bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of Two Dimensional Fisher Linear Discriminant for Palm Vein Recognition
Authors: Wu Wei
Published: September 2013

Palm vein is covered with skin, some captured NIR palm vein images are not clear because of light scattering in the skin. The identification performance is not high by extraction palm vein feature directly. This paper proposes project the palm vein image matrix based on two dimensional Fisher linear discriminant directly, then calculates the Euclidean distance of the projection matrix, seeks the nearest distance for classification. The experiment has been done in a self-build palm vein database. Firstly, this paper tests the proposed method by different component numbers, then compares the identification performance with the other typical palm vein recognition methods.
Preprocessing for Local Bianry Pattern Based Face Recognition
Authors: Xing Ning , Gui Lan Xian
Published: September 2013

This paper studies the pre-processing methods on Local Binary Pattern (LBP) for face recognition. Three methods are well investigated, such as Gaussian smoothing, histogram equalization and Sobel operator. The extensive experiments on FERET database show that the best recognition rate increase is achieved by combination of histogram equalization, Gaussian smoothing, and Sobel with LBP. The conclusion achieved in the paper is useful for real face recognition system.
Segmentation of Welding Defect Image Based on Exponential Cross Entropy and Improved PCNN
Authors: Ye Zhi Long , Wu Yi Quan , Wan Hong , Cao Zhao Qing
Published: September 2013

Aiming at welding defect image with complex background and low contrast, a segmentation method of welding defect image based on exponential cross entropy and improved pulse coupled neural network (PCNN) is proposed. Firstly, the area of weld is extracted by gray projection algorithm. Then, link weighted matrix and dynamic threshold function of PCNN are improved. Finally, the exponential cross entropy is calculated as criterion to determine the number of iteration for improved PCNN and get the optimal segmented image. The experimental results are given. Compared with the threshold segmentation method based on exponential cross entropy, the segmentation method based on PCNN and Shannon entropy, the proposed method can achieve better segmented results.
Micro-Motion ISAR Imaging Method Based on MP Sparse Decomposition for Fast Moving Target
Authors: Gong Jian , Lei Teng , Li Zhi Long , Li Chuang
Published: September 2013

In this paper, a new micro-motion ISAR imaging algorithm is proposed, which achieve high cross range resolution by using the changes of azimuth angle caused by micro-motion. Before Wigner-Ville transformation to eliminate the cross-term interference, the echoes of the same range cell are decomposed. Comparing to traditional the Wigner-Ville imaging algorithm and Range-Doppler algorithm, this new algorithm in this paper has better imaging precision and no cross-term interference is existed. At last, the effectivity of the proposed algorithm is demonstrated by the simulated results.
Based the Morphological Filtering BP Algorithm of SAR Image Recognition
Authors: Jiang Ding Ding , Cai De Rong , Wei Qiang
Published: September 2013

SAR image recognition is an important content of of aviation image interpretation work. In this paper, the characteristics of SAR images a practical significance of morphological filtering neural network model and its adaptive BP learning algorithm. As can be seen through the experimental results, the algorithm can not only adapt to the complex and diverse background environment, and has a displacement of the same continuous moving target detection capability, telescopic invariant and rotation invariant features.
Improved Self-Adaptive Image Histogram Equalization Algorithm
Authors: Peng Na Xin , Chen Yu Qiang
Published: September 2013

Histogram equalization (HE) algorithm is wildly used method in image processing of contrast adjustment using images histogram. This method is useful in images with backgrounds and foreground that are both bright or both dark. But the performance of HE is not satisfactory to images with backgrounds and foregrounds that are both bright or both dark. To deal with the above problem, [ gives an improved histogram equalization algorithm named self-adaptive image histogram equalization (SIHE) algorithm. Its main idea is to extend the gray level of the image which firstly be processed by the classical histogram equalization algorithm. This paper gives detailed introduction to SIHE and analyzes the shortage of it, then give an improved version of SIHE named ISIHE, finally do experiments to show the performance of our algorithm.
Research on Minimum Resolvable Contrast of the Telescope
Authors: Tan Bi Tao , Chen Hong Bin , Wang Qun Shu
Published: September 2013

At present, the research on the minimum resolvable contrast is limited to the simple imaging system, or the imaging devices, and mainly limited to the method of measurement in the laboratory, the research on minimum resolvable contrast of the telescope has not developed. Based on the imaging process of the telescope and the detecting SNR, noise equivalent contrast is put forward, then combined with the system MTF, the model on minimum resolvable contrast of the telescope is build. At last, the model is simulated on the computer, the simulation results indicated that the minimum resolvable contrast can evaluate the telescope ability more comprehensive, the atmosphere, the aberration and the motion can affect the ability seriously. The model can give a scientific basis for the optimization design of the system and the development of practical work.
An Edge Detection Algorithm Based on Human Visual System
Authors: Xiao Chuan Min , Ma Tian Lei , Xia Ren Bo
Published: September 2013

