Computer Science
Computer Science
Started in January,1974（Monthly）
Supervised and Sponsored by Chongqing Southwest Information Co., Ltd.
ISSN 1002-137X
CN 50-1075/TP
CODEN JKIEBK
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Current Issue
Volume 41 Issue Z6, 14 November 2018
  
Survey on Vehicular Ad hoc Network Based Intelligent Transportation System
CHENG Jia-lang,NI Wei,WU Wei-gang,CAO Jian-nong and LI Hong-jian
Computer Science. 2014, 41 (Z6): 1-10. 
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This paper reviewed the state-of-the-art in VANET-based ITS application and gets insights into the topic,firstly analyzed the challenges to be addressed and then reviewed existing works．According to the purpose of solutions and approaches used,we provided an overall categorization of existing works and discussed them with deep analysis．Different approaches were compared with pros and cons．Based on the analysis of existing works,we found out problems to be addressed and directions of future research．
Survey and Research Trends of Workflow Modeling Techniques
CHEN Guang-zhi,PAN Rong and LI Lei
Computer Science. 2014, 41 (Z6): 11-17. 
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With the comprehensive application of Workflow Management System (Business Process Management System),workflow technologies have drawn a great deal of attentions from researchers and practitioners,meanwhile the research of workflow modeling techniques also gets a more attentions．Since the workflow model plays a core role in workflow technologies,the workflow modeling techniques have been broadly researched,and a variety of modeling techniques are emerged．In the paper,we introduced and discussed 11mainstream workflow modeling techniques,and classified them according to our classification standard which is proposed in the paper.For some of them,we presented their core graphical symbols and utilized the open source tool to draw the workflow model examples of them．Finally,we summarized some research hotspots and research trends for workflow modeling techniques.
Several Techniques Used in Parameterized Computation
ZHOU Xing and PENG Wei
Computer Science. 2014, 41 (Z6): 18-23. 
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Parameterized computation and complexity are one of the techniques arised in the end of last century and the beginning of the current one．Because of its solid theoretical foundation and excellent running performance,it has achieved much success despite of its short-time development．In a trend,parameterized computation is becoming a hotter and hotter branch of computer science．This paper first introducesd the important theoretical base and key idea of parameterized computation,then mainly introduced the key techniques used in it,introduced its function,basic design principles and advantages/disadvantages for every technique,and used simple examples to explain it.
Verification for Robustness of Chroma Feature
ZHANG Xiu,LI Nian-zu and LI Wei
Computer Science. 2014, 41 (Z6): 24-28. 
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Content-based cover song detection is a hot research program in the field of music information retrieval in recent years．With the consideration that the different versions of music may change in many aspects,such as tempo,speed,pitch,timbre and structure,the key factor in this research is to extract robust audio feature,which can represent songs’ main melody progress,and compare their similarities between cover songs．Chroma features express the distribution of audio energy among different pitch class,consider presence of harmonics ,timbre independence and robustness to noise,so are used by a lot of cover song detection systems．Based on the theory,we designed and conducted the experiment to explore the effect of different forms of audio interference,and verified Chroma’s robustness in the aspect of pitch invariance.
Artificial Bee Colony Algorithm Based on Ito Algorithm
ZHAO Zhi-yong,LI Yuan-xiang and YU Fei
Computer Science. 2014, 41 (Z6): 29-32. 
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When resolving complex problems,the artificial bee colony (ABC) has some disadvantages of slow convergence rate and easy to fall into local optimization,with the inspiration of the Brownian motion and Ito process,and imitating the designed idea of Ito algorithm,this paper proposed a improved artificial bee colony based on Ito algorithm (BMABC)．We designed different drift operator and fluctuation operator in the phases of the employed bees and the onlookers respectively．The drift operator ensures the drift direction to the optimal solution．The fluctuation operator ensures the diversity of the solutions．ABC,GABC and BMABC were tested by five classic functions．Experimental results show that BMABC retains the fast convergence and high convergence precision characteristics,as well as better stability.
(V,R)-Languages
SHI Hai-zhong and SHI Yue
Computer Science. 2014, 41 (Z6): 33-36. 
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V is an alphabet.FV is a free semigroup on V．R is a subset of FV．At first,we proposed a concept—(V,R)-semigroup and proved that graph-semigroup and digraph-semigroup are both(V,R)-smigroups．Second,we proposed a concept—hypergraph semigroup．The theories of hypergraphs and free semigroups are connected by the hypergraph semigroups．On this base,we proposed two concepts--(V,R)-languages and hypergraph language．The theories of hypergraphs and formal languages are connected by the hypergraph languages．Furthermore,we proved that the hypergraph language,undirected graph and digraph language are all(V,R)-languages．Third,we proved that the undirected graph language and the digrapg language are both regular languages,which answers the open problems in references of “undirected graph languages” and “digraph languages “．(V,R-)semigroups and(V,R)-languages are new theories and methods of studying free semigroups and formal languages．
Survey of Bio-inspired Natural Computing
KOU Guang-jie,MA Yun-yan,YUE Jun and ZOU Hai-lin
Computer Science. 2014, 41 (Z6): 37-41. 
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Bio-inspired natural computing is a rising interdisciplinary field．The meaning and the research scope of bio-inspired natural computing were introduced firstly．Then the relationships of bio-inspired computing and other branches of natural computing were discussed．Thirdly,the bio-inspired computing models proposed in recent years were classified and reviewed in the following levels:human society,biotic population,individual,tissue and organ,cell,molecule．Finally,the latest developments of these algorithms were introduced.
Task Scheduling Algorithm for MapReduce Based on DAG
TANG Yi-tao,HUANG Jing and XIAO Qiu
Computer Science. 2014, 41 (Z6): 42-46. 
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Hadoop has been the basic platform of cloud computing research,and MapReduce is the computing mode for distributed processing of big data．For heterogeneous cluster,considering MapReduce’s defects in data distribution,data locality and process of the job execution,we proposed a DAG based MapReduce scheduling algorithm．The algorithm groups the nodes based on their computing ability,transforms MapReduce job execution to DAG model and improves upward ranking to achieve better accuracy and a more reasonable sequencing of task priority．By combining the computing ability of nodes,data locality and cluster utilization,choosing the proper data nodes for task distribution and execution,our algorithm shortens task completion time．The experimental result shows that the proposed algorithm can distribute data reasonably,improve data locality effectively,reduce communication overhead,shorten schedule length of set of job,thus improving utilization of cluster.
Neural Network Based Power Prediction Strategy for Multi-core Architecture
YUAN Jing-ling,MIAO Xu-yang,YANG Min-long and XIANG Yao
Computer Science. 2014, 41 (Z6): 47-51. 
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Multi/many-core processor is a trend of computer development．In the design process of multi-core processor,how to find the design structure from a large design space to meet the conditions has become a critical and challen-ging task．In order to solve the high overhead and low efficiency problem of traditional software simulation technology,this paper proposed a model based on neural network to predict the performance and power of multi-core processors,established two kinds of BP and RBF neural network prediction models,used SESC simulator to simulate CPI and power,and compared and analyzed the prediction accuracy and reality of two kinds of prediction models．Simulation results show that the neural network prediction model average error is 1.6%~6.6% in control．Compared to general software simulation method,it can also save time and improve efficiency．More importantly,RBF neural network prediction model has better prediction accuracy.
Modifications and Applications of Harmony Search Algorithm
ZHOU Ya-lan and HUANG Tao
Computer Science. 2014, 41 (Z6): 52-56. 
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Harmony search (HS) algorithm mimicking the improvisation process of music players is a new metaheuristic approach for global optimization．Many researchers have proposed lots of modified versions of the original HS and applied them to a wide range of optimization problems．Firstly,the original HS is introduced．Secondly,these variants of HS algorithms and their applications are reviewed．Finally some future research lines are given.
Survey of Many-objective Optimization Algorithms
ZHOU Cao-chen,CHEN Zi-yu and HE Zhong-shi
Computer Science. 2014, 41 (Z6): 57-60. 
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At present,most multi-objective evolutionary algorithms MOEA (Multi-Objective Evolutionary Algorithms) are designed for the problems of 2～3goals with good optimization results．But for 4or more goals, approximating Pareto front by MOEA and maintaining a low computational complexity are very difficult．This article analyzed the problems caused by the number of objectives in Many-objective optimization algorithm．To solve the problems,some of strategies and algorithms were introduced．This paper introduced the improvement of dominant mechanism in existing many-objective optimization algorithm and focused on a systematic review of many-objective reduction algorithm,comparative analysis of the effectiveness of various algorithms,and gave the directions for further research．
Research on Collision Detection of Convex Polyhedron Based on Mixed Artificial Fish Swarm Algorithm
LIU Hai-ping
Computer Science. 2014, 41 (Z6): 61-63. 
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This paper put forward a detection algorithm based on the shortest distance calculation．The algorithm uses convex polyhedron three dimensional space vertex coordinates of convex hull to present convex polyhedron,and the distance between the convex objects comes down to a non-linear programming problem with a restricted condition．Using mixed artificial fish swarm algorithm solves the problem.In the optimization process,using artificial fish swarm algorithm can quickly find the global extremal neighborhood,and in the late process using pattern search method can accurately find the global extremal．Experiments show that no matter in speed or in accuracy,mixed artificial fish swarm algorithm has more obvious advantage than penalty function method and genetic algorithm.
