bluuebunny/crossref_metadata_2025 huggingface dataset:
Algorithms of Data Mining and Knowledge Discovery of Correlativity in Two-Dimensional Time Series
Authors: Hu Shao Lin , Li Ye , Zhang Wei
Published: December 2012

Oriented at dynamic data from complicated process with noise disturbance, it is very difficult to discover knowledge of correlativity and orderliness. Following some analyzing results about the shortcoming of relative coefficients in mining non-stationary time series, a series of new algorithms are built in this paper to mine correlativity in two-dimensional time series. These new algorithms are based on a expansible framework of model set. Based on these new mining algorithms, a making decision table is listed not only to mine correlativity in two-dimensional time series, but also to discover deepening knowledge to transform the qualitative knowledge “nonlinear relativity” as well as “non-relativity” into deeper quantitative knowledge about analytical model. These new approaches given in this paper is exoteric in framework and can be enriched with additional new models. In this way, some professional data mining and knowledge discovery cab be fulfilled to aim at some specific professional fields.
Experimental Research on Diffserv-Aware MPLS Traffic Engineering
Authors: Zhou Jin He , Xia Guo Min
Published: December 2012

Diffserv-aware and Traffic Engineering combine the advantages of MPLS, Traffic Engineering (TE) and Differentiated Services (Diffserv, DS) to provide high performance and Quality of Service(QoS) in networks. We have designed three scenarios on Juniper Networks platforms to analyze the packet loss rate and delay for video, voice and data. The results show that MPLS DS-TE can improve the QoS for differentiated service effectively. The research has practical value for the development of DS-TE based on MPLS.
Implementing Parallel Metaheuristic Optimization Framework Using Metaprogramming and Design Patterns
Authors: Tsyganov Andrey V. , Bulychov Oleg I.
Published: December 2012

In the present paper we introduce an approach to implementing parallel metaheuristic optimization frameworks which is used in the design of the framework HeO. This experimental cross-platform framework is a collection of popular optimization methods implemented in C++ as algorithmic skeletons. The key feature of the discussed approach is the wide usage of metaprogramming and design patterns which allow to increase the reusability of the code and ease the process of hybrid algorithms construction for the end-user. We consider framework structure and implementation details and provide the results of numerical experiments for some well-known optimization problems.
Minimum Test Case for Discrete-Type Software Reliability Testing by Stratified Sampling
Authors: Li Qiu Ying , Luo Lei
Published: December 2012

The traditional approach for generating software reliability test cases according to operational profile (OP) can be regarded as a simple random sampling. The stratified sampling is a complex but more accurate sampling approach which can make the sampling results more accurate and less variance by dividing the population into several subsets and randomly sampling from each subset respectively. Firstly, this paper introduced the traditional method which can be used to determine the number of test cases in the discrete-type software reliability demonstration testing. Secondly, the necessary condition for the minimum test case based on the stratified sampling was studied. Then a new approach was proposed and its principle was analyzed for determining the minimum test case of the discrete-type software by using the stratified sampling. Finally, the future work was discussed.
Program Slicing Technique in Programming Assessment
Authors: Tang Hong Jun
Published: December 2012

For the teachers of teaching basic computer programming language, a very large number of student programs should be graded and human graders have great difficulty in judging the correctness and efficiency of programs. A programming assessment method is proposed based on program slicing technique and the method has reduced the complexity in the assessment of large-scale program by decomposing program. The method divides the program into several slices by generating program dependence graph and on those slices we can get the score of the student program by comparing the student program with the template program. The method has successfully improved the grading process and it is also employed for the undergraduate courses.
Research of Disk Operating Technique in UEFI Shell Environment
Authors: Wu Wei Min , Li Shao Yong , Huang Huan Kun , Chen Wei De , Su Qing
Published: December 2012

This paper describes the theory and method of programming under the environment of UEFI Shell and also introduces the UDK2010.UP4 install and configuration. The program run in UEFI Shell can get EFI Boot Services through the EFI_SYSTEM_TABLE parameter, after this it can operate disk files through Simple File System Protocol and EFI File Protocol. The work in this paper mainly introduces some file operations in UEFI Shell, such as file creating, data access on a FAT file system disk through a UEFI Application (UEFI App hereafter).
Research on Multi-QoS and Trusted Task Scheduling in Cloud Computing Environment
Authors: Li Fu Fang , Xie Dong Qing , Gao Ying , Xie Guo Wen , Guo Qiu Ye
Published: December 2012

Multi-QoS and Trusted resource management and Task Scheduling are key problem in cloud computing. This paper presented an effective Multi-QoS and Trusted resource management model and Task Scheduling algorithm in Cloud Computing Environment. By using the idea of fuzzy clustering for reference, the proposed approach can subtly schedule the Cloud tasks to appropriate resources that exactly meets its’ multi-QoS needs of resources. Considering the credibility of cloud resources, the credibility and trusty of task scheduling has been dramatically improved.
TextSumIt: a Semantic Single Document Summarization Model on Android Mobile Device
Authors: Foong Oi Mean , Lee Mellissa
Published: December 2012