Edge detection is a fundamental problem in computer vision. In this paper, we present an effective algorithm to find salient edges from infrared scene images based on Human Visual System. The algorithm integrates three basic edge features: edge contrast, edge density and edge length. In this manner, the proposed algorithm works well to detect salient region boundaries and to suppress false edges from background and texture. The experimental results demonstrate the effectiveness of the proposed algorithm.
Application of Wavelet Transforms Method to Infrared Image Enhancement
Authors: Xu Wei Chang , Tang Tao , Liu Ji Fang , Huang Wei
Published: September 2013

Wavelet transformation was introduced into the image enhancement step of infrared thermal wave NDT (nondestructive testing). This paper first explained the theory of image enhancement of wavelet transformation and then devised the enhancing process, where to get the best enhancing effect, this paper studied the selection of the threshold value and enhancement factor of the enhancement function to draw the conclusion that threshold value T mainly has impact on noise reduction, enhancement factor k1 on the enhancing effect of transition area, and enhancement factor k2 on image contrast, and also described the parameter selection method; on this basis, this paper finally selected threshold value T 600, k1 10, and k2 0.15 to carry out enhancement processing on the infrared thermogram of a composite and by comparison with the original image proved the effectiveness of this method.
Kinect Depth Data Segmentation Based on Gauss Mixture Model Clustering
Authors: Du Ting Wei , Liu Bo
Published: September 2013

Indoor scene understanding based on the depth image data is a cutting-edge issue in the field of three-dimensional computer vision. Taking the layout characteristics of the indoor scenes and more plane features in these scenes into account, this paper presents a depth image segmentation method based on Gauss Mixture Model clustering. First, transform the Kinect depth image data into point cloud which is in the form of discrete three-dimensional point data, and denoise and down-sample the point cloud data; second, calculate the point normal of all points in the entire point cloud, then cluster the entire normal using Gaussian Mixture Model, and finally implement the entire point clouds segmentation by RANSAC algorithm. Experimental results show that the divided regions have obvious boundaries and segmentation quality is above normal, and lay a good foundation for object recognition.
Coastline Detection from Remote Sensing Image Based on K-Mean Cluster and Distance Transform Algorithm
Authors: Liu Ying
Published: September 2013

Using remote sensing technique to determine coastline's position has been received vital attention. This paper presents a novel approach for detecting coastline of remote sensing image based on K-Means cluster and Distance Transform algorithm. K-Means cluster algorithm divides the image into two regions-water and land area. Then to extract the sea area by distance transfoming. Finally, the coastline will be detected by edge traking. Results showed that the method proposed in this paper have good performance in accuracy and completeness.
Method of Moment Analysis of Wire Antennas Based on Different Basis Function
Authors: Li Guang Yu , Liu Jin Bo , Yu Xiang Zhi , Gao Hong Min
Published: September 2013

For the study of highly precise simulation algorithm for the analysis of antenna, the basic thought of method of moment analysis of wire antennas is introduced. The mathematical model is established and the formula derivation is presented in this paper. The method of moment equation is solved through utilizing three different basis functions and weight functions. Two examples are given, and the computing results are contrasted with the simulation results of FEKO. The comparison result shows that method of moment is quite accurate when it is used to analyze wire antennas, and the computed results acquired by applying Galerkin matching method are the most accurate of all. In the end, an accurate and effective electromagnetic simulation method is presented.
Path Recognition Technology of Self-Tracing Car Based on OV6620
Authors: Cheng Shuang , Shi Kai , Wang Li Guang , Ye Meng Jun , Hu Chang Hui
Published: September 2013

This paper proposes extracting black line with small-scale method in the self-tracing car system based on OV6620 as the video sensor unit. Describe the hardware design of OV6620 and other two kinds of image signal extracting methods, which are to extract black line from left to right, and extract black line from middle to both sides. The testing shows that extracting black line with small-scale method has good stability, accuracy, and anti-interference.
Iris Boundary Localization Based on Improve Hough Transform
Authors: Zhang Guo Yu , Zhao Hui , Han Min , Chen Li Ling
Published: September 2013

ris location is one of the key steps of iris recognition system. Non-ideal iris image has some problems, such as eyelid and eyelash occlusion, low contrast of iris and sclera, uneven illumination, and so on. Because of that, its difficult to identify the boundary, especially the exterior boundary. Therefore, this paper proposes a method based on the improved Hough Transform. First, use the minimum method to find the datum point in the pupil, after that identify the valid area of the interior boundary base on that point. Apply the improved Hough Transform to that valid area to identify the interior boundary of the iris image. Then regard the center of the interior circle as our new datum point, use the same method to identify the exterior boundary. Experiment results show that our algorithm has higher accuracy than traditional method on the non-ideal iris image segmentation.
Image Mosaic Based on Improved SIFT
Authors: Wang Yan Wei , Lin Bing , Sun Hua Dong
Published: September 2013