Method for Verification of LHPN-based Cyber Physical System
QIU Wei
Computer Science. 2014, 41 (Z6): 64-66. 
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Because the cyber-physical system(CPS) hardware integration and software involvement in degree rise ceaselessly,many software and hardware have heterogeneous connectivity and mutual control．The analysis design,modeling of CPS have become more and more difficult．In this paper,a safety verification method based on 1abeled hybrid Petri net and differential-algebraic dynamic logic was proposed．The method firstly transforms LHPN model to differential-algebraic program,then realizas the specification of system safety using differential-algebraic program,and finally the cyber physical systems safety is verified according to differential-algebraic program reasoning rules．It is effectiveness for the method through an instance of the prototype application.
Recognition and Transformation for Element Sub-sentences in Patent Machine Translation
ZHANG Dong-mei and JIN Yao-hong
Computer Science. 2014, 41 (Z6): 67-71. 
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This paper proposed a rules-based method for recognizing and transforming the element sub-sentences to improve the translation quality of them in patent machine translation．By analyzing the format of Chinese element sub-sentences,we extracted the description features,and created the recognition rules based on that．By comparing Chinese and English element sub-sentences,we summarized the differences between them,and created the transformation rules based on that．At last,we applied the rules to an existing MT system．Experiment shows that the method can recognize and transform element sub-sentences,and then improve their translation quality in patent machine translation.
Short-term Wind Speed Prediction Based on EMD-GRNN Combination of Probability and Statistics
ZHU Ya,SUN Dong-mei,HE Xiang and LIU Man-man
Computer Science. 2014, 41 (Z6): 72-75. 
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Referring to raw data of the wind farm and based on the characteristics of wind speed,this article proposed a short-term wind speed prediction algorithm based on EMD-GRNN combination of probability and statistics．The paper firstly preprocessed the original data,then took advantage of empirical mode decomposition (E-MD) on the original wind speed,to get all the basic raw wind modal component (IMF).Nextly,this paper proceeded to reconstruct the data of each component to get the training samples and forecasting samples and utilized the train-ing sample to train GRNN network to make the network predictive capability.Finally this paper made a probability statistics on the output data of the various components．Simulation results show that the EMD-GRNN prediction model of combination of probability and statistics has good predictive accuracy and stability.
New Forecasting Method of Intuitionistic Fuzzy Time Series
LI Na,LEI Ying-jie,ZHENG Kou-quan and DU Ji-jun
Computer Science. 2014, 41 (Z6): 76-79. 
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Aiming at the problem that the existing intuitionistic models lack persuasiveness in partitioning interval and series data intuitionistic fuzzifying,the intuitionistic fuzzy time series forecasting model was advanced．The new method reflects the distribution characters of the uncertain data set accurately by introducing sliding windows scheme,optimizes the domain-dividing interval with the intuitionistic fuzzy C-means clustering algorithm on parameter adjusting,defines series variable intuitionistic fuzzy sets based on the intuitionistic fuzzy distance norm．Consequently,the prediction accuracy of time series in complex environment is improved effectively．Finally,the experimental results validate the efficiency and advantage of the proposed algorithm．
Signal Timing Fuzzy Control Based on Road Green Wave Effect Collaborative Strategy
ZHANG Yi
Computer Science. 2014, 41 (Z6): 80-82. 
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With growth of urban road traffic volume and the increase of road network density,correlation between adjacent road intersections is becoming more and more obvious．An intersection traffic signal adjustment tends to affect the health of a number of adjacent intersections road traffic flow．Its congestion may over time gradually spread to within a few blocks and regions all around the intersection．Therefore increasingly high demands of urban traffic signal control to reach a variety of advanced control technology integration,achieve the purpose to adjust a control parameter,in order to achieve dynamic coordination within the city-wide traffic control,to satisfy traffic demands,and then let the road traffic and the transport demand to reach a new balance．This article introduced the use of the green wave effect collaborative strategies adjacent green extension of fuzzy control in order to solve the problem of coupling between intersections road．This algorithm makes Signal Timing to be more flexible.
Task Scheduling in Cloud Computing Based on Swarm Intelligence Algorithm
CHEN Hai-yan
Computer Science. 2014, 41 (Z6): 83-86. 
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In order to improve the QoS of task scheduling of cloud computing,this paper proposed a cloud computing task scheduling model based on warm intelligent algorithm．Firstly,genetic algorithm which has global search ability is used to quickly find he optimal solutions of cloud computing task ssheduling problem,and then the optimal solutions are converted to the initial pheromone of ant colony optimization algorithm,finally,the global optimal solution of cloud computing task scheduling is obtained by information communication and feedback among ants．The simulated experiment was carried out on cloudsim platform.The experimental results show that compared with other models,the proposed model significantly improves the efficiency of cloud computing tasks scheduling and reduces the completion time.
Keyphrase-based Chinese Tags Generation Hybrid Algorithm
LIU Dong and ZHANG Cai-huan
Computer Science. 2014, 41 (Z6): 87-90. 
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This work provided an algorithm HTGA(Hybrid Tags Generation Algorithm) to generate tags for Chinese documents,which extracts phrase chunks as candidate keywords,and considers other factors like TF.IDF,words span etc．Experiments show that this algorithm improves the accuracy of keyword extraction,and has a stable performance over various texts．Some samples were extracted and compared with the standard answers．There are more than 60% results that are as well as or better than the standard answers in reflection of document topics.
Method of Short-term Load Forecasting Based on GA and SVM
MENG Fan-xi,QU Hong and HOU Meng-shu
Computer Science. 2014, 41 (Z6): 91-93. 
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In this paper,a method based on support vector machine and genetic algorithm was proposed for the power system load forecasting．In this method,a next hour load forecast is developed by using structure risk minimization instead of traditional empiric risk minimization to mine more information from the original data.The genetic algorithm is used to optimize the SVM parameters to improve the performance of forecasting and the training speed．Historical load,atmospheric data and the calendar factors are the model inputs．Forecasting results show that this model is effective and feasible,as well as the better robustness and forecast accuracy than the BP neural method．
Bus Line Scheduling Research Based on Residents’ Travel Behavior Analysis
LI Zhang-wei,GUO Bing-bing,MING Jie and ZHANG Gui-jun
Computer Science. 2014, 41 (Z6): 94-97. 
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On a city bus for residents travel peak pressure,we established the bus line scheduling model which is mainly based on residents' travel behavior analysis．The model uses survival analysis theory to analyze the influence factors of residents travel time,find out the urban residents travel time interval science tumble,and construct nonlinear programming model function on bus headway of the peak time in the region．Model function includes the time cost of passengers and the bus company operating costs,introduces weighting factor,and uses particle swarm algorithm to get the best grid interval．On the basis of Hangzhou citizens travel data in a given area,the article derived optimized scheduling schedule from empirical studies,verified the feasibility and validity of the model.
Natural Language Semantic Representation Based on Cognitive Linguistics
YE Xi-jun and YIN Yan
Computer Science. 2014, 41 (Z6): 98-102. 
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Semantic network is valid to semantic understanding and common sense reasoning,but coarse-grained semantic is difficult to represent complex relationship between objects．Though cognitive linguistics provides approaches to represent complex object-relational,it’s difficult to support natural language processing because of its abstract．This paper presented a method of natural language semantic representation based on cognitive linguistics．The method uses image schema to represent the relationship between object nodes in semantic network,and attribute spaces to represent the semantic of object which can be digitized(such as color)．On this basis,we transformed the building and modifying process on semantic network and attribute space into a sequence of semantic operations,so that we could reconstruct the semantics of sentences dynamically．Compared to the traditional method of semantic representation based on semantic network,the proposed method can express dynamic relationship and has stronger reasoning ability．The paper gave examples to prove the feasibility of this approach.
ADST:Approache of Automated Differentiating Sarcoidosis from Tuberculosis Based on Statistical Learning Theory
CHEN Ai-xiang and CHEN Zhi-feng
Computer Science. 2014, 41 (Z6): 103-109. 
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Differentiating sarcoidosis from tuberculosis is still difficult．The support vector machine is a powerful tool in statistical learning.In this paper,we collected 106cases of sarcoidosis and tuberculosis,used an SVM to build a disease classifier named ADST(Automated Differentiating Sarcoidosis from Tuberculosis).In order to get the raw medical data into a form usable by SVM,we extracted feature vectors of the raw medical data by turnning the qualitative feature into digital one and dropping the features that do not have much classification value.Then ADST conducts simple scaling on the data,uses cross-validation to find the best parameter of model,uses the best parameter to train the whole training set to obtain the SVM model.Finally ADST uses the resulted SVM model to predict a new patient case.The experiment result shows that the ROC areas of SVM,DCT and NB are 0.978,0.96,0.690respectively,and the training accuracy is 95.28%,90.57%,92.38%,and test accuracy is 100%,96.15%,96.15%．Clinical pratice shows that the classification result is correct:19cases of undiagnosed patients are recovered after treatment according to the results of the diagnosis of ADST.