The explosion of information in the World Wide Web is overwhelming for readers with limitless information. Large internet articles or journals are often cumbersome to read as well as comprehend. More often than not, readers are immersed in a pool of information with limited time to assimilate all of the articles. As technology advances, it becomes more convenient to access information on-the-go, i.e., portability of information by utilizing mobile devices. In this research, a semantic and syntatic based summarization is implemented in a text summarizer to solve the information overload problem whilst providing a more coherent summary. The objective is to integrate WordNet into the proposed system aka TextSumIt which condenses lengthy documents into summarized text. The empirical experiments show that it produces satisfactory preliminary results on Android mobile phones.
Virtual City Ground Object Modeling and Visualization Based on OpenGL
Authors: Xu Xu Dong , Wang Jing , Lv Guan Feng
Published: December 2012

A kind of modeling method of regular ground object in virtual city was proposed through splicing certain spatial simple geometries based on VC++ and OpenGL, which combining the ground objects’ characteristics with modeling realistic demand. This method firstly generated some basic shapes (cylinder, cone or sphere) which were the constituent parts of regular ground object, by using simplified 3D basic geometry modeling method of OpenGL. Then joined these basic shapes together by doing coordinate transformation to construct the regular ground object. The case of modeling street lamp was taken as an example to introduce the ground object’s modeling methods and visualization technology. The modeling process just need calculating a small number of coordinates, and the amount of data is also very low. Experimental results show that generated models looks very real.
A Proposal of a Software Development Model Based on Industrial Engineering Concepts
Authors: Baptista Gabriel Lara , Salles José Antonio Arantes
Published: December 2012

The Software Engineering can be considered a new area. During its recent history, many techniques applied for managing and producing software have been taken from Industrial Engineering. It is known that issues related to achieve the deadline, cost and functionalities are being discussed and are still a challenge for software development. This paper aims to propose a software development process model based on concepts of Industrial Engineering. Besides, the paper discusses some standards and models from Software Engineering that helped in the development of the model proposed. The result of this work is the model itself, together with some future works proposed to continue the research.
Study of the CAD in Landscape Gardening Design
Authors: Weng Jun Pu , Zhang Ya Qian , Zhang Xi Rui
Published: December 2012

This paper describes the advantages and disadvantages of CAD software in landscape gardening design. The CAD software is not only brought a lot of convenience in the modern garden design, but also brings new support to all walks of life, and depicts a CAD software application prospects in the garden design.
The Design and Implementation of Code Generation Based on J2EE in the Development of JBPM Workflow System
Authors: Song Yong Chao , Wu Bu Dan , Chen Jun Liang
Published: December 2012

According to the feature of the JBPM workflow system development, the target code generated is determined by analyzing the process of JBPM workflow development and the architecture of J2EE. The code generation tool generates code by parsing the static form source code and loading the code generation template. The code generation tool greatly shortens the JBPM workflow system development cycle and reduces the cost of software development which has the good practicality and scalability.
A New File Updating Discovery Algorithm Supporting Semantic Synchronization
Authors: Li Qiang , Zhu Li Gu , Zeng Sai Feng
Published: December 2012

Updates discovery is the key problem of data synchronization; it has been used to generate updates operations. The traditional algorithms ignore the modify semanteme, cause the updates operations increased. A new file updating discovery algorithm that supports semantic synchronization is proposed in this paper. The algorithm takes advantage of semantic info, which preserved in file system journal, to accurately recognize users originally modify intents. We take the NTFS file system as an example to realize and test the new algorithm. By comparison, the algorithm effectively reduces synchronization requests. Experiments show that, the algorithm cans timely respond to users’ modification and support massive file changes that occurred in short time. The algorithm is designed based on the basic features of file system journal, and can be applied to other file systems.
Framework Design of Cloud Computing Based Environmental Information Disclosure Platform
Authors: Zeng Wei Hua , Yu Long Quan , Zhao Lin Jia , Zhong Xiao Hong , Wang Kun Peng
Published: December 2012

In order to promote multi-directional exchanges among environmental management departments, enterprises and public to improve capacity of environmental information disclosure, environmental governance open innovation model based on environmental information disclosure should be established to take advantage of the public pressures of environmental governance to promote improvement of environmental behavior of enterprises and government departments. Environmental governance open innovation model is based on the public access to environmental information, thereby establishing a comprehensive environmental information platform is essential. By taking advantage of cloud computing technology features of ultra-large-scale, high scalability and on-demand services, a cloud computing based environment information platform will be established to meet needs of public access to environmental information and environmental participation. The platform can customize different services for different users, and promote the development of environmental governance mode to achieve the improvement of environmental quality.
SMS Spam Filtering Based on “Cloud Security”
Authors: Wu Hongli , Jiang Yong Hui
Published: December 2012