Feature matching used in SIFT methods to extracting feature points, is the key of image mosaic. The advantages of SIFT is one of the most robust and the widely used image matching algorithms based on local features, which ensure the good mosaic image and reliable result. In this paper, we proposed a new image mosaic technology based on simple, which can solve massive calculation and long processing time produced by SIFT. The first step from this method is that 32 vectors, from the feature points, reduce to 16 vectors, and the feature points with 16 vectors construction a pot set, which is the space transformation matrix. And space transformation, the transformation is the mapping of the two images. The processed image is edge processed to eliminate image edge ambiguity and the right results is also rests on cluster .The stitched image is achieved thorough it. Experimental results show that the proposed algorithm is effective and comparing favorable with existing techniques, Practical application shows that this method also proposes a reliable parameter estimation method, and the result is reliable to stitching a large image. At the same time, the processing time is faster than SIFT.
Content Based Image Retrieval with Color Invariants
Authors: Song Ya Hui , Chen Xiao , Qu Shan Shan
Published: September 2013

Content based image retrieval (CBIR) is an essential task in many applications. Color based methods have received much attention in past years, since color could serve efficiently for image retrieval, especially in the case of large database. However, there are two main drawbacks for color based image retrieval methods. Firstly, color based methods are not suitable for similar scenes under different illumination conditions, because color is sensitive to illumination. Secondly, existing approaches usually employ image descriptors with large size, which makes the approach unsuitable for real-time application. To overcome drawbacks mentioned above, an adaptive image retrieval method has been proposed, which integrates the color invariant with the spatial information about images. Different from previous methods, the quantization of the color space has not been manually determined. Instead, it has been decided according to the content of image, using an adaptive clustering technique. Therefore, the size of image descriptor is very small.
In the proposed method, feature maps for images have been firstly established, which consist of color invariants. And then the Markov chain model has been employed to capture color information and spatial features. Finally, similar images are retrieved based on two-stage weighted distance. Experimental results show that the proposed method has improved simplicity and compactness of color based image retrieval methods, without the loss of efficiency and robustness.
Design and Implementation of Wireless Mobile Unit Based on GPS & GSM
Authors: Gao Hong Min , Gong Tong Ze , Yu Xiang Zhi , Fang Jie
Published: September 2013

The subject is a research on a terminal which can accomplish the transmission of real-time location information, location, navigation, and communication by the wireless network of a monitoring system. The terminal equipment uses ARM as the microcontroller for extracting the information of GPS position, velocity and time. Then, the information is sent in the form of data packages or text messages by the GSM network and the ISM network of wireless transmission. The solution is stable and easy to control.
A New Kernel Orthogonal Projection Analysis Approach for Face Recognition
Authors: Jing Xiao Yuan , Li Min , Yao Yong Fang , Zhu Song Hao , Li Sheng
Published: September 2013

In the field of face recognition, how to extract effective nonlinear discriminative features is an important research topic. In this paper, we propose a new kernel orthogonal projection analysis approach. We obtain the optimal nonlinear projective vector which can differentiate one class and its adjacent classes, by using the Fisher criterion and constructing the specific between-class and within-class scatter matrices in kernel space. In addition, to eliminate the redundancy among projective vectors, our approach makes every projective vector satisfy locally orthogonal constraints by using the corresponding class and part of its most adjacent classes. Experimental results on the public AR and CAS-PEAL face databases demonstrate that the proposed approach outperforms several representative nonlinear projection analysis methods.
Application of Image Processing to the Vehicle License Plate Recognition
Authors: Chen Chun Yu , Cheng Bao Zhi , Chen Xin , Wang Fu Cheng , Zhang Chen
Published: September 2013

At present, the traffic engineering and automation have developed, and the vehicle license plate recognition technology need get a corresponding improvement also. In case of identifying a car license picture, the principle of automatic license plate recognition is illustrated in this paper, and the processing is described in detail which includes the pre-processing, the edge extraction, the license plate location, the character segmentation, the character recognition. The program implementing recognition is edited by Matlab. The example result shows that the recognition method is feasible, and it can be put into practice.
Real-Time Human Action Recognition System Using Depth Map Sequences
Authors: Li Yan Li , Wang Gui Jin , Lin Xing Gang , Cheng Guang , He Li
Published: September 2013

This work presents a real-time human action recognition system that uses depth map sequence as input. The system contains the segmentation of human, the action modeling based on 3D shape context and the action graph algorithm. We effectively solve the problem of segmenting human from complex and cluttered scenes by combing a novel quadtree split-and-merge method and the codebook background modeling algorithm. We aims at recognizing actions that are used in games and interactions, especially complex actions that contain foot motion and body heave. By expanding the shape context descriptor into 3D space, we obtain translation and scale invariant features and get rid of normalization error, which is a common problem of real-life applications. Experiments in various scenarios demonstrate the high speed and excellent performance of our procedure.
A 94 Ghz Orthomode Transducer for Dual Polarization Receivers
Authors: Wu Ze Wei , Li Hao , Fu Hua , Xu Jian Hua
Published: September 2013