Journal Evaluation Based on PageRank Algorithm and HITS Algorithm
YU Yi,GAN Ruo-xun,FAN Suo-hai,LIU Qing and SHAO Qing
Computer Science. 2014, 41 (Z6): 110-113. 
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Journal citation network is formed with 31kinds of computer technical core journal in this paper.The PageRank value,authoritative value(authority) and the central value(hub) of these journals are calculated using the algorithms of PageRank and HITS．The comparative study for advantages and disadvantages among impact factor with PageRank value,authoritative value and center value was discussed．The results show that journal impact factor ranking is slightly different from PageRank algorithm,HITS algorithm results ranking,indicating that different evaluation algorithms reflect different journal evaluation purposes.
Research of Reconfigurable Cache Method for Power Calculation in CMP
FANG Juan and CHEN Xin
Computer Science. 2014, 41 (Z6): 114-117. 
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Multicore dynamically reconfigurable Cache is an important way to solve the Cache-power troubled．Existing Cache-power simulator does not support multi-core dynamic reconfigurable Cache-power research, reconfigurable multi-core dynamic power consumption model of the Cache was researched to find the methods and ideas that can calculate reconstruction Cache. CACTI was used to build the structure of the various components Cache power model to more accurately estimate reconfigurable Cache-power．In Simics simulator,building dynamically reconfigurable Cache,running the test,comparing conventional architectures,reconfigurable Cache power consumption can be obtained a 10.4% decrease．Also it is found that the decrease in power consumption is more than just Dynamically Reconfigurable Cache contribution,but the contribution by the integrated system,prompting a comprehensive consideration of the overall system power consumption and performance in a low-power design,to avoid one-sided consideration of the Cache structure,leading to the improvement of the overall power consumption.
Content-based Image Retrieval Using Color Position and Texture Fused Features
HUANG Ren and HU Min
Computer Science. 2014, 41 (Z6): 118-121. 
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Content-based image retrieval is an important and fascinating point in the image retrieval．An image retrieval algorithm based on multiple features was proposed in this paper．First,the color image was transferred into HSV color space,quantized by unequal quantification method,and extracting color feature and each color position message．Then,we implemented image fractal coding based on the center area of the original gray image,and fractal coding parameters are used as texture features．After normalizing each component of the vector and different features by Gaussian normalization method,we combined the color features and the texture features for image retrieval using artificial fish swarm algorithm．The experiment results show that the algorithm can produce good performance in terms of the retrieval effect and the retrieval speed.
Application Research on Comparability Matching for Image-Data Based on Enhanced SIFT Algorithm
ZHANG De-quan and DONG Shi-cun
Computer Science. 2014, 41 (Z6): 122-124. 
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For the deficiencies on efficiency and accuracy of the SIFT(Scale Invariant Feature Transform)algorithm,improvement was made by two ways,in which one is to reduce the overlap computation on major direction and generation of description,and the other is to shrink the search coverage of feature point match．The experiment on the match of moon image database gives a preferable result,in which the real-time performance and matching accuracy are improved.
Improved SIFT Matching Algorithm Based on Orientation Constraint
QI Nai-xin,CAO Li-jia,YANG Xiao-gang and LI bing
Computer Science. 2014, 41 (Z6): 125-128. 
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SIFT algorithm has good invariance in rotation,scaling the image,brightness change,etc.,and is widely used in image matching．But the generation process of SIFT feature vector is complicated,and results in that the real-time of the algorithms is not ideal．In the same time,there are still some matching mistakes in the matching result,affecting the accuracy of the algorithm．Therefore,we improved the SIFT algorithm,and proposed to use the grid in the selection of seed points to simplify the feature vector generation process,and used the orientation constraint of the key points to reject matching points with directional differences,thus simplifying computation and improving the matching rate．Experimental results show that the improved algorithm can maintain the basic stability of the original SIFT algorithm and improves the speed of feature vectors described nearly doubled．Through orientation constraint of the key points,the false match point with direction differences is rejected,and the matching rate is improved,greatly enhancing the accuracy of the algorithm.
Simple Tampered Portrait Identification Algorithm Based on Inconsistent Shadow
WANG Huan-wen,XU Xiao-gang,XU Guan-Lei and WANG Xiao-Tong
Computer Science. 2014, 41 (Z6): 129-131. 
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A simple tampered portrait identification algorithm based on inconsistent shadow was proposed by analyzing of binarization of the image shadow．The algorithm determines whether the image is tampered by first manually selecting the local image of the nose area and chin area,then statistically analyzing shaded area after Ostu binarization process,and finally comparing the shadow consistency between the nose area and chin area．A lot of experimental results show that the method has simplicity,high accuracy,strong reliability and has some practical value in image forensics．
Improved Face Emotion Identification Algorithm by MLS-SVM with Modified Gauss Kernel Function
LU Zhao-gan,XU Chun-mei,SUN Nan and MIAO Xu-na
Computer Science. 2014, 41 (Z6): 132-134. 
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Aiming at the map of the low dimension data space for support vector machines (SVM) to high dimension feature space,the Riemann measure tensor was used to extend the SVM linear disjunctive borders,and the SVM classification accuracy was improved．In fact,the good multiple resolution approximation accuracy of MLS-LSM has the similar process to that of the face emotion identification of human eyes．Therefore,one face emotion identification algorithm with the improved MLS-SVM by Guass kernel function was proposed in this paper,which could improve the face emotion identification accurate．At last,the numerical evaluation results show that the accurate of face emotion identification is improved with the comparison to two classification approaches.
Detection of Spliced Photographic Based on Abnormal Prediction Features
HOU Jun and CHENG Yan
Computer Science. 2014, 41 (Z6): 135-138. 
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The paper proposed an algorithm to expose spliced photographic merging two or more parts from different photos into one composite．The proposal algorithm firstly segments photo into several parts under perceptual grouping criterion,minimizing the disassociation between parts and maximizing combination within part with normalized cut algorithm,then predicts each pixel’s value according to its eight neighbors by minimal least square methods,conducts statistical features of inharmonic points．Since these features are influenced by texture characteristics,features of co-occurrence matrix,which display the image’s texture,are also calculated．Finally,all features are feeded to a support vector machine (SVM) classifier．The test experiments show that the proposal method is effective in exposing splicing image.
Edge Detection Based on Spatial Moments of Local Region
CHEN Chang-xiao,HE Ming-hao and QU Zhi-guo
Computer Science. 2014, 41 (Z6): 139-142. 
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The SUSAN edge detector is an algorithm based on the local region information which is prone to false-edge problems in noisy environment since it only utilizes the zeroth spatial moment of local region．To solve that problem,a novel edge detector,which utilizes information of higher-order spatial moments such as the first and second-order spatial moments of local region,was presented．Experiments were conducted on synthetic image and real images with different kinds of noise.The results show that M-USAN can remove false-edges and improve the performance of SUSAN edge detector effectively.
Fast Stereo Matching Based on Progressive Reliable Point Growing Matching for Speckle Pattern Images
ZHANG Yan-feng,HUANG Xiang-sheng,LI Hang and WANG Meng-wei
Computer Science. 2014, 41 (Z6): 143-146. 
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Different from the traditional region growing matching algorithm which is excessively dependent on the growing threshold,PRPGM(Progressive Reliable Points Growing Matching) sets a sequence of thresholds from high to low for both seed point selection and growing matching to implement the stereo matching in an iterative process,thus enhancing the results’ robustness on the thresholds．A research has employed this method for depth estimation for speckle projection system and achieved good results．However,it motivates us to conduct this research that the calculation is not fast enough for practical applications as well as there are still many illegal points on the disparity map．We proposed a sparse seed point selecting method that selects seed point from grid divided by certain size on the speckle pattern image in the stage of selecting seed point and a jumping growing matching method instead of the conventional connectivity constraint of 4-neighbors domain during the growth of the reliable points．Both of the above revises have been verified to improve calculation speed greatly．Meanwhile,we applied the PRPGM to handle illegal points in post-processing of stereo matching and eliminated most of illegal points consequently.
Face Recognition Based on Sampled 3D Points Clouds
ZHOU Juan
Computer Science. 2014, 41 (Z6): 147-149. 
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This paper resampled the 3D face points clouds based on its whole contour to characterize the face．Firstly,the points set of 3D face region will be adjusted into a unified attitude coordinates and then be changed into depth images.Secondly,the first and second order of gradient ratio of the depth images will be calculated,also a certain threshold will be set to extract the boundary curves of them,in succession,the corresponding points clouds in 3D space of the 2D boundary curves will be found to characterize the human face.Finally,D-ICP algorithm will be used in model registration step and also the similarity of two models will be measured．The experiments were carried out on the European face database GAVAB3D.And the results indicate that our method is handy and effective.
Fast and Efficient Algorithm for Airborne Target Recognition
PAN Ming-xing and SUN Han
Computer Science. 2014, 41 (Z6): 150-152. 
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Because the target recognition is very difficult under the complex scene and with 3D motion of airplane,a fast and efficient algorithm was proposed．First using a color-based object detection method,the coarse positions of region of interest(ROI) are achieved quickly．Then the features of ROI are extracted according to chain code tracing method．And then the decision rules for special targets are concluded based on sample video,and are used to judge whether each ROI is the true target．Finally the recognition for special targets detection is realized．Experiments also show that the new algorithm is fast,practical and suitable for real-time processing.