“Cloud Computing” technology has very big advantage in the computing power, scalability, reliability and cost etc. “Cloud Security "and " Cloud Storage " is one of the two main research fields. This paper puts forward “filter cloud” strategies of filter spam messages based on "Cloud Security" in order to achieve the purpose of filtering spam messages by addressing its root causes. It is a new attempt that applying “Cloud Computing” in spam messages filter and more mobile business would move to "cloud computing" platform in the future.
Surfacelet Hard-Threshold Video De-Noising Method Combining Multi-Cycle Spinning
Authors: Li Jian Nan , Yu Lei , Zheng Li Ying
Published: December 2012

Taking into account that the Surfacelet hard threshold video de-noising would produce pseudo-Gibbs phenomenon, this paper proposes Surfacelet transform video de-noising method combining Cycle Spinning. Experimental results show that video which is processed by this algorithm not only eliminates the pseudo-Gibbs phenomenon which is produced by hard threshold de-noising, but also achieves higher PSNR, significantly improving the video quality after de-noising.
A Method of Hopfield Neural Network Based Nearest Neighbor Mode Solving Logistics Distribution
Authors: Yu Bin
Published: December 2012

To solve the problem of invalid and not optimal result for Hopfield neural network to logistics distribution, a nearest neighbor mode Hopfield neural network algorithm based on improved-loop is constructed. The solution of logistics distribution is initialized by nearest neighbor matrix, to seek optimized solution of logistics distribution with the energy function evolvement of Hopfield neural network. To verify this algorithm and the result of simulation, which is compared to other well-known algorithms, indicated that , nearest neighbor mode Hopfield neural network algorithm would avoid invalid result, and better than other well-known algorithm both in convergence rate and quality of optimization.
Using Artificial Bee Colony to Improve Functional Link Neural Network Training
Authors: Mohmad Hassim Yana Mazwin , Ghazali Rozaida
Published: December 2012

Artificial Neural Networks have emerged as an important tool for classification and have been widely used to classify non-linearly separable pattern. The most popular artificial neural networks model is a Multilayer Perceptron (MLP) that is able to perform classification task with significant success. However due to the complexity of MLP structure and also problems such as local minima trapping, over fitting and weight interference have made neural network training difficult. Thus, the easy way to avoid these problems is by removing the hidden layers. This paper presents the ability of Functional Link Neural Network (FLNN) in overcoming the complexity structure of MLP, using it single layer architecture and proposes an Artificial Bee Colony (ABC) optimization for training the FLNN. The proposed technique is expected to provide better learning scheme for a classifier in order to get more accurate classification result.
Determination of Major Metabolites of Aspirin Using HPLC-DAD Combined with SWATLD Algorithm
Authors: Sun Jian Qi
Published: December 2012

The highly overlapping chromatograms and spectra of the major metabolites of asprin, salicylic acid (SA) and gentisic acid (GA) in the presence of uncalibrated and interfering pyrocatechuic acid (PA) were resolved using HPLC-DAD combined with SWATLD algorithm. The elution time was set from 0.6628 min to 0.9495 min and the detection wavelength was chosen from 268 nm to 332 nm. Both SA and GA were determined simultaneously in aqueous solution with their recoveries were (100.5 ± 6.7) % and (109.2 ± 5.3) %, respectively. The satisfying results indicate this method can be easily performed and applied to solving second-order calibration problems quickly and accurately.
Energy Demand Forecast of City Based on Cellular Genetic Algorithm
Authors: Cheng Yu Gui
Published: December 2012

As a branch of genetic algorithm (GA), cellular genetic algorithm (CGA) has been used in search optimization of the population in recent years. Compared with traditional genetic algorithm and the algorithm combined with traditional genetic algorithm and BP neural network, energy demand forecast of city by the method of combining cellular genetic algorithm and BP neural network had the characteristic of the minimum training times, the shortest consumption time and the minimum error. Meanwhile, it was better than the other two algorithms from the point of fitting effect.
Failure Mode Recognition Clustering Algorithm Based on Manifold Learning
Authors: Lou Zhi Gang , Liu Hong Zhao
Published: December 2012

Manifold learning is a new unsupervised learning method. Its main purpose is to find the inherent law of generated data sets. Be used for high dimensional nonlinear fault samples for learning, in order to identify embedded in high dimensional data space in the low dimensional manifold, can be effective data found the essential characteristics of fault identification. In many types of fault, sometimes often failure and normal operation of the equipment of some operation similar to misjudgment, such as oil pipeline transportation process, pipeline regulating pump, adjustable valve, pump switch, normal operation and pipeline leakage fault condition similar spectral characteristics, thus easy for pipeline leakage cause mistakes. This paper uses the manifold learning algorithm for fault pattern clustering recognition, and through experiments on the algorithm is evaluated.
Research on Immune Algorithm of Subregional Caccine Extraction
Authors: Jiao An Quan , Li Xiao Ling , Zhong Sheng
Published: December 2012

