with the idea of user behavior analysis engine, the combination of the static analysis of user behavior and real-time monitoring, real-time acquisition of Web log and user to access the context information of the page, apply to the improved data mining model analysis, which based on cloud computing technology, meanwhile efficient processing and storage, cloud database test showed that, the system can significantly improve the effect and efficiency of user behavior analysis.

Abstract: Traditional file systems have some shortages in storing small files, such as randomness of data layout, waste of disk space and lack of inode resources. In this thesis, a log-structured file system named LevelFS based on LevelDB is presented. By setting the write buffer, it can make disk randomized writes of small files into disk sequential writes, and reduce the distance of related data, so as to improve the read and write performance of file system. Experiments show that LevelFS can greatly improve read and write performance of small files without affect the large ones.

Abstract: Optical detectors consist of optical lenses and sensors, which lead to great influence on image quality. The modulation transfer function (MTF) was selected as the image performance index. The influence of focal shift on MTF in optical system was studied and image quality was simulated in this article. The results show that when the focal shift quantity increases, the MTF of detector decreases accordingly, and the high-frequency messages lost gradually. The conclusion is useful for design evaluate optical imaging system.

Abstract: There is a lot of analysis algorithm in Recorder wave file system. In addition, the various types of analysis algorithm, the different of parameter and output. According to the above mentioned characteristics, we propose an information processing method of Separated Request-Algorithm-Data. We can unified manage it via the model and schedule the correct algorithm through user’s request. Then we can get result from data. In the experiment, we evaluate the model we proposed is supportive when schedule the recorded wave file analysis algorithm. The method improves the versatility and scalability in the respect of wave analysis algorithm.

Abstract: Rough Set Theory is a mathematic tool which mainly deals with the uncertain knowledge. In this paper a new comprehensive evaluation model of low carbon economy based on rough set is formed. At last, the results of comprehensive evaluation of low carbon economy of 6 provinces based on this model are obtained which show this method is effective and feasible.

Abstract: This letter presents a new color image encryption scheme based on the coupled chaos maps. First, the algorithm uses the coupled logistic map to generate random strong key stream, and then designed a kind of initial simple diffusion-joint scrambling-combined diffusion method from the point of the relationships of components R, G, B. The simulation results indicate that this algorithm has stronger security compared with the independent encryption of each color component.

Abstract: Based on GPS and RFID technology, a vehicle path planning guidance system is analyzed in this paper. Specially, the ant colony optimization in the vehicle path planning application of Internet in vehicles environment is proposed, and an improved strategy is put forward to provide an efficient path planning algorithm for the construction of intelligent transportation system. As an alternative of wireless radio and guidance display screen and other primary induction means, the ant colony optimization in this work could supply some significant exploring and thinking for currently construction of the intelligent transportation system.

Abstract: It is difficult to estimate the parameters of Weibull distribution model using Maximum Likelihood Estimation based on Ant Colony Algorithm (ACA) or Particle Swarm Optimization theory (PSO) for which is easy to fall into premature and needs more variables, thus Fruit Fly Optimization Algorithm (FOA) theory is introduced into maximum likelihood estimation, and a parameter estimation method based on FOA theory is proposed, an example has been simulated to verify the feasibility and effectiveness of this method by comparing with ACA and PSO.

Abstract: With the ever-changing education information technology, it is a big problem for the universities and college that how to classify the thousands of copies of the image during the art examination marking process. This paper is to explore the application of artificial intelligence techniques, and to do accurate classification of a large number of images within a limited time and under the help of computer. It is can be seen that the proposed method is feasible through the application of the results of the actual work. Artificial neural network training Artificial neural network training methods have two mainly style, which are Incremental Training and Batch Training, and take the amount of different network training mission as the distinction standard. First, to introduce the Incremental Training [1], that means whenever the network receives the input vector and target vector, it have to adjust once the connection weights and thresholds. It is an online learning method. The other one is Batch Training [2], that means no longer adjust the connection and immediately, but perform bulk adjustment, and after a given volume of the input vector and target vector. Both training methods can be applied, whether it is static or dynamic neural network. Different results will be obtained by artificial neural network for the use of different training methods. When using artificial neural networks to solve specific problems, learning methods, training methods and artificial neural network function should be selected according to the expected results of question type and its specific requirements [3-4]. The selection of parameters of wavelet neural networks and adaptive learning