Split Bregman Method of Image Segmentation Based on KFCM and Improved CV Model
XIE Dong,GONG Qu and CHEN Xiao-biao
Computer Science. 2014, 41 (Z6): 153-155. 
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Aiming at the problems of the sensitivity to noise,the low computational efficiency and the segmentation result depended on heavily the initial value,we put forward an image segmentation method based on KFCM and improved CV model.Firstly,the average nuclear fuzzy clustering method was used to determine the interest area as the initial value in the algorithm.Then we improved the efficiency of iterative calculation of the CV model in calculation and time by the Split Bregman method.The experimental results show that this algorithm not only keeps the advantage of image segmentation algorithm,but also has obvious effect on the noise performance and segmentation efficiency．
Study of Hitting Effect Evaluation Technology Based on SAR Images
XU Ying,LI Hua-jun,WU Chong and ZHANG Lin-na
Computer Science. 2014, 41 (Z6): 156-159. 
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Firstly,by analyzing hitting effect evaluation scheme based on SAR images,an improved hitting effect evaluation scheme based on SAR images was given and expert exponent libraries were added to the new scheme,then according to image registration,change detection and damage assessment,hitting effect evaluation technique based on change detection was studied,finally,aiming at the problems which are not solved in studying of hitting effect evaluation based on SAR images,a summary was made．This paper has certain guiding significance.
Retinex-based Color Image Enhancement Algorithm by Improved Mean Shift Filtering
ZHOU Yang,SUN Jin and NIU Ben
Computer Science. 2014, 41 (Z6): 160-163. 
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To avoid the halo artifacts and color distortion by the traditional center/surround-based Retinex enhancement methods,this paper proposed a Retinex method based on improved Mean Shift filtering．Firstly,low contrast image is decomposed into two parts:luminance and chrominance by principal component analysis (PCA)．Improved Mean Shift filtering is introduced to get the enhancement of luminance adaptively．In addition,color image inpainting is performed independently according to Meylan method.Finally,image compensation is completed based on the global analysis．The experimental results show that the proposed method can effectively overcome the halo artifacts while maintaining color consistency when dealing with low contrast images,and speed up the process comparing with the similar adaptive methods.
Depth Estimation of Single Camera Zooming Image
GAO Hong-wei,WANG Hui-ke,LIU Chuan-yin and LI Bin
Computer Science. 2014, 41 (Z6): 164-166. 
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Some key technologies for the depth estimation of single camera zooming image were investigated in detail．Firstly,camera parameters calibration was executed combining the characteristics of zooming camera．Then,robust feature matching based on SIFT was realized by geometry constraint of zooming image．Finally,the 3D reconstruction model of zooming image was established．The experiment results based on real sample images prove the validity and practicability of the related algorithms.
Feature Field-based Evolution Method for Image Segmentation
WU Tao
Computer Science. 2014, 41 (Z6): 167-173. 
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In order to correctly select the optimal threshold for image segmentation,a novel method of high-dimensional thresholding based on data field mechanism was proposed．Combing the local grayscale and Tamura’s texture model,including coarseness,contrast and directionality,enough image information is extracted as far as possible．Taking each pixel with multi-features as a data particle with certain mass,a feature field is generated in the image feature space．Assuming the optimal threshold is latent optimal evolution direction,and feature field-based coevolution is achieved by adaptive attraction and repulsion among particles because of the interactions in dynamic data field,and the final result is determined by majority rule．The experimental results suggest that the new method obtains better performance without obviously increasing the time cost,and it is efficient and effective.
Image Recognition Algorithm for Esophageal Endoscopy
CHEN Gang,HU Zhen-peng and LU Hong-xing
Computer Science. 2014, 41 (Z6): 174-177. 
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Videoendoscope is an important tool for the diagnosis of esophageal cancer in early stage．Computer aided diagnosis could improve the efficiency．However,there is lack of effective recognition algorithms．Therefore,the paper proposed an image recognition algorithm for esophageal endoscopy (IRAFEE) based on esophageal endoscopic image texture features．Firstly,the IRAFEE algorithm divides the endoscopic image into sub-areas,extracts gray level co-occurrence matrix for each sub-area．Secondly,the IRAFEE algorithm calculates four features of gray level co-occurrence matrix:angle second moment,contrast ratio,inverse difference moment and degree of association,constructs feature vectors．Finally,the IRAFEE algorithm clusters the feature vectors for several times,filters the result clusters based on expert rules and identifies the potential lesion areas．The experiments show that the proposed IRAFE algorithm is feasible and effective.
Discriminative Sparse Representations in Face Recognition
HU Wei,ZHANG Shao-hua and GUO Xiao-li
Computer Science. 2014, 41 (Z6): 178-180. 
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In order to alleviate the influence of illumination variations on face recognition,in this paper,we proposed an effective discriminative sparse representation face recognition method．Firstly,we decomposed test image by using nonsubsampled contourlet transformation (NSCT),then used coefficients of each subbands to calculate the contribution of each subbands and fusion the subbands information according to the contribution of each classified image block．Finally,we obtained the discriminative character of the test image,applied it in the face recognition．The experiment on AR database shows that the proposed algorithm is more robust in illumination and expression variations in face recognition．
Rendering of Moving Water Reflection Based on Backward Ray Tracing and Image Based Rendering
LI Gang and LUO Yu-jun
Computer Science. 2014, 41 (Z6): 181-183. 
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A water reflection algorithm was presented based on image based rendering (IBR) and backward ray tracing．At first,backward ray tracing method was used to find the reflection point set of water surface which can be seen by eye．Then the scene image plane research was used to find out the cross point of reflected light ray and the scene objects and the cross point in the image plane was projected inversely to the view coordination system to find the color of reflected things．Finally,the point color which can be seen by eye was calculated by Fresnel equation．The algorithm can physically simulate the water reflection effect especially when there are things nearby or floating on the moving water.
Novel Change Detection Method Using Independent Component Analysis and Oriented-object Method
LI Xiao-chun,JIA Chun-yang and LI Wei-hua
Computer Science. 2014, 41 (Z6): 184-186. 
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Through analyzing problems brought on change detection methods of remote sensing images with high resolution,a novel change detection algorithm using Independent Component Analysis combined with oriented-object and undecimated discrete wavelet transform (UDWT) was proposed．First,feature images of image’s objects extracted using oriented-object method serve as data of input vector to estimate sub-space for Independent Component Analysis,which can improve effect of noise suppression,simultaneously,a new algorithm using self-adapted weight was proposed in order to extract image’s object,which optimizes processing method on oriented-object deeply.New partitioning scheme using undecimated discrete wavelet transform overcomes effectively prominent problem as follows:the size of input vector becomes shrinking which leads to unprecisely estimation of sub-space for independent component analysis using present partitioning scheme． Simulation results show that compared with typical algorithm,such as Independent Component Analysis and undecimated discrete wavelet transform, new algorithm improves robust and veracity of change detection for high-resolution images greatly by using qualitative and quantitative results.
Calibration Method Based on Linear Feature for Fisheye Image
GUO Xiong-fei,LU Bin,LI Qing and XUE Chen-yang
Computer Science. 2014, 41 (Z6): 187-190. 
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In order to calibrate the distorted image captured by fisheye cameras,this paper drawed out a effective calibration method with the chessboard．Adopting standard distortion model,it firstly gets objective function on the basis of the linear feature,then detects accurately chessboard corners with a improved SUSAN algorithm．The next step it conducts curve fitting based on the previous corners．Finally the optimal distorted coefficients can be computed with progressive optimization algorithm so that objective function is minimal．Experiment results show that this method gets accurate corners coordinates,and has a low time complexity,moreover can calibrate effectively the distorted image because of fisheye lens.
Calibration for Single Viewpoint Depth Image Based on Sparse Feature Points
GUO Qing-hui,LIANG Xiu-xia and ZHANG Rui
Computer Science. 2014, 41 (Z6): 191-195. 
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Efficient and accurate calibration is the key issue for 3D model reconstruction based on the depth image．Based on the synchronous color image and depth image obtained from the Kinect camera,a calibration method based on the sparse feature point was presented．We took the color image as a reference image,used the geometric relation between the depth image and the color image to calculate the corresponding matrix transformation parameters．Then we extracted corresponding sparse feature points of the two types of data to determine the calibration parameters,and thus obtain a mapping relationship between the two data．Finally,we achieved the calibration of depth information according to the determined parameters．The results show that the relative transformation between the depth image and the color image meets a linear approximation conversion．This method has low computational complexity,high accuracy and easy to realize．So it is suitable for further promotion in related fields.
Study on α Stable Distributions and Speckle Suppression
GUAN Tao and NIU Xiao-tai
Computer Science. 2014, 41 (Z6): 196-202. 