A 94 GHz waveguide orthomode transducer to be used as a receiver has been designed, fabricated, and measured. The waveguide choke, realized by a cascade of symmetrical steps, is introduced as the polarization discriminator, which could remarkable lower the difficulty of manufacturing and assembling in W-band and above. The designed orthomode transducer has low return loss, high isolation, and moderately broad bandwidth, and its performance closely follow the simulation results.
Using Exchange Attenuation to Control Non-Disentanglement Quantum Information Transport in Phase Damping Channel
Authors: Hu Ju Ju , Ke Qiang , Hu Hai Jiang , Ji Ying Hua
Published: September 2013

It is effective to constitute a hybrid qubit system by taking advantages of different types of qubits to overcome the effects of decoherence and achieve quantum information transport. We find that energy relaxation exists in the process of information exchange bewteen the hybrid qubits. Combining this kind of energy relaxation with the decoherence effects from external environment, quantum information transport of non-disentangled effect can be achieved in phase damping channel if the exchange decay rate and decoherence time satisfy certain constraint relations.
Design of Tiny TTY for Multi-Process Micro-Kernel Embedded OS on ARM
Authors: Qu Bo
Published: September 2013

This paper describes the design and implementation of tiny TTY driver for ARM based multi-process micro-kernel embedded operating system in technical details, including overview of TTY (Control flow of terminal driver, process modes for TTY, data structures for tiny TTY), interrupt-mode UART driver, and tiny TTY driver for micro-kernel OS. The ARM based operating system is designed and implemented by the author of this paper on Linux with GNU tool chain. Based on the TTY, some shell commands are designed, in which the key strokes on the super terminal are read as the input of the commands analogous to the case for ordinary embedded Linux. On the premise of implementing essential functions, the routines for the tiny TTY is designed as simple as possible therefore it is suited to not only embedded operating system research but also embedded related curriculum teaching in colleges and universities.
A Novel Construction Method of QC-LDPC Codes Based on Generalized ACE Constrained
Authors: Zhao Hong Hao , Meng Fan Bo , Zhao Qing Qi , Wang Jie
Published: September 2013

Recently, structured LDPC codes have been focused on due to excellent performance and lower complexity. An improved construction of QC-LDPC based on a modified PEG algorithm is proposed in this paper. The modified Progressive Edge-Growth algorithm is a PEG algorithm with Approximated Cycle Extrinsic Message Degree (ACE) metric, which is used to describe the connectivity of cycles. The approach can maximize the girth of the cycles, improve the connectivity of cycles and have the advantages of QC algorithms. The simulation results demonstrate that the PEG algorithm based on ACE has lower Bit Error Rate (BER) and Frame Error Rate (FER) than the original PEG algorithm at the low Signal Noise Ratio (SNR) values, and has a relatively lower computational complexity.
Semantic Inner Product Based Web Service Matchmaking Method
Authors: Li Wen Qing , Zhang Yu Ting , Zhao Pu , Wang Ke Xiang , Lu Wen Qin
Published: September 2013

Web Service matchmaking ensured the availability of the discovered service, is a critical issue for Web Service discovery. In this paper we proposed a Semantic Inner Product based Web Service Matchmaking method (SIP-WSM). SIP-WSM merged the structural and semantic information into the Semantic Inner Product of element in WSDL document to realize a loosely structured matchmaking on semantic level. Experiment result shows that SIP-WSM performs better.
A TIFF-Tree Based High Utility Itemset Mining Algorithm
Authors: Pan Yi , Zhang Bo
Published: September 2013

Owing to their major contribution to the total transaction's sales profits, increasingly importance has been attached to high utility itemsets mining. This paper has proposed a TIFF-tree based algorithm, which takes two-pass database scan to obtain the transaction utility information, the conditional matrix of potential high utility is adopted, through the row-column operation, the calculation of transaction utility can be simplified. The experiment result analysis shows that as the decreasing of user-defined threshold, the performance of TIFP-Growth algorithm is much better than the two-phase algorithm.
Comparisons on the Architecture and Implementation of Distance Education Platform
Authors: Li Xiao Ping , Liu Feng , Wang Xiao Jun , Mao Xu
Published: September 2013

This paper gives the structural model of modern distance education platform of distance education ,compares the implementation method and functional framework of the platform of distance education of J2EE architecture with that of service-oriented architecture (SOA) , and proposes the service-oriented architecture (SOA) as an intelligent way of distance education platform architecture. According to CELTS-1 standard, the necessary hardware topology for intelligent distance education platform and the detailed functional design of main module of the platform are given.
An Improved Data Possession Checking Scheme in Cloud Computing
Authors: Meng Xiang Lei , Ai Ming Shun , Yu Peng Peng
Published: September 2013

