Applied Mechanics and Materials Vols. 416-417

Abstract: Cluster network structure is one of the most common topological properties of complex networks and the most important topological attribute, and has the characteristics of the same cluster nodes connected to each other, and the sparse characteristics of the dense clusters interconnected with nodes. To reveal the complex network clustering method of network cluster structure has a very important theoretical significance for the analysis of complex network topology structure, to understand its function, discovering the behavior of the hidden patterns, prediction, and is widely used in social networks, biological networks and the world wide web. This article reviews the research background of the complex network clustering method, research significance, research status at home and abroad as well as the major problems currently facing this new research direction in an attempt to draw a comprehensive and clear outline, to provide a useful reference for researchers of the complex network, data mining, intelligent Web, Bioinformatics and other related fields.

Abstract: This article discusses the problems existing in power system graphics software, and analyze wxWidgetss characteristics like cross-platform, local perception, face to objects and other features. The validation based on the wxWidgets development can make up for the graphics software shortcomings, providing new ideas for the development of future coal mine power system graphics software.

Abstract: In order to short the modelling time of BP neural network, this paper designs a kind of genetic algorithm to optimize it. By encoding the individual components, initializing the number of populations, and designing proper fitness function, a binary coding genetic algorithm is provided for BP neural network. And it is used to optimize input variables of BP neural network and reduce its dimension. The experiment is carried out based on KDD Cup 99 data set. The results show that the optimized model has shorter modelling time.

Abstract: Considering the particular scene that the moving ships in Inland River are surrounded by the nearly static water, this paper presents a method that updates the background by adopting the neighboring static region to replace the dynamic areas. By making the difference between the current frame and the background image to get the foreground area, and using the region growing algorithm to shape a complete ship region, we can get the coordinate, the center point and the direction of its movement. To obtain its mean gray value to replace the foreground dynamic region, we choose a static adjacent background at front-end of the ship. Then we adopt a variable weight method to update background in order to prepare for the next image proceeding background difference calculation. As the loop goes on, we can make fast and accurate ship image identification from the surveillance streaming media.

Abstract: The article put forward to new recognition method of handwritten digital based on BP neural network. Its recognition process mainly includes ten aspect: incline correction of handwritten number, edge detection and separation of a set number, binarization, denoising, extraction of numerals, window scaling, location standardization, thinning, extraction of numeral feature and fuzzy recognition based on BP neural network. The test results show that the recognition rate of this method can be over 92 percent. The recognition time of characters for character is less than 1.1 second, which means that the method is more effective recognition ability and can better satisfy the real system requirements.It should be widely applied practical significance for Book Number Recognition, zip code recognition sorting.

Abstract: With rapid development of space information crawl technology, different types of spatial database and data size of spatial database increases continuously. How to extract valuable information from complicated spatial data has become an urgent issue. Spatial data mining provides a new thought for solving the problem. The paper introduces fuzzy clustering into spatial data clustering field, studies the method that fuzzy set theory is applied to spatial data mining, proposes spatial clustering algorithm based on fuzzy similar matrix, fuzzy similarity clustering algorithm. The algorithm not only can solve the disadvantage that fuzzy clustering cant process large data set, but also can give similarity measurement between objects.

Abstract: In view of that detent force (DF) spatial harmonic has great influence on thrust ripple of permanent magnet synchronous linear motor (PMSLM), a harmonic suppression method is proposed. DF of the PMSLM model is calculated by finite element method (FEM) and its harmonic spectrum is achieved by Fourier transform (FT). Also total harmonic distortion (THD) is introduced to quantificat spatial harmonic. The effects of air gap, permanent magnet (PM) size, primary size, secondary size and pole-arc coefficient upon DF are analyzed. In order to minimize THD, orthogonal optimization design is adopted to optimize PMSLM structural parameters. A double-secondary PMSLM is chosen as the subject of research in the paper. Based on quantitative calculation, orthogonal experiment and range analysis are used to obtain optimal structures. This paper provides an effective quantitative analysis method for PMSLM spatial harmonic suppression.

Abstract: After the MCU-processing, the temperature data, collected from 18B20 temperature sensors, are sent back to computer by serial port. Through the combination of computers RS232 serial port and LabVIEWs VISA, the signal can be received and be saved as text file and the save interval time may be user-define. If the temperature exceeds the limited range, it can produce warning with manners of pilot lamp or sound and at the same time the warning times are marked in txt file. This design can transmit the information from RS232 serial port to MCU and vice versa by the use of RS232.

Abstract: For The fix algorithm of TV model caused the staircase effect, iterations low efficiency and produce false edge drawback when gradient only along the perpendicular direction to diffusion. The paper propose an improved K and P parameters based image restoration algorithm. The combination of isotropic and anisotropic diffusion model, used in a smaller area of the pixel gradient isotropic diffusion, that will improve the speed of iteration, and a larger region in the pixel gradient value take the P-Laplace operator to anisotropic diffusion to avoid the staircase effect in the the image flat areas repair. Experimental results show that the algorithm has good repair and good convergence.

Abstract: Device fingerprints has potential to identify the source of digital communication information. Although identifying transmitters with their fingerprints remains an arduous question, fusion identification with multiple device fingerprints is a feasible methodology. In this paper, a relationship between parameters of two representations of discrete-time linear time-invariant (LTI) autoregressive moving average (ARMA) system model is derived which has definite physical meaning. With the relationship, a novel linear device fingerprints is proposed which may enlarge the inter-class distance of the transmitters to be identified. The proposed device fingerprints can be used for fusion identification of network devices and the corresponding ARMA systems especially for that with slight differences.