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stable distributions are the generalization forms of Gaussian distribution and Rayleigh distribution,capacity of accurately describing impulsive data and have widely applications in imaging and noise suppression．However,there are still lack of comprehensive introduction and comparative analysis in this aspect．Associating with current hot research points in speckle suppression and departing from MAP based filtering approaches,this paper introduces the definition,characteristic functions and properties of α stable distributions and their special forms including symmetrical α distribution,generalized Rayleigh distribution,Gauss distribution and some kinds of mixture distributions,and then analyzes some useful parameter estimation principles and methods．Subsequently,an experimental comparison was carried out and it verifies the superiority of MAP based filter．Besides,this paper introduces the newest applications in speckle suppression of these distributions．At the same time,this paper summaries the statistical characteristics of speckle and discusses some commonly used noise filtering algorithms,such as non-local mean approach．
Application of Improved Interpolation IELAD Algorithm in Image Denoising
FAN Sheng-juan,ZHANG You-hui,WANG Zhi-wei,DONG Rui and CAO Meng
Computer Science. 2014, 41 (Z6): 203-206. 
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An ideal image denoising algorithm should preserve details of image while removing the image noises．This article drew on the Edge-based Line Average algorithm (ELA) thinking which is used to venue interpolate in video signal processing and put forward an Improved Edge-based Line Average Denoising algorithm (IELAD) which is used to remove salt-and-pepper noises．In this algorithm,an extended 5+5order vertical-window is added based on the 5+5order horizontal-window．We saw the noise pixels as the interpolating pixels．Then according to the edge direction of the noise,the right window and direction were choosed adaptively for filtering．Experiments show that this method makes full use of the edge-preserving property of ELA window and can effectively remove the salt-and-pepper noises．This algorithm can maintain the edge details of the image and reduce image blur．
Robust Region-based Active Contours Model for Image Segmentation
MENG Hong-bo,WANG Chang-ming and BAO Jian-dong
Computer Science. 2014, 41 (Z6): 207-210. 
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A novel region based active contours model was proposed to deal with the images with intensity inhomogeneities and weak boundaries．For the proposed model,a new energy function was defined,which consists of a local fitting term and an auxiliary global fitting term．Then,the energy functional was incorporated into a variational level set formulation．Furthermore,we regularized the level set function by using Gaussian filtering to keep it smooth and eliminated the re-initialization．In addition,the proposed model can degrade to a new global CV model．Experiments results show that the proposed model can not only segment images with intensity inhomogeneities and weak boundaries,but also robust to the noise and initial contours．Also,it has high computational efficiency.
New Noise Digital Images Filter Based on Adaptive Neuro-fuzzy Inference System
ZHU Li-xin,YANG Kuo and QIN Jia-he
Computer Science. 2014, 41 (Z6): 211-214. 
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A new impulse noise detector based on an adaptive neuro-fuzzy inference system(ANFIS) was presented．The proposed operator is a hybrid filter obtained by appropriately combining a median filtering,a Wiener filtering and the ANFIS．The noise is exactly estimated through the proposed operator．The internal parameters of the ANFIS are adaptively optimized by training．The training is easily accomplished by using simple artificial images that can be generated in a computer．The noise image,noise estimation of median filtering and noise estimation of Wiener filter are as three inputs of adaptive neural fuzzy system．The output of the adaptive neural fuzzy system is judged whether the pixel is a noise point by means of a fixed threshold value．If it is a noise point,the median filter is used．If it is a real image point,remain unchanged．The distinctive feature of the proposed operator is that it offers well line,edge,detail and texture preservation performance while,at the same time,effectively removing noise from the input image．Simulation experiments show that the proposed operator may be used for efficient restoration of digital images corrupted by impulse noise without distorting the useful information in the image.
Novel PCNN Model and its Application on Image Segmentation
AN Qi,LI Min,HE Yu-jie and YAO Jun-ping
Computer Science. 2014, 41 (Z6): 215-217. 
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Considering the parameters of pulse coupled neural network (PCNN) are mainly adjusted manually,a novle PCNN model are proposed to reduce the parameters and simplifies its modulation parameter β and connect matrix K as linking matrix W.This paper brings forward a segmentation method based on a novel PCNN with the parameters determined by images’ spatial and grey characteristics automatically.Segmentations on images are implemented with the proposed method and the experimental result are better than that of other methods,such as Otsu method and manual adjustment method of PCNN parameters.
Cytology Images Chromatin Feature Extraction Method
XU Chuan-yun,ZHANG Yang and Wang Sen
Computer Science. 2014, 41 (Z6): 218-219. 
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This paper focused on the requirements of describing particle size and distribution uniformity of nuclear chromatin in image analysis of cervical cytology,proposed a mathematical morphology-based particle analysis method to describe particle size of nuclear chromatin.In this method,the distribution uniformity of chromatin is described using the variance of color depth of each radiation line whose starting point is the centroid of nuclei.It described two specific chromatin feature extraction algorithm.The experiments prove that the proposed chromatin described features can be more effective nuclear chromatin image characteristics.
Study on Exponential Filter of Filter Back Projection Algorithm for CT Image Reconstruction
LUO Yan-hong
Computer Science. 2014, 41 (Z6): 220-223. 
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Computed Tomography(CT) image reconstruction playing the core role in CT technique,the performance of reconstruction algorithm is of vital importance to the judgement of accuracy of monitor results．The image of the object is reconstructed from projection data by using algebraic or analytic algorithms．Analytical algorithms are deduced based on rigorous mathematic theories,and have the advantages of fast processing speed．So the analytical algorithms are used widely on CT detection equipment．In the analytic reconstruction algorithms,filter back projection algorithm is the mainstream．The main reason is the filter back projection algorithm has higher operation efficiency,and better reconstructed image quality．It is low cost,easy to realize parallel processing,so it is used in many industrial CT machine．In the process of analytical algorithms,the selection of the filter function playing a decisive role in reconstuction result and efficiency．This paper firstly introduced R-L and S-L filter function,and analyzed their natures．Secondly,it put forward exponential filter function,and analyzed the influence of exponential function in the absence of noise and noise conditions on image reconstruction by adjusting index value of parameter．Lastly, proved by experimental simulation that the exponential filter function can obtain not only better spatial resolution,but also better image properties．
Digital Fusion Image Quality Objective Assessment Method Based on Visual Information Fidelity
HUA Dong and YU Hong-sheng
Computer Science. 2014, 41 (Z6): 224-226. 
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Objective quality assessment of fusion image is of fundamental necessary in real-time digital image fusion system．A fusion image quality objective assessment method based on visual information fidelity (VIF) was proposed considering the assessment results of traditional objective assessment methods are disagree with the human subjective assessment results．Assuming that the image sources meet Gaussian scale mixture model,regarding image fusion proces-sing as image signal distortion channel,and considering human visual noise characteristics,VIF digital image fusion objective quality assessment model was established,and an image fusion quality evaluation index－FVIF was derived also．The experient indicated that the method can evaluate fusion image quality comprehensively and is better than other methods．The results of FVIF method are consistent with the human subjective assessment results.
Improvement of Compressive Sensing Based Differential Correlated Imaging
ZHANG Guo-qiang,XIE Hong-mei and XIE Yi-xin
Computer Science. 2014, 41 (Z6): 227-229. 
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Compressive sensing based differential correlated imaging can reconstruct high quality object image using less number of samples than traditional correlated imaging method,but the former method still has the problem that large computation memory space and it need long image reconstruction time．To solve the problem,this paper proposed an improved differential compressive correlated imaging scheme using the fact that the fluctuations intensity of the optical field influences the contrast quality of the reconstructed image．The scheme can be described as following:First,the measurement data was preprocessed and only the measurement data that is higher than the average value were used to construct the initial dictionary by re-ordering the selected data and extend them to be vector．Then using the training sample,we got the learned initial dictionary D0as the sensing matrix,next with the learned D0,and using K-means singular value decomposition(K_SVD) algorithm we obtained the updated dictionary D and the corresponding sparse matrix．Finally,the object image information was gotten by orthogonal matching pursuit algorithm．Real experimental data of the object “single slot” and different imaging method were used,the imaging results show that the improved scheme can reconstruct high-definition images using less sample data amount (about 300samplings) than the traditional compressive sensing based differential correlated imaging method (about thousands of samplings)．Thus the new scheme greatly improves the imaging efficiency and image quality,reduces the excessive demands of the system storage hardware,and shortens the image reconstruction time．In addition,another object’s image can be obtained by single optical path measuring provided that the parameters of optical source and distances unchanged,which can reduce the hardware complexity of correlation imaging．All this benefits will make the correlation imaging to be more practical for real applications.
Hyperspectral Image Classification Based on Semi-supervised Neighborhood Preserving Embedding
FENG Hai-liang,PAN Jing-wen and HUANG Hong
Computer Science. 2014, 41 (Z6): 230-233. 
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In order to solve the dimension reduction problem of hyperspectral image to improve the classification algorithm’s classification accuracy rate and the problem that hyperspectral image usually contains little labeled samples,we proposed a hyperspectral image algorithm based on a semi-supervised neighborhood preserving embedding algorithm and improved k-Nearest Neighborhood classifier．This algorithm uses both the labeled samples and the unlabeled samples of the neighborhood based on Neighborhood Preserving Embedding to get the neighborhood embedding structure,and improve the classification feature through raising weight of the labeled neighboring samples,and thus improving the sample accuracy rate of KNN classifier．The experimental results on the Urban and Indian Pine data sets show that the accuracy rate of the proposed method is improved by more than about 8.7%,3.6%,respectively,and thus the classification performance has been improved clearly.