Based on the analysis of the flaw mechanism of tradition genetic algorithm and critically inheriting the immunity theory foundation, the paper proposes a new optimized algorithm - Subregion Artificial immunity Optimized Algorithm Based on Parallel, which can speed up the partially convergence and at the same time maintain the global convergence through the simulation of actual immunity behavior of organism. The basic thought of this algorithm is firstly to divide a complex question into several simple questions, secondly to carry out parallel “immunity” computation according to those simple questions, thirdly to pour the results (the antibodies) into the global immunity algorithm, which not only simplifies the complex question, but also raises the efficiency of the algorithm.
Study of Test Cases Prioritization Based on Ant Colony Algorithm
Authors: Chen Lu Lu , Zhang Ling
Published: December 2012

Regression testing is an important activity to ensure the quality of software. In order to improve the efficiency of regression testing, in this paper, the author proposes to reorder test suite based on ant colony algorithm in regression testing, and compare the result with other common sort results. Through experiment, it shows that the method can get the optimal sequence of test cases under the time limit and it has been proven a superior method in both effectiveness and efficiency for test cases prioritization.
A Video Quality Assessment Model Based on Edge Information
Authors: Wei Xue Hui , Zhao Meng
Published: December 2012

Video quality assessment can be gotten by combination the distortion in the space area and the time area. As we all known that edge information is one of the most important features in image quality estimation. Based on the edge model in the perceived image quality estimation, we used it in the space and time area in the video, and get the edge information distorted model in space area and time area of the video. Using multilinear regression to combine the two models, we can get the video quality assessment model based on edge information. The proposed model only uses the edge information, and the consumption in both areas is small. After compared with other methods given by video quality estimation group, it’s found that our method is convenient and good at the 50 Hz video sequence of low bit rate(768kb/s -4.5 Mb/s).
A Method of Chinese Texts Sentiment Classification Based on Bayesian Algorithm
Authors: Yang Ai Min , Zhou Yong Mei , Lin Jiang Hao
Published: December 2012

In this paper, the author did the sentiment classification experiment with Chinese hotel reviews from internet based on semantic lexicon and Naive Bayesian. Many experiments have shown the method in order to improve the accuracy of sentiment classification, and time shortened of text processing, the method can also be used in fast sentiment classification for mass data of Chinese texts.
A Multi-Ink Color-Separation Algorithm Improving Printing Quality
Authors: Tang Hong Jun , Xiu Xiao Jie
Published: December 2012

Conventional color-printing systems often use three or more inks, such as CMY, CMYK or CMYKLcLm. When the inks hues exceeds three, such as CMYKRGB, CMYKOrG and so on, there is the usual color-management one-to-many mapping problem. An algorithm was developed for multi-inks printing in which the one-to-many mapping problem was overcome by dividing the standard color space into several sub-spaces, founding the relationships between the sub-spaces and the printing color-separations and building the lookup table. The algorithm was tested using a digital inkjet printer-Mutoh8000 of CMYKOrGB. Mutoh8000 prints separated color blocks using this algorithm were compared with a generic ICC profile for CMYKLcLm prints. The CMYK inks were common to both prints. The algorithm has been proved effective and improved color printing quality significantly.
Moving Object Detection and Tracking Algorithm Based on Background Subtraction
Authors: Ye Qing , Zhang Yong Mei
Published: December 2012

Moving target detection and tracking algorithm as the core issue of computer vision and human-computer interaction is the first step of intelligent video surveillance system. Through comparing temporal difference method and background subtraction, a moving object detection and tracking algorithm based on background subtraction under static background is proposed, in order to quickly and accurately detect and identify the moving object in the intelligent monitoring system. In this algorithm, firstly, we use background acquisition method to receive the background image, then use the current frame image and the received background image to perform background subtraction in order to extract foreground object information and receive the difference image; secondly, we use threshold segmentation and morphology image processing to process the difference image in order to eliminate noises and receive the clear binary moving object image; finally, we use the centroid tracking method to track and mark the moving object. Experimental results show that the algorithm can effectively and quickly detect and track moving object from video sequence under static background. This algorithm is easily realized and has good real-time and robust, which is automated and self triggered for background updating. The algorithm can be used in driver assistance systems, motion capture, virtual reality and other fields.
Process Optimization Based on Artificial Neural Network of Potassium Hydroxide to Preparing Biodiesel
Authors: Wang Chang Mei , Wu Shao Bing , Zhang Wu Di , Chen Yu Bao , Yin Fang , Liu Shi Qing , Liu Jing , Zhao Xing Ling
Published: December 2012

In order to obtain the optimal technological conditions of preparing biodiesel, artificial neural network was used to study the biodiesel processing model on transesterification method based on the single factor experiment and orthogonal experiment. The results of experiment indicated that we used the back propagation BP algorithm of artificial neural network to set the network prediction model based on the orthogonal test data can forecast the biodiesel conversion rate under different reaction conditions more accurately.The optimal conditions were obtained from this network model as follows: Molar ratio of methanol to oil was 6:1, the catalyst was 1.0% (w/w, based on oil), reaction temperature and reaction time was 65°Cand 2.5h respectively. Under the optimal conditions, the conversion rate of prediction was 94.93%, the conversion rate of experiment was 95.42% and the relative error was 0.51% compared with the predicted value. Therefore, the network k model could reflect inherent law of sample.
An Improvement of Non-Local Means Denoising Method in the Presence of Large Noise
Authors: Salih Musab Elkheir , Zhang Xu Ming , Ding Ming Yue
Published: December 2012