Remotely data storage in cloud computing faces great challenge. Data possession checking ensures the data integrity and availability. In this paper, a cloud data possession checking model has been presented. Based on Paillier cryptosystem and elliptic curve cryptograph (ECC),we designed a data possession checking scheme, where the user asks the server to compute a checking value of randomly appointed data blocks, and then makes a decision by proof verification. The homomorphic verification tag (HVT) generated based on Paillier cryptosystem to achieve unlimited queried times. Extensive evaluation and analysis shows the proposed scheme is efficient and secure with the features: a high confidence level, un-forged HVTs, a small constant overhead, etc.
A Novel Wideband Transition between Waveguide and SIW
Authors: Zhou Yi Hong , Wang Hai Yang , Li Jia Yin
Published: September 2013

Based on a linearly tapered antipodal finline, a novel low-loss wideband transition between waveguide and substrate integrated waveguide (SIW) is discussed. Results show that a low insertion loss (1.2-2.1dB) and a return loss better than 15dB across the entire Ka-band are obtained for a back-to-back transition structure.
Flow Field of XCP Probe's Head and Optimization Choice of Structural Parameters
Authors: He Hong Kun , Yang Shuang Qi , Li Guang Yu , Gao Hong Min
Published: September 2013

In this study, numerical simulation of XCP probe was executed. The 3D Navier-Stokes equations were used as governing equations, and the finite volume method combining two-equations turbulence model was applied. The flow field of XCP Probe was analyzed, especially around the XCP Probe's head. The results show that the arc design of the XCP Probe's head plays an important role on the steady falling speed. In addition, when the radian is 27°, the resistance of the probe is smallest and a larger falling speed can be achieved; The electrodes of probe should be located in front end of a conduit which is in the middle of the probe.
Research of Distributional Ecology Cloud-Structure
Authors: Lan Ji Ming , Lu Shu Jie , Zhang Li Ming
Published: September 2013

Proposed that idea of cloud computing ecology development, supports and guiding cloud model deployment, the cloud service management and Clouds protocols observes the purification of mix cloud environment. Has designed the multiple dimension data saving structure and real-time mass-data processing of model as well as the asynchronous overall construction distributional ecology cloud structure. It has been shown that this ecology cloud structure is healthy.
Research on the Application of College Automated Course Scheduling System Based on Genetic Algorithm
Authors: Li Xiu Ying , Du Dong Ju
Published: September 2013

A reasonable curriculum contributes to the improvement of the training and teaching quality of college students. Using computer which is speed and strong ability to arrange curriculum automatically is imperative. Automatically curriculum arrangement is a constrained, multi-objective and intricate combinatorial optimization problem. Based on genetic algorithm of population search, it is suitable to process complex and nonlinear optimization problems which it difficult to solve for traditional search methods. In this paper solves complex automated course scheduling using genetic algorithms.
The Design and Research of Digital Service Platform Based on Semantic Web
Authors: Wang Xin Yu , Zhang Qing Song
Published: September 2013

With the application of semantic web technique and concept map theory, this paper constructs a personalized platform model based on semantic web, which is called digital library. The model consists of personalized module, information resource integration and process module, semantic analysis and process module, and query module. The function of each module is analyzed concretely.
A Research and Implementation on the Optimum Proposal of Self-Adaptive Mobile Learning Activity Mode Based on Android
Authors: Hu Hai Yan , Yan Hui
Published: September 2013

To better reach the goal of education reform, the learning system is expanded and transplanted to the Android cell phone platform. Optimum proposal of setting up self-adaptive mobile learning activity mode on Android mobile platform is the focus of this paper. The key issue of the research is to design a kind of adaptive optimization algorithm for learning program. By analyzing the learning behavior of the students and evaluating the learning activity mode, self-adaptive optimization can be realized based on the result of systematic analysis. Compared with traditional mobile learning activity mode, learning activity efficiency is enhanced.
The Optimization Algorithm of Aviation Equipment Maintenance Cost Forecast and its Applied Research
Authors: Xiao Li Zhi , Yang Dong Ping , Sun De Xiang , Wang Xiao Kun , Li Zhi Liang
Published: September 2013

The maintenance cost forecast of aviation equipment is a multifactor influenced, non-linear and little samples problem. Aiming at the problem, genetic algorithm (GA) and support vector machine (SVM) were combined to build a GA-SVM forecast model for maintenance cost of aviation equipment. The model used GA to optimize the parameters of SVM, which can avoid the blindness choice of parameters and improve its forecast efficiency. Through the example analysis, the model has more accurate results and extensibility than PSO-SVM, SVM and multivariate linear regression in the forecast of maintenance cost of aviation equipment.
The Research on the Consuming Prediction of Military Aircraft Spare Parts
Authors: Sun De Xiang , Tang Sheng Quan , Xing Guo Ping , Wang Xiao Kun , Liu Yong Yu
Published: September 2013