Feature Extraction Algorithms and Applications Based on Complex Visual Information of Image
ZHAO Yan-ming and JI Sheng-jie
Computer Science. 2014, 41 (Z6): 234-238. 
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Feature extraction is a key position in the field of image analysis,understanding and recognition.At the present stage,the approach of feature extraction ignores its own visual information of image．Based on that,feature extraction algorithms and applications based on the complex visual information of image itself was proposed.The algorithm analyzes the complex cells function of at the area V1layer 4B of visual cortex,reveals the ability of the complexity of the visual cells,i.e.extracting image region independent,non-linear and translation invariant features,creats the mathematical model of complex visual cells,and extracts complex visual information of region image.It solves the shortcomings of ignoring the visual characteristics of the image itself and achieves good search results in the field of content-based image retrieval.
Survey of Semantics for Internet of Things
YUAN Ling-yun and WANG Xing-chao
Computer Science. 2014, 41 (Z6): 239-246. 
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Information Sensing provides the information sources for the Internet of Things(IOT),and it regarded as the basis of information collaboration in IOT．But the primitive sensing information by the sensing devices in IOT is always uncertain,magnanimous and heterogeneous,which not only brings the challenges in information transmission,storage and processing for the restrained sensor network,but also increases the difficulty in information presentation and mana-gement．Semantic technology has provided a new idea for this problem．In this paper,we have expounded that semantics is applied to IOT．Firstly,semantic requirements at different levels in IOT are analyzed．Then,the application researches of semantics for IOT are described and analyzed,including semantics-based resource description and modeling,sensor data presentation and processing,semantic annotation for sensor data,service building and providing,and sensor data storage and query for IOT．Finally,some future prospects of the challenges and research directions are given.
Reliability Research for Wireless Sensor Networks:A Survey
HU Lian-ya,LI Jian,ZHOU Hai-ying and ZUO De-cheng
Computer Science. 2014, 41 (Z6): 247-251. 
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Due to the characteristics of small volume,low power consumption,limited resources for the WSN node and the characteristics of large-scale,stochastic seeding,task environment variable for the WSN,reliability has been regarded as the fatal factors which restrict the development of the wireless sensor networks．With the analysis of the reliability constraints,this paper surveyed the wireless sensor networks reliability methods,respectively from node and networks aspects introduced main reliability methods in domestic and foreign．Through the study of the modeling methods of the WSN reliability from nodes level and networks level,this paper pointed out the standard of evaluating reliability modeling and gave the summary of reliability modeling technology．Finally,this paper pointed out some problems in reliability research from domestic and foreign and the development of WSN reliability research prospects.
Multi-hop Routing Algorithm Based on Clustering in WSN
LI Han,WU Qiu-xin and WANG Xiao-ni
Computer Science. 2014, 41 (Z6): 252-254. 
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Wireless sensor networks (WSN) pose new research challenges related to the design of algorithms,network protocols,and software that will enable the development of applications based on sensor devices．In this paper,we proposed a multi-hop routing algorithm based on clustering to reduce the energy consumption and prolong network lifetime．In order to avoid nodes with low residual energy becoming cluster heads,our algorithm selects residual energy as an energy-control factor to balance the energy consumption．Through the introduction of Cluster Head-weight,multi-hop Cluster Head routing trees with shortest path are constructed．Through the multi-hop transmission way,it reduces the number of Cluster Heads to connect directly with Base Station in communication．Simulation results show our algorithm is more efficient to reduce and balance energy consumption and hence prolong the lifetime of WSN.
UPSO (Uniform Particle Swarm Optimization):An Algorithm of Dynamic Overlay Optimization for WSN
CAO Jian-wei,CHEN Qing-kui and ZHUANG Song-lin
Computer Science. 2014, 41 (Z6): 255-257. 
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For the problem of dynamic coverage problem can be transformed into multi-objective optimization,this paper proposed an algorithm of dynamic overlay optimization for WSN base on division space uniform particle swarm optimization (UPSO)．The algorithm first defines the process of dividing regional based on sensor distributed evenly or unevenly,and then searches for the Pareto optimal solution of sub-regional by particle swarm in different region．Experiments show that in different network size and number of iterations,the regional coverage and network lifetime compared to traditional classical algorithm have better improvement.
Fast Algorithm for Overlapping Community Detection in Directed Networks
LI Li-jie,CHEN Duan-bing and WANG Guan-nan
Computer Science. 2014, 41 (Z6): 258-261. 
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With the development of the society,the scale of data and networks are increasing rapidly．As one of the effective ways of studying network structure,community detecting is a significant issue in deep understanding of large scale networks．Based on the methods of non-overlapping community detecting in directed networks and overlapping community detecting in undirected networks,an overlapping community detecting algorithm in directed networks was proposed in this paper．The basic idea of this method is to divide a network according to two parameters:directed weight and belonging degree of nodes．The influences of these parameters on partition are discussed and the optimal parameters are obtained．The performance of the proposed algorithm was tested and compared with other algorithms on two real networks and one computer-generated network．Experimental results show that the algorithm presented in this paper is rather efficient to detect overlapping communities of directed network.
Research for Access Control Model Based on UCON in Cloud Computing
CAI Ting and CHEN Chang-zhi
Computer Science. 2014, 41 (Z6): 262-264. 
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UCON(Usage Control) access control model,by introducing two concepts of “obligation” and “conditon”,integrates the three technical fields of traditional access control model－confidence mana-gement and digital copyrigh management,and extends the cover scope in control mechanism of the model,which make it more adapt to cloud computing．In consideration of the privacy protection in UCON model,an authorized management control(AM-UCON) model based on encryption pattern was proposed．Based on identification and monitoring,the model uses multiple validation to improve the creditability in the renew of attributes and the correctness in authorization,to some extend,which can deal with the problem of malicious tampering for privacy strategies．Finally,the model’s realization process was given,and was achieved in the digital object release system based on cloud computing environment.
Method for Probing Sources Selection Based on General Dispersity of Sources in Network Topology Discovery
YANG Xu,QIU Han,ZHU Jun-hu and WANG Qing-xian
Computer Science. 2014, 41 (Z6): 265-269. 
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Due to the significant effect on the discovery result,probing sources selection plays a vital role in unauthori-zed target network topology discovery．Thus,properly selecting a fixed number of probing sources would dramatically increase the coverage of discovered network．For this,a novel indicator,GDS(General Dispersity of Sources),depicting the logic distance of a set of probing sources was designed．Meanwhile,experiment shows that probing source set with a larger GDS tends to get a wider topology coverage．Subsequently,maximum GDS selection which represents screening the probing source set with maximum GDS out of the whole probing source collection was proposed．Moreover,the HGSAA (Hybrid Genetic Simulated Annealing Algorithm) often used in the field of power grid formulation was tailed-made to accurately screen out the probing source set with maximum GDS．On the basis of experiments,it is demonstrated the probing source set selected by the method based on maximum GDS selection results in more router interfaces and links compared with the ones of SDIS selection,low degree selection and random selection.
Research of Router Queue Scheduling Algorithm LW-WFQ
YANG Xiao-ping,NIU Yang and HU Yu
Computer Science. 2014, 41 (Z6): 270-272. 
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The router active Queue scheduling algorithm WFQ (Weighted Fair Queuing) can no more guarantee the QoS requirements of low-rate real-time traffic and a real-time burst will lead to increased delay and jitter problem as congestion occurs,so an algorithm named LW-WFQ(WFQ Base on Length and Weight) was proposed．The algorithm adds an adaptive queue manager and mechanisms which can deal with burst to reduce the waiting time of packets.NS2is last used as a platform to compare a great deal of performance simulation of WFQ and LW-WFQ,and then we regulated and confirmed the parameters to prove that LW-WFQ had certainly improved the performance of delay and jitter.
Localization Algorithm Based on Azimuth Angle and Network Topology
ZHENG Chun-feng and XU Yang
Computer Science. 2014, 41 (Z6): 273-275. 
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In wireless communication,interference sources have become a huge concern recently．How to search and eliminate precisely is very important so as to restore the network communication for radio monitoring department．In this paper,we took a rounded study on the interference source localization problem in radio monitoring．First introduced two existent localization algorithms,Brown Least-square Triangle Localization and Virtual Force Iterative Localization．Then presented an algorithm,the localization algorithm which is based on azimuth angle and network topology．We compared the localization accuracy with three interference source localization algorithms through simulation and experiments,and found that the localization algorithm which is based on azimuth angle and network topology has higher accuracy in the actual interference source localization.
Comparison and Analysis of Routing Protocol Based on Mobile Sink
ZHANG Hui-qi,LIN Zhi-gui,LI Min and MENG De-jun
Computer Science. 2014, 41 (Z6): 276-280. 
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Designing a routing protocol based on mobile sink is a key technique for mobile sink wireless sensor network．Firstly,this paper analysed the network structure of mobile sink wireless sensor network and evaluation indexes of mobile sink routing protocol．Secondly,the existing mobile sink routing protocols were summarized and divided into three types of protocol,including non hierarchical routing protocol,routing protocol based on virtual grid and routing protocol based on virtual cluster．Finally,in terms of the network energy consumption,the number of survival nodes and received packet by sink,the protocols were emulated．Emulation results verified the theoretical analysis of protocols,which provides help for the selection of effective mobile sink routing protocol.