The performance of singular value decomposition (SVD) based nonlocal mean (NLM) denoising method degrades when the noise is high. This paper describes an approach of an improvement of NLM denoising when the noise is large. Instead of SVD, we combine the kernel principal component analysis (KPCA) with NLM. It is demonstrated in terms of peak signal to noise ratio (PSNR) in decibels (dB) that the NLM denoising method is improved using various test images corrupted by large additive white Gaussian noise (AWGN)
Research on NoC Power Consumption Mapping Based on GPU Accelerating Ant Colony Algorithm
Authors: Bai Yu Dong , Yang Wei , Chen Qiao , Chen Jing Yu
Published: December 2012

As the power consumption becomes a hot topic in the field of NOC, many researchers are studying the design technology that minimizes the power consumption of NOC. Some articles realize the NoC mapping by ant colony optimization algorithm. However, by these methods, the system consumes much more CPU time when the scale of the problem or the amount of ants increases. In this article, by GPU acceleration, the scale of the problem to be solved can be increased linearly with the increasing of ants.
On Density-Based Clustering Algorithms over Evolving Data Streams: A Summarization Paradigm
Authors: Amini Amineh , Wah Teh Ying
Published: December 2012

Clustering is one of the prominent classes in the mining data streams. Among various clustering algorithms that have been developed, density-based method has the ability to discover arbitrary shape clusters, and to detect the outliers. Recently, various algorithms adopted density-based methods for clustering data streams. In this paper, we look into three remarkable algorithms in two groups of micro-clustering and grid-based including DenStream, D-Stream, and MR-Stream. We compare the algorithms based on evaluating algorithm performance and clustering quality metrics.
Variable Step Size LMS Adaptive Filtering Based on Genetic Algorithm
Authors: Shi Jian , Zhang Hua Dong , Wu Guo Hui
Published: December 2012

A common form of variable step size LMS algorithm is presented，which is derived by the extensive analysis about several variable step size LMS algorithm. Using genetic algorithm parameter optimization, the algorithm get the optimal valueα、β、m and h quickly and efficiently，and not rely on experience or method of trial and error. MATLAB simulation results confirmed the theoretical analysis, the algorithm took on good convergence and tracking properties，and could be widely used in modern digital communication systems.
Uncertain Reliability of a Series System via Non-Linear Programming
Authors: Liu Huan Bin , Dang Shao Hua
Published: December 2012

In this paper, a new algorithm has been introduced to construct the membership function and non-membership function of uncertain reliability of a series system via non-linear programming techniques, which having components following different types of intuitionistic uncertain failure rates.
Dynamic Textures Retrieval Using the Integrated Wavelet-Based Surfacelet Transform
Authors: An Zhi Yong , Liu Pei Qiang , Jiang Hai Lan
Published: December 2012

To reduce the redundancy, a new integrated wavelet-based surfacelet transform(WBST) is proposed. The integrated WBST is constructed by combining the integrated 3D non-redundant wavelet with nonsubsampled directional filter banks. For 3D non-redundant wavelet transform, there are seven high frequency sub-bands and one high frequency sub-bands. Therefore, we design the integrated scheme with three high frequency sub-bands. In order to get the texture-spatial features, 3D local binary pattern (3D LBP) is used to describe the dynamic texture feature of low frequency sub-band. The mean and standard deviation of coefficients in each sub bands can be used as the high frequency features. Experiments show that the proposed algorithm using the integrated WBST outperforms the 3D WT.
Research of P2P Searching Technology Based on Distributed Hash Table
Authors: Zhang Xiao Hong , Zhang Jian , Lou Li
Published: December 2012

This paper expatiate the principle ,structure ,and the methods based on P2P resource searching technology by classifying the features，conclude and analyse present main developing directions and development state- Put forward a MRD algorithIT1 which is based on Distributed Hash Table(DHT), and conclude with efficiently searching probability of Networking resource searching by mathematic analysis alast.
Study on the Application of Improved Artificial Fish Swarm Algorithm in the Initial Alignment of the SINS
Authors: Zheng Zhen Yu , Gao Yan Bin , He Kun Peng
Published: December 2012

In the process of inertial alignment for an strapdowm inertial navigation system(SINS) on stationary base , the azimuth error’s poor observability leads to its long alignment time . In order to solve the problem,the paper considers inertial alignment as an optimizing process with the application of improved artificial fish swarm algorithm.Simulation results show that improved artificial fish swarm algorithm has rapidly,global and local optimizing characteristics.After applicating on SINS initial alignment,alignment accuracy is almost the same as the limited precision,however,the azimuth alignment times are greatly reduced.
A Combinatorial Algorithm for Generalized Maximum Flow Problem in Lossy Network
Authors: Dong Li Wei , Zhang Xiaofen , Wang Hong
Published: December 2012