Aiming at the problem that the consuming-related factors of military aircrafts spare parts cant be revealed in the model, support vector machines (SVM) model was applied in the consuming prediction of spare parts. In the model, the main factors that affected spare parts consumption were taken as the input of SVM while the output was the consumption. Then, the test samples were input the trained model for prediction. The results show that, compared with GM (1,1) model and neural network model (ANN), the model has higher prediction accuracy and dynamic adaptability, which can provide some reference for the spare parts management sections.
A Calculation Model of Pull-Off Force with Edge-Effect
Authors: Niu Shao Hua , Gao Shi Qiao , Du Jing Qing
Published: September 2013

Based on the pull-off force calculation model with the liquid bridge capillarity force theory, analysis of the circumstance of the liquid bridge, puts forward an pull-off force calculation model with the consider of the edge effect. More experiment test results show, the model is effective and it can use for the exactitude calculate.
On Real-Time Modeling of 3D Terrain Database
Authors: Zhang Wei , Zhang Chun Hua , Zhang Yan
Published: September 2013

With the uprising deployment of large-scale environmental simulations, as well as the wide applications of the GIS data in the simulation models, the traditional modeling methods have been difficult to meet the requirements of terrain generation of large areas. In this paper, we study a new terrain database modeling process based on Celerity/TerraVista, which uses the techniques of image compression, block optimization, and level of detail (LOD) , for terrain generation of large areas. Tis new modeling process has been applied in our independently developed simulation system and has achieved good results.
Analysis of Web Log Data Mining Based on Improved Fuzzy Clustering Algorithm
Authors: Chen Chuan Qi
Published: September 2013

Fuzzy clustering analysis is a clustering algorithm based on function best practices, technology and optimal cost function using calculus. Fuzzy clustering, each sample is no longer belong to a class, but belong to a certain degree of membership of each class. In this paper, Web log sequential pattern mining knowledge gained, and visitors have the same browsing mode access to cutting the interaction of users with the Web information space. The paper presents analysis of Web log data mining based on improved fuzzy clustering algorithm. The experiment demonstrates the improved algorithm has better scalability.
A Method on Process Planning Decision Based on Genetic Algorithm
Authors: Tan Dan Dan , Zhang Yi Ming
Published: September 2013

This paper proposes a method for optimizing the process planning with GA in ERP, analyzes the factors relating to production planning decisions in ERP. On this basis, builds the mathematical model of process planning and gives the step of solving mathematical model using GA through a specific example.
Curve-Skeleton Extraction Using Appropriate Threshold Optimization
Authors: Wang Shuai , Qiu Zhong Pan , Song Zhi Jun
Published: September 2013

The curve-skeleton of an object is an important abstract geometrical and topological representation of its shape, which is extremely useful for pattern recognition and computer vision applications involving in shape analysis. In this paper, we propose an effective algorithm for extracting curve skeleton based on the definition and properties of curve skeleton from pixel cloud, which integrates the advantages of the visual main parts reliability for object recognition and the skeletons reduced-dimension for object representation. This algorithm can detect each pixel of the image, and find the salience value of each pixel; the salience value is the possibility of the pixel being a skeleton point. Then an appropriate threshold is selected to pruning the skeleton and to get the curve skeleton. In this way, the algorithm can be effective in reducing the number of non-skeleton pixels, and reduce the overall time of extracting skeleton. The experiments show that the skeleton keeps the topology of the target. And the corners of the skeleton are smoother and more natural. In additionally, it can effectively reduce redundant branches of skeleton.
Automatic Translation in Chinese and English Based on Mixed Strategy
Authors: Chen Heng , Yu Yong Sheng
Published: September 2013

English and Chinese translation is an essential part in language teaching. Automatic translation is the focus of language research. In this thesis, we analyze the traditional translation system and the intelligent translation system, coming up with the working model. Then we discuss the different granularity in English and Chinese translation and its influence on translation, and propose sentence construction model and Chinese and English translation model. Through the analysis, the advantages of the auto translation based on phrases are shown. Then, on the purpose of assisting English language teaching, automatic translation framework with mixed strategy based on phrase collecting, judgment, statistics and functional words connection, is worked out. The framework includes building up translation knowledge database by analyzing the translation documents resources, identifying phrase and sentence models, and automatic translating based on the knowledge database.
Determine Execution Time and Selection Probabilities in Process Mining via Petri Nets
Authors: Zhou Huan , Lin Chuang , Deng Yi Ping , Wan Zi Cheng
Published: September 2013

In process mining research, process discovery techniques can produce or rebuild models with the information from logs. There are already algorithms supporting control-flow perspective mining which focus on the order of events and provide understanding workflow paths. But few of them take time perspective and path selection probabilities into consideration, which are important in performance evaluating, delay prediction, decision making, as well as process redesigning and optimizing. This paper provides a novel algorithm which determines the information of time perspective and selection probabilities from a log and integrates them with the control-flow perspective. By applying this algorithm, a stochastic Petri net is provided which is useful in performance analyzing and process optimizing.
Research on Spreading and Evolution of Opinion in Online Social Network
Authors: Zhang Chang Lun , Li Chao
Published: September 2013

the online social network has served as a critical medium for information dissemination, diffusion of epidemics and spread of behavior. In this paper, we proposed a model of opinion spreading and evolution based on online social network, where the social temperature is taken into account. First, the forms and features of the opinion spreading and evolution in social network are analyzed. Then a model of opinion spreading and evolution is established, in which social temperature as an external factor participate the opinion evolution of nodes and then affect the opinion spreading. Simulation results show that social temperature has an important impact on the opinion spreading and evolution.
Optimization of Financial Forecasting Based on Least Squares Support Vector Machine
Authors: Li Yun Fa
Published: September 2013