Research on Channel Detection Algorithm of Intelligent Minefield Based on WSN
GUO Ying and ZHAI Yan-long
Computer Science. 2014, 41 (Z6): 281-285. 
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The fourth generation of intelligent minefield system characterized by network and intelligence is an inevitable trend in the development of modern mines．The United States and other developed countries have carried out the development work of networked intelligent minefields a decade ago and have initially put it into armed forces．In this paper,we carried on research in allusion to the channel detection problem of intelligent minefields based on the wireless sensor network,established minefields networked model,defined the concepts of internal channel and edge channel of minefields and proved that channels exist in the minefield is the necessary condition for the motor vehicle to pass minefields．Meanwhile,detecting algorithm was designed respectively for two kinds of channels and this provides both theoretical basis and technical implementation approach for channel detection of networked intelligent minefields and the subsequent minefield self-healing.
Design on Fault Localization Algorithm Based on Stochastic Network
GAO Jian-ming
Computer Science. 2014, 41 (Z6): 286-288. 
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With the increasing scale of the network,a large random distribution between routing nodes occurs.It is difficult to establish the accurate localization model,so the traditional methods based on feature matching is difficult to describe the random characteristics in fault location of nodes,resulting in inaccuracy of fault location.This paper discussed the overview and characteristics of stochastic networks,and degree distribution and characteristic spectrum of stochastic networks.Through defining the diameter and average distance for stochastic network,calculated the clustering coefficient of stochastic network,extracted effective parameters of stochastic networks fault feature,constructed a feature module of fault data.Using the fault feature node of random walk network fault detection algorithm as a random seed registration point and a node failure detection method for the initial,the methods prove the detection efficiency using the combination of random variation of fault characteristics and registration detection.Simulation results show that the improved method can improve the accuracy of fault localization.
Uneven Clustering Algorithm Based on Clustering Optimization for Wireless Sensor Networks
CHEN Tao,LUO Yong-jian,XIAO Fu-gang,SHI De-yang and ZHANG Sha
Computer Science. 2014, 41 (Z6): 289-292. 
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In consideration of the characteristic that cluster heads close to the base station consume the larger energy in wireless sensor networks using multi-hop communication model,an uneven clustering algorithm based on clustering optimization was presented in this paper．The constructed network model is divided into various non-uniform layers,and then each layer completes unequal clustering by clustering independently．During the course of cluster heads election,the proposed algorithm optimizes the cluster heads election method according to the weighting sum of the node’s residual energy and distance to layer’s middle line．After completion of clustering,cluster heads adjust their communication distance in order to build dynamic multi-hop routing among cluster heads．Simulation results show that the proposed algorithm can generate the stable number of cluster heads and reasonable topology,and also prolong the network lifetime by balancing the energy consumption of nodes effectively compared with LEACH and EEUC.
Multi-antenna Precoding Design Based on SAR Constraint
LIANG Xue-jun,WU Zhen,LI Wei and HUANG Ying
Computer Science. 2014, 41 (Z6): 293-295. 
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This paper proposed two novel precoding schemes to maximize the system sum-rate under the constraint of Specific Absorption Rate(SAR) for MIMO uplink system．These schemes not only maximize the system spectral efficiency,but also take the SAR impact on the transmit power into account．This paper brought the SAR constraint into system resource optimization early so as to reduce the burden introduced by SAR measurement and test work．Simulation results show that these schemes could fulfill the SAR under the limit,meanwhile greatly improve system perfor-mance．
Improved Dijkstra Algorithm for Two Regional-cross Network Diagram
YANG Xi-shu,LIU Huai-yu and HU Ya-hui
Computer Science. 2014, 41 (Z6): 296-299. 
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The traditional Dijkstra algorithm is the classical algorithm to calculate the single-source shortest path for a network diagram,but not suited for two regional-cross network diagrams in reality．In this paper,the new concept of regional signature was put forward,and the regional signature and access-control logic for two regional-cross network diagram were designed too.Based on these,the Dijkstra algorithm was improved．The experiment proved that the improved Dijkstra algorithm can correctly calculate the single-source shortest path for two region-cross network diagrams,its place complexity & time complexity are the same as the traditional algorithm．Through this improvement,the adaptation range of the Dijkstra algorithm was expanded.
Heuristic Method for Identifying P2P Application Based on IP Address Entropy
LIU Bin and ZHOU Li-juan
Computer Science. 2014, 41 (Z6): 300-302. 
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The rapid increase of P2P traffic worsens the congestion of network while P2P traffic identification becomes the basic technical support for network management．The heuristic method for identifying P2P application was studied．Firstly,the behaviors that are inherent to P2P host were explored．The behaviors were translated to metrics:remote hosts’ IP address entropy．An algorithm based on remote hosts’ IP address entropy characteristics was proposed．The algorithm showed low false positive in experiment.
Research on Delay in a Kind of Internet of Things Control System
ZHAO Wei-quan,YUAN Hua-qiang,LI Di and WEI Xiao-rui
Computer Science. 2014, 41 (Z6): 303-305. 
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As a kind of special networked control systems,internet of things control system is the extension and expansion of Networked Control Systems．Based on the analysis of system structure,the impact of sampling period on network load and control performance,the simulation research about delay of Internet of things control system was carried out．For there kinds of typical cases of zero delay,fixed time delay and variable delay,the impact on system performance was quantitatively analyzed．According to the delay distribution under different load conditions,the related simulations were finished．Simulation conclusions are as follows:reducing forward channel delay can improve system performance,random delay on Internet of things control system impact more seriously than the fixed delay.
Video-distortion Optimized Cooperative Wireless Network Coding
DI Hai-yang,BAI Guang-wei and SHEN Hang
Computer Science. 2014, 41 (Z6): 306-311. 
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Network coding can greatly improve the network throughput．Especially,an appropriate network codes selection strategy is great important to enhance quality in video transmission．This paper proposes an efficient network coding scheme (ENC)．On this basis,considering the characteristics of video transmission,we propose an efficiency optimized network coding scheme based on rate control (ENC-RaDio),using Lagrange multiplier method to choose those coded packets,such that we can achieve a lower distortion for video transmission．Our simulation results demonstrate that,compared with typical loss-aware network coding schemes,ENC-RaDio achieves significant performance improvement in terms of decodable frame ratio and throughput.
Multi-service QoS-based Cross-layer Scheduling Algorithm in LTE System
WU Zhe-fu,JIN Teng-fei and ZHU Jian-jun
Computer Science. 2014, 41 (Z6): 312-315. 
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Among the numerous scheduling algorithm of resource allocation,few studies of scheduling strategies are focused on the distinction of multi-service’s QoS requirements．This paper proposed a new downlink scheduling algorithm to satisfy the Quality of Service (QoS) needs of multi-users’ real-time services and non real-times services in the Long Term Evolution (LTE),．From a cross-layer perspective,the algorithm introduced a weight factor on the basis of EXP algorithm．Simulation results show that the proposed algorithm reduces the users data drop rate and improves the system throughput considerably,while ensures the users’ fairness.
Hierarchical Priority Scheduling Strategy of Job for SLA in Cloud Computing
LIN Qing-ying,LU Xi-cong and XU Lin
Computer Science. 2014, 41 (Z6): 316-317. 
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In order to meet service level agreements between the service provider and the service consumer in cloud computing,this paper proposed a framework with meta-level scheduling and local-level scheduling in the cloud environment．It uses multi-level feedback queue scheduling algorithm in each level．The scheduling algorithm with job prioritization is used to give more priority for deadline based and shortest jobs．Also,the meta-scheduler is designed to allocate and monitor resources．Finally,the experiments simulated show that our strategy can satisfy the consumer on response time of job and can meet the SLA.
Network Emulation System Based on Virtual Machines and Resource Mapping
LIU Xing-bing,MU Xiao-xia and DUAN Xin-tao
Computer Science. 2014, 41 (Z6): 318-320. 
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Performance evaluation is an important stage during the development of network protocols．Algorithms and Protocols are usually tested in experimental network or simulation environments．Simulation level of abstraction may be too high to capture low-level effects．Experimental networks are neither controllable nor repeatable．Emulation provides a third point for protocol testing and evaluation；it is expected to be a low-cost,controllable and repeatable testing platform with high degree of realism．In this paper,we make a survey on network emulation systems,including their concepts,classification,focus on design methodology of the Virtual Machines and the Resource Mapping emulation system,the developing trends and main challenges are also summarized.
Underground Target Track Prediction Algorithm Based on Markov Chain Model
MENG Fan-zhen,WU Jie,BU Xu-song and FENG Feng
Computer Science. 2014, 41 (Z6): 321-323. 
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In view of the downhole conditions,the beacon node failure will exist a large number of blind area,this paper proposes a underground target track prediction algorithm based on markov chain model,the use of the existing wireless sensor networks and wireless radio frequency identification technology,combined with markov chain model to estimate target motion track,and the traditional centroid localization algorithm is improved,and adapt it to the prediction model,at the same time reduce the positioning error,improve the positioning coverage．Experimental results show:in hundreds of meters range error is smaller,which can realize accurate positioning.