This paper first presents the method for finding a generalized augmenting path according to the idea of Dijkstra's algorithm. Then the combinatorial algorithm for solving the generalized maximum flow is given in lossy network. The algorithm runs in strongly polynomial times by finding the generalized f-augmenting path in a generalized residual network.
Fast Mining of Closed Frequent Itemsets in Data Streams
Authors: Mao Yi Min , Chen Zhi Gang , Liu Li Xin
Published: December 2012

With the emergence of large-volume and high-speed streaming data, traditional techniques for mining closed frequent itemsets has become inefficient. Online mining of closed frequent itemsets over streaming data is one of the most important issues in mining data streams. In this paper, a combinative data structure is designed by using an effective bit-victor to represent items and an extended dictionary frequent item list to record the current closed frequent information in streams. For tremendous reduction of search space, some new search strategies are proposed to avoid a large number of intermediate itemsets generated. Meanwhile, some new pruning strategies are also proposed for the purpose of efficiently and dynamically maintaining of all the closure check operations. Experimental results show that the method proposed is efficient in time, with sound scalability as the number of transactions processed increases and adapts rapidly to the changes in data streams.
A Differential Evolution Algorithm Based on Self-Adapting Mountain-Climbing Operator
Authors: Lei Sheng , Liu Wei , Cai Yao He
Published: December 2012

This paper presents a Differential Evolution algorithm based on Self-Adapting Mountain-climbing operator (LCDE) to overcome the problem of low convergence speed and bad local searching ability in the evolution period. The algorithm dynamically adjusts the value of climb radius during using the information of the individual search efficiency in the search process. The experiment results demonstrate that the new differential evolution algorithm has fast convergence speed and high computation precision.
Auxiliary Problems in Convex Alternating Structure Optimization Algorithm
Authors: Zhang Tao Zheng , Wang Xiao Jie , Chai Jian Ping
Published: December 2012

There exist principles of Relevancy, Orthogonality and Domain Adaptation for auxiliary problems (APs) selection in Alternating Structure Optimization (ASO) algorithm. Convex Alternating Structure Optimization (cASO) algorithm is an improved one based on ASO algorithm, whose kernel still lies in creating excellent APs. In order to validate the effectiveness of the preceding principles in cASO algorithm, many types of APs were created by taking example of Chinese syntactic chunking. Experimental results and analyses both demonstrate that those principles still hold in cASO algorithm.
Visual Tracking Using Combining Motion Constraint Model and Online Multiple Instance Boost Random Ferns
Authors: Zheng He Rong , Huang Ye Jue
Published: December 2012

Video object tracking is essential algorithm for computer vision applications. An object tracking algorithm using combining motion constraints model and online multiple instance boost random ferns is proposed, which use IIR filter to obtain online learning for random ferns, and the random ferns are selected by online multiple instance boosting to construct classifier of online multiple instance boost random ferns. To reduce effects of tracking error accumulation, object motion constraint model is constructed to constrain the results classified by online multiple instance boost random ferns to locate object correctly, and construct positive and negative set to online update the classifier. The experiment shows that the proposed method achieves competitive detection results, which are comparable with state-of-the-art methods.
Research of Motion Tracking Based on CamShift Algorithm
Authors: Zhu Li , Hu Hang
Published: December 2012

At present, objects detection, identification and tracking according to machine vision technology, have been widely used in various economic aspects. In this paper, a real-time monitoring system was discussed. This surveillance system mainly combines two sub-systems, motion detection and objects tracking. An Adaptive Gaussian Background Model was established in order to automatically update the background and detect the outline of moving objects. By analyzing different algorithms, this paper brings out approaches to promote the performance.We proposed CamShift algorithm to complete motion detection and objects tracking, which applied for static background video sequences. And the experimental results show that our method can achieve the pre-determined targets.
Circle Pose Estimation Based on Stereo Vision
Authors: Ma Wen Juan , Sun Shu Sen , Song Jin Yu , Li Wen Shu
Published: December 2012

This paper presents a simple method of circle pose estimation based on binocular stereo vision. It takes the projective equation of a circle as the basis, and gives the closed form solution of the pose parameters. Since there are two possible sets of pose parameters for a circle from one calibrated perspective view, the stereo vision constraints are incorporated and the accurate pose parameters are determined. Experiments using computer simulated data and real data demonstrate the robustness and accuracy of our method.
Clinical Breast Cancer Analysis with Surface Fitting in the Medical Thermal Texture Maps
Authors: Ye Fuli , Shi Gui Lian
Published: December 2012

This thesis tries to calculate quantity and distribution of heat source in vivo from body surface temperature. A superposition temperature image of a number of point heat sources is surface fitted to get the Q of heat sources (information of cancer cells) quantitatively. More precisely, surface fitting the surface of temperature distribution based on T formula of multiple heat sources with MTLAB software. The result can reflect the disease area information because cancer cell’s Q value is much higher than that of normal cell. This application is a new try in the diagnosis of breast cancer, has an important value on the early detection and diagnosis of disease source.
Research on Wear Debris Recognition Based on Patch Similarity of Anisotropic Diffusion and BP Neural Network
Authors: Kang Jian Li
Published: December 2012