To master the variation regularity of finance, obtain greater benefits in stock investment. study of the support vector machine and application in prediction of stock market. The simulated annealing algorithm to optimize the least squares support vector machine prediction model, and the least square support vector machine and simulated annealing algorithm is described, given the optimal prediction model. Through the research on the simulation of the Hang Seng Index, shows that this method is simple, fast convergence, the algorithm with high accuracy. Has the actual guiding sense for investors, the stock market of the financial firm to operate.
Target Tracking Analysis Based on Corner Registration
Authors: Kang Zheng Xi , Zhao Hui , Dang Yuan Zhen
Published: September 2013

Target tracking algorithm based on Mean-Shift and Kalman filter does well in linear tracking. However, the algorithm might lose the target when the trace of mobile target is curve or the acceleration is not constant. To cope with these drawbacks, this paper proposes Target Tracking Analysis Based on Corner Registration. The algorithm modifies the initial iteration center of Mean-Shift by using the corner features combined with affine transformation theory and then the Mean-Shift can track the target. The theoretical analysis and the experimental results demonstrate that this method can overcome the drawbacks we talk above and make achievements in target tracking.
Analysis of Generalization for a New Kind of Neural Network
Authors: Zhang Dai Yuan
Published: September 2013

To describe the performance of a new kind of approximation algorithm using B-Spline weight functions on feedforward neural networks, the analysis of generalization is proposed in this paper. The neural networks architecture is very simple and the number of weight functions is independent of the number of patterns. Three important theorems are proved, which mean that, by increasing the density of the knots, the upper bound of the networks error can be made to approach zero. The results show that the new algorithm has good property of generalization and high learning speed.
Application of Thinking Method of Decomposition and Combination in Developing Software
Authors: Tu Ye Xia , Gao Yu
Published: September 2013

There are many thinking method, the thinking method of decomposition and combination is important and widely used. In the category of scholars, "decomposition and combination" belong to "analysis and synthesis". Developing software is a complex mental activity, so it requires the use of a variety of thinking method. Thinking method of decomposition and combination is the use of the most frequent in developing software. Content of thinking method of decomposition and combination is analyzed. Application of thinking method of decomposition and combination has been analyzed from four aspects. Four aspects are the development trend of software, the main content of the structured software development method, the main content of the object-oriented software development method, several commonly used software development tools.
Design Method of Database System Based on DPT and P2P Point Cloud for Internet of Things
Authors: Chen Chao , Guo Hui
Published: September 2013

In recent years, with the development of Internet of Things, a new challenge is posed on data access. Focusing on the database management problems of internet of things, a design method of database system for Internet of Things was proposed by means of DPT and P2P point cloud. An example of Internet of Things for medical health system verifies the method can solve the problem of database management of Internet of Things to a certain extent and provide technical support for Internet of Things combining distributed processing technology, network technology, and middleware technology.
Hippocampus Segmentation Techniques: A Survey
Authors: He Bing Song , Zhang Xue Ping , Shi Yong Gang
Published: September 2013

Since the volume of hippocampal formation has been found to be an early biomarker for MCI and Alzheimer's disease, hippocampus segmentation plays a significant role in clinical diagnosis. Because hippocampus in MR images presents features of low contrast, low signal-to-noise ratio and discontinuous boundaries, accurate segmentation still remains a challenging task. We presented a survey of the methods used to segment the hippocampal formation in MR images of human brain and concluded with a discussion on the trend of the future research in hippocampus segmentation.
Optimization of Launching Angle Base on the Acquisition Probability for Laser Semi-Active Terminal Correction Projectile
Authors: Li Xing Long , Wang Xiao Ming , Yao Wen Jin , Yu Ji Yan
Published: September 2013

In order to improve the acquisition probability for laser semi-active terminal correction projectile, the scheme of optimizing launch angle is proposed, the mathematical model of the strapdown seeker laser detector and the capture field model of target is established, and the scheme is verified by Monte Carlo ballistic simulation method. The results show that the scheme of optimizing launch angle improves the target acquisition probability, and will be of important significance to firing table modifying of laser semi-active terminal correction projectile.
Design and Implementation of Network Topology Discovery System Based on OSPF
Authors: Wang Jie , Chen Bing , Tan Cheng Xiang
Published: September 2013