Wear debris recognition,which is based on patch similarity of anisotropic diffusion algorithm and BP neural network,is researched.At first, feature parameter refining of wear debris image,which was based on patch similarity of anisotropic diffusion algorithm feature parameter refining,was researched.Second,wear debirs classifier,which was based on the BP neural network and the first step,was researched.At last,with experiment results and experiment results analysis,the wear debris recogniton system in the paper is proved to be some merits,which include high classification accuracy,fast learning convergence rate and high recognition rate.
An early Mode Decision Algorithm for the Enhancement Layers in H.264 Scalable Video Coding
Authors: Yuan Chun , Xu Bo Lin
Published: December 2012

This paper presents a early mode decision algorithm, which is proposed to reduce the complexity of the mode selection process for enhancement layers in H.264 Scalable Video Coding. The proposed algorithm consists of the following three main steps. We firstly divide all the macroblocks into 4 classes according to the mode of collocated macroblocks in the base layer. Then, the macroblocks are subdivided with trained BP (Back Propagation) network according to the mode of neighboring macroblocks. Finally, we choose different mode selection algorithms for different divided cases, and check whether the algorithms are agreeable. Compared to JSVM 9.18, experiment results show that, with this algorithm, 30% encoding time can be saved with a negligible loss in BDSNR, and BDBR can be significantly reduced.
A Method of Getting Special Landmark Outline in Satellite Image
Authors: Li Chang Hai , Liu Yan Chun , Xu Zhen Dong
Published: December 2012

In allusion to non-exactness edge positioning in the process of place a three-dimensional model, a method of multi-scale wavelet transfer is applied to obtain edge signals from satellite image and perform pixel dot correction, which is proved to give prominence to the landmark edge curve without avoiding sacrificing the precision position of the target landmark edge .This method, with fixed dot correction, makes it more convenient and more precisely to settle down edge positioning in the process , in order to place a three-dimensional model.
Research of Image Processing Based on Lifting Wavelet Transform
Authors: Li Ren Chong , You Yi Long , You Feng Xiang
Published: December 2012

This paper Study problems which based on lifting wavelet transform image processing. Coding and decoding a complete digital image by using W97-2 wavelet basis wavelet transform, combined with the embedded zerotree wavelet coding and binary arithmetic coding, and complete a lossless compression combined with the international standard test images. Experimental results show that graphics, image processing will come into a higher level because of wavelet analysis combined with image processing.
Researching Skyway Design Based Digital Aerial Photogrammetric Camera
Authors: Li Tian Zi , Liu Chang Hua , Wang Hong Tao
Published: December 2012

SWDC aerial camera series，developed and produced independently by our country, uses the automatic exposure to replace artificial manual exposure and the high precision fixed-point exposure to replace time exposure. So that we need our own design of perturbation site and the data interface which is suitable for the operating system of automatic exposure. What we should do is to research the things routes, north-south routes as well as inclined routes, and come up with computer algorithm after ascertaining the parameters of the aerial camera, measured area and plotting scale. In order to examine the perturbation sites, we have designed the algorithm and made it accessible.
The Application of LabVIEW and IMAQ in Image Acquisition and Processing
Authors: Zhang Hui , Gao Ling , Liu Jing , Wang Zhao Xin , Zhai Yan Nan
Published: December 2012

This paper which is based on digital image process technology, with LabVIEW and IMAQ Vision,designs a effective method about image acquisition and processing. The system achieve image acquisition,save,playback,gray transformation,denoise,threshold segmentation ,template matching and calculation the center of the target lacation.Virtual Instrument which own flexible hardware and software,has greatly enhanced efficiency and accuracy.
3D-Visualization for DICOM Series Based on ITK and VTK
Authors: Dong Hui , Xia Ling , Peng Zhi , Zhang Jin
Published: December 2012

Nowadays, medical image processing and three-dimensional visualization have become a very important support for doctor diagnosis and treatment planning. It’s a novel technology that using ITK and VTK to process and display medical images in VC++. In this paper, the Curvature FlowImageFilter class of ITK libraries is used to denoise and smooth the medical images. The MC algorithms is used to reconstruct the volume data in the VS2008. Immediate Mode algorithms and Stripper filter algorithms are adopted to speed up large data processing. The experiment results demonstrate that using the MC algorithms and the acceleration algorithms base on the VTK can implement 3-D visualization efficiently and satisfy practical applications.
Quadrilateral Extraction Method and its Application on Parking Cell Detection
Authors: Wang Mei , Wang Zuo Peng , Chu Yong Ling
Published: December 2012