This paper presents an algorithm of network topology discovery based on OSPF protocol and introduces the implementation. It is different than the traditional topology discovery algorithms which are mostly based on SNMP and ICMP protocols. The test results show that it has made an efficient and useful solution to network topology discovery.
Use of Watermark in Educational Administration System
Authors: Liu Yi , Lai Si Yu
Published: September 2013

With the widespread use of watermark in video, audio and image, propose a relational database based watermark embedding and extraction method. The algorithm utilizes the singlemultiple mapping approach to plug in watermark, which scatter the distribution of watermark information and enhance the anti-attack ability of the algorithm. The experiments show that the method enjoys strong robustness to such attacks as tuples resorting, subset selection and so on.
Stability and Bifurcation Analysis in Leukopoiesis Models with Two Delays
Authors: Zhang Cui Lian , Guo Zhao Zhuang
Published: September 2013

We consider a nonlinear system of two equations, describing the evolution of a stem cell population and the resulting white blood cell population. Two delays appear in this model to describe the cell cycle duration of the stem cell population and the time required to produce white blood cells. We establish sufficient conditions for the asymptotic stability of the unique nontrivial positive steady state of the model by analyzing roots of a second degree exponential polynomial characteristic equation with delay-dependent coefficients. We also prove the existence of Hopf bifurcations which leads to periodic solutions.
An Evaluation Model to Human Factors in Information Systems Based on Consistent Quantification of Index and Evaluation Equilibrating
Authors: Shen Jian Guo , Shi Zhi Yong , Wang Jiao , Zhao Yuan
Published: September 2013

In this paper, a comprehensive evaluation model to human factors is presented for information systems. The model can be used in the evaluation that the number of evaluation expert for every evaluated object or target is different. By introducing the concept of Gini coefficients, the coordinated and balance degree of evaluated targets can also be reflected in the evaluation. The proposed model can be widely used because it contains the process of different types of index such as quantitative, qualitative, cost and benefit targets. The reliability and universality are validated by experiment results.
Methods for Determining Differences of Attribute Weight between Evidences in Bridge Assessment
Authors: Li Xiao Feng , Ding Shu Chun , Wang Xue Mei
Published: September 2013

The attribute weights determined is a key issue in the decision-making. Attribute weights given in the form of distribution of the attribute value to language assessment and rating their trust completely unknown or partially unknown circumstances, the proposed method of weight determination of the two based on objective evidence of differences between rights. Method one calculated based on the evidence of conflict between the coefficient weights; method to calculate the mean and variance of the research evidence weights. Finally, through the application of specific cases to verify the effectiveness of the method.
Analysis on Local Congestion of Network-on-Chip
Authors: Tang Ming Hua
Published: September 2013

In Network-on-Chip (NoC), adaptive routing provides packets multi paths to reach their destinations. Thus, packets can escape the hot-spot nodes. However, as our study indicates that adaptive routing cannot distribute traffic evenly in the network as expected. A local region will be injected more packets than others, which makes congestion takes place in that local region. Local congestion has significant impact on network performance. In this paper, we carry out a detail studying on local congestion in NoC.
Design of Low-Noise and High-Density Signal Intelligent Detection System
Authors: Yang Xiaoan
Published: September 2013

Using motion state of the equipment transducer to determine the presence of a weak signal is a common method of signal detection, whose core is to determine the system's phase change. There a many traditional ways to judge phase transition, but most of which have computational complexity and need a large amount of data which make them difficult to apply engineering practices. In order to solve these problems, this paper presents a detection method based on Lyapunov exponent classification with a small amount of data. This approach has some advantages such as requiring fewer observed values, small calculation amount, and able to automatically determine the phase transition without subjective factors involved etc. Experiments show that this method has stable performance, high effectiveness, strong practicality and promotion.
Fabrication and Testing of PDMS Pitch-Variable Gratings Based on Silicon Mold Technology
Authors: Li Xin Peng , Li Yi Gui , Luo Chen Chen , Wang Wei
Published: September 2013

A period-variable grating is designed and fabricated in this paper. The PDMS grating is replicated by method of Si mold which is fabricated by MEMS process. The grating is connected with a mechanical system which can change its pitch when a force is applied, so it can extend the grating and change the grating's period. In the diffraction experiment, about 20% extension ratio of the first diffraction order has been obtained, which will generate the change of diffraction angle of 0.096rad.
The Investigation on Defect Mode Property of the Ten-Fold Photonic Quasicrystal
Authors: Wu Yu Long , Sun Xiao Hong , Liu Wei
Published: September 2013

In this article,the transmission spectra of ten-fold photonic quasicrystals (PQC) are calculated by using finite-difference time-domain method (FDTD). By changing the crystal structure and introducing the point and line defects to devise the good micro-cavity and waveguide structures.In TE mode, the transmission spectra with defect modes are observed and quality (Q) factors are calculated to optimize the micro-cavity structure.It has the biggest Q factor when the central dielectric cylinder is removed. Furthermore, Design different waveguide structures and explore the field distribution. Different waveguide structure can control different light path and choose different incident light frequency.