This paper presents a quadrilate extraction method based on four vertices of the image object to solve the problrm of object area inaccuracy depending on conventional rectangular segmentation method. Firstly, four vertices are given by the mouse-click depending on quadilateral object spatial feature; and then the quadrilateral object shape feature is estimated by each side of the quadriangle computing by straight-line formulation of two adjacent vertices of object in order to acquare the quadrialeratal object inernal pixel. At last, the pixels of quadrialeratel external region are cleaned. Arbitrary quadrilateral region segmentation is achieved accurately. The method can be used for any quadrilateral region segmentation based on image processing, The experiments on actual color parking images show any parking cell template extraction accuracy reached 100% and parking cell state detection accuracy is 99.8%. The result verifies the algorithm effectiveness and robustnes
Research and Analysis of Edge-Detection of Digital Images
Authors: Wang Li Yuan , Kang Kai
Published: December 2012

Edge-detection is the basic characteristic of images. Edge-detection plays an important role in computer vision and image analysis, it is the key link of image analysis and recognition. In this paper, we mainly analyze several edge-detection operators, research the processing results. The edge-detection operators mainly include Roberts operator, Prewitt operator, Sobel operator, Canny operator and LoG operator. Finally we discuss the advantage and disadvantage of the edge-detection operators.
Automatic White Balance Based on Gaussian Decomposition
Authors: Hu Yong
Published: December 2012

In this literature, an automatic white balance adjustment algorithm based on Gaussian decomposition is proposed. The improved algorithm is aiming at handling the problem occurred in automatic white balance algorithm, such as lack of correction or high complexity. First, Gaussian distribution of gray level is obtained by using Gaussian decomposition. And then, gain curve of each component in RGB color image are calculated by the parameters. After the coefficient is used for white balance adjustment, a corrected image is finally obtained. Experimental results show that the algorithm can effectively correct the image color cast problems, and are suitable for a variety of different scenarios.
Phased Array Radar Signal Recognition Method Based on Ant Colony Optimization and SVM
Authors: Pu Jian Feng , Lin Jun , Li Yan Zhi , Quan Wei
Published: December 2012

In order to improve the efficiency for phased array radar's ESM, an ACO and SVM conjoint method is used in this paper to solve the problem of phased array radar signal recognition. By introducing ACO to supervise SVM parametric selection, the method is able to quickly discover seemly parameter value and improve SVM separation efficiency. Experimental results show that textual algorithm possess upper exactness rate to phased array radar that the whole pulse signals sorting can be identified. With normal-SVM and RST-SVM means to compare, the algorithm SVM parameter access time is short, thereby shorten the monolithic hour.
A Dynamic Fuzzy Sets Method and its Application to Pattern Recognition
Authors: Zhang Zhen Hua , Hu Yong , Ke Xiao Hua
Published: December 2012

We present a novel dynamic fuzzy sets (DFS) method, which is the generalization of fuzzy sets (FS) and the dynamization of interval-valued intuitionistic fuzzy sets (IVIFS). First, by analyzing the degree of hesitancy, we propose a DFS model from IVIFS. Second, we introduce the distance measure of DFS. Finally, a pattern recognition example is given to demonstrate the application of DFS, and the experimental results show that the DFS method is more effective than some IVIFS methods.
An Approach for Extracting Neighborhood Points of Surface Intersection Curves
Authors: Cheng Jun Ting , Zhao Hong Feng , Zhao Can
Published: December 2012

This paper comes up with an approach for surface reconstruction from arbitrary, unorganized and intersecting curves. First of all, camera calibration determines the interior and exterior camera parameters. Based on laser triangulation measurement, the point in world coordinate system can be computed. The extracted curves are processed in a volumetric in which a vector field is built and updated to compute the neighbor-hood points. Then the surface reconstruction can be obtained with MC algorithm. This approach makes surface reconstruction and curves registration a unified procedure. This algorithm solves the problem of linear complexity respect to input curves, and makes it suitable for interactive modeling. The experiment verifies its available, reduces the effect of registration errors and has a good result.
Image Classification Algorithm Based on Structural Information
Authors: Chen Yu Feng , Yang Zhi Zhong , Yan Gao Jie , Li Fei Fei
Published: December 2012

Bag of words algorithm is to integrate visual words, described the local features of the object, together to form a bag model. It does not consider the structural information of the object, considering only the local features. This paper presents an image classification algorithm based on structural information. Algorithm adds the structural information of the object according to the ideas of generalized Hough transform. We use the structural information on the local features of the test image with generalized Hough transform and get the possible position of the center of the object. Then, we have to analyze the template size on the basis of the dispersion degree of the voting points, and finally optimize the voting results. Experimental results demonstrate that our proposed method is superior to the method which does not consider the structural information and uses the low-level features to classification.
Improved Tracking-Learning-Detection Human Tracking Algorithm
Authors: Liang Yan , Pan Feng , Yang Bo , Li Wei Xing
Published: December 2012

For the problem that appearance of human will be changed in motion, it is a challenge to those capabilities of tracker, related to adaptation of human appearance. In the paper, an improved Tracking-Learning-Detection algorithm, including short-term-tracking, real-time-detection and online-learning, is proposed. Furthermore, scale-invariant feature is applied to the short-term-tracking to determine the location of target in consecutive frames. The video stream of the PETS2006 database is utilized to evaluate the proposed algorithm. Experiments results demonstrate the effectiveness, especially on the short-term-tracking performance.