Tandem Policy Based on Signal Detection Algorithms
LU Cheng-gang
Computer Science. 2014, 41 (Z6): 324-325. 
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Through enhanced designing or adding 3rdparty module,the accuracy rate and reliability rate of signal detection can be improved．One algorithms concatenation theory for enhancing signal detection is provided within research of the quantitative relation between positive alarming rate(PAR) and false alarming ratio(FAR)．The policy can guide developers to design post-processing or pre-processing algorithm which is connected with already-known algorithms in tandem．Two usage samples on QRS complex detection in ECG digital processing and Tone Detection in FSK are discussed with application of this policy．Three highlights in this research:1) Consideration of the quantitative relation between PAR and FAR disclosing the indirect contradictory hidden in PAR and FAR(Theorem 1)；2) Putting forward one sufficient condition to solve the contradictory(Theorem 2) --the theory of enhancing signal detection；3) Two application cases being attached to verify how to apply this theory.
Performance Evaluation of Zigbee Routing Protocol in VANET Monitoring System
FAN Qing-gang,YE Xue-mei and CAI Yan-ning
Computer Science. 2014, 41 (Z6): 326-328. 
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Considering the fact requirement of wireless network among vechicles,a network model named double-deck topology structure is proposed,and is simulated by NS2.At the same time,the performance of three kinds of routing protocol,which are Cluster-Tree,AODVjr and ZBR,in the application of wireless network among vechicles is studied.The simulation experiment demonstrates that ZBR routing protocol can decrease control overheard while keeping higher packet delivery rate and shorter time delay.
Application of Modern Optimization Techniques in Wireless Sensor Networks
HE Shou-qian
Computer Science. 2014, 41 (Z6): 329-333. 
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The wireless sensor network is a wireless self-organizing network which is composed by a large number of cheap and tiny sensor nodes,for real-time monitoring of the environment．Due to the limitation of wireless sensor networks,such as the scale,the characteristics of the nodes of the computing and storage resource-constrained network topology dynamic uncertainty,the design of high-performance wireless sensor networks often involves difficulties in traditional techniques modeling and solving complex optimization problems．A modern optimization technique is an emerging powerful tool solving complex optimization problems in wireless sensor networks．It is a heuristic optimization algorithm containing strong global search capability. The main study area of the author is the application of modern optimization techniques in wireless sensor networks,which is the positioning of sensor nodes,the optimization of deployment of network nodes,the optimization of network coverage,network routing optimization and data integration．Base on the analysis of modern optimization techniques,the author concludes the advantages and disadvantages of solution of modern optimization techniques about complex optimization problems in wireless sensor networks,and also foresees the development trend of its future prospects.
Brief Overview of Translation Validation Method in Trusted Compiler Construction
LIU Yang,YANG Fei,SHI Gang,YAN Xin,WANG Sheng-yuan and DONG Yuan
Computer Science. 2014, 41 (Z6): 334-338. 
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There is a growing awareness of the security and reliability of compilers in recent years．Especially in the safety-critical systems,the miscompilation can make a huge damage．The conventional approach to weeding out miscompilation is heavy test,but test is impossible to achieve full cover and can not guarantee that compiler is safe and trustworthy．In recent years,formal verification method has been successfully used to construct the trusted compiler．One approach is to perform formal verification for compiler itself．It can put an end to miscompilation by strict proof．However,this approach tends to “freeze” the compiler design,and discourages any future improvements and revisions．Translation validation is another formal method that can be used to construct trusted compiler,which avoids the verification for the compiler itself,and has good reusability．It has been widely researched in the compiler verification field,and has already obtained remarkable achievements．The concept and research progress of translation validation are discussed in this paper.
Improved Bayesian Text Classification Algorithm in Cloud Computing Environment
ZHANG Lin and SHAO Tian-hao
Computer Science. 2014, 41 (Z6): 339-342. 
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Used the idea of cloud computing,according to MapReduce model to solve the traditional Bayesian classification algorithm suited to large-scale data deficiencies,greatly improved the speed of classification．And the combination of the characteristics of the parallel algorithm was improved accordingly.Adding synonyms and word frequency filtering combined approach allows vector dimensionality reduction,reducing false positives．Wherein the particular keyword was then weighted to enhance the accuracy of classification．Finally,the Hadoop cloud computing platform was experimentally proved that the traditional text classification algorithm after parallelization on Hadoop cloud computing platforms,has better speedup,and the improved algorithm can improve the classification accuracy.
Utilization Pattern Based Android Root Vulnerability Analysis
YANG Chao,LIU Wen-qing,ZHANG Wei and CHEN Yun-fang
Computer Science. 2014, 41 (Z6): 343-346. 
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Malware on android platform can bypass the conventional android security mechanisms through the privilege escalation process．Due to the android fragmentation phenomenon,the emergence of root vulnerabilities in utilization patterns and scopes strongly urges the researchers’ exhaustive understanding of these mechanisms to implement corresponding security policy．The categorization of android root vulnerabilities was proposed based on their utilization patterns of whether they can be directly utilized on the mobile terminal．And then a detailed description of the existing vulnerabilities in the implementation particulars,exploit patterns,as well as coverage was presented to help to further develop the vulnerability detection program.
Space Polymorphic Technique Based on Redundance of PE File
GU Ding-feng and MA Heng-tai
Computer Science. 2014, 41 (Z6): 347-351. 
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Many computer viruses use polymorphic and metamorphic techniques to mutate their code on each replication as they propagate,thus protecting themselves from antiviruses．However,there are still some disadvantages existing in traditional polymorphic and metamorphic techniques．These techniques are too difficult to implement．What`s more,it could lead to size expansion,when viruses spreading among computers．In response to these shortcomings,by analyzing the PE file frame structure,according to the characteristics that redundancy existing in the PE file,space polymorphic technique is proposed．Then,the principle of space polymorphic technique is introduced in detail,as well as the design implementation of space polymorphic engine．At last,robustness of space polymorphic technique is analysed for further research.
Impossible Differential Cryptanalysis of CLEFIA
YIN Guang-li and WEI Hong-ru
Computer Science. 2014, 41 (Z6): 352-356. 
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To analyze impossible differential cryptanalysis on the block cipher CLEFIA,the results are presented based on two 9-round impossible differential role．It uses the output and input differences of S-boxes to recover round keys,which apply one impossible differential attack to 11-round reduced CLEFIA．Improved result on 14round CLEFFIA-256is given with the number of chosen plaintexts being reduced to 2104.23and the time complexity reduced to 2221.5．At the same time,exploiting the key relations,using Early -Abort technique and S-boxes differential technique,impossible differential attack is proposed on 12and 13-round CLEFIA-128based on two impossible differential roles respectively．
Decision for Autonomous System Maliciousness Based on Quantitative Trust Measurement
WANG Yu,WANG Zhen-xing,ZHANG Lian-cheng,GUO Yi and KONG Ya-zhou
Computer Science. 2014, 41 (Z6): 357-360. 
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Decision for Autonomous System maliciousness has not been effectively resolved within the current inter-domain routing system．On the basis of the research on trust relationship via the human society networks,a model of decision for the Autonomous System maliciousness based on the quantitative trust measurement is proposed．Three criteria including direct decision,collaborative decision and degree of coordination are defined,on which the comprehensive analysis and quantization towards the interactive routing behaviors of target Autonomous System,and the degree of participation is also defined as the amplifying factor．Experiments based on simulation topology is launched and the result indicates that,under the typical circumstances of routes spoofing,services restriction and intended incorrect decision by collaborative Autonomous System,the model can effectively discriminate and make reasonable decisions to the target malicious behavior,with good accuracy and stability.
Improvement of Extended Multivariate Public Key Cryptosystem
LUO Wen-jun and GONG Shou-peng
Computer Science. 2014, 41 (Z6): 361-362. 
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Extended Multivariable Public Key Cryptosystem (EMC) is a new kind of public key cryptosystem．It introduces a transformation and increases some redundant variables to enhance security of original scheme．However,Xunyun Nie and his partners declare that there are some security vulnerabilities in EMC,and crack the diagonal matrix D in Tame.We changed the structure of matrix D and sequence of redundant variables．What’s more,we also proved that there are no security vulnerabilities in EMC after the changing．The level of security of EMC is higher.
Research on Cloud Security Model Based on Trusted Third Party on Multi-tenant Environment
WANG Pei-xue and ZHOU Hua-qiang
Computer Science. 2014, 41 (Z6): 363-365. 
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Aiming at multi-tenant environments for cloud computing,introducing the trusted third party is into cloud security solutions,this paper proposed a new cloud security model based on trusted third party．Then we designed the authentication protocol and a multi-tenant resource allocation algorithm based on TTP．Finally,the CloudSim simulation tools were used for simulation and performance analysis,and Short Jobs First strategy,First-come First-served policy were compared with TTP strategy in successful implementation rate of resources．The experimental results show that the model provides the highest credibility cloud node resources to cloud users,builds a trust web between entities effectively,verifies the correctness of the data and the correctness of the data exchange,and provides a multi-level,end-to-end security services in the distributed environment.
Digital Signature Scheme Based on Elliptic Curve and Factoring
ZHOU Ke-yuan
Computer Science. 2014, 41 (Z6): 366-368. 
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The digital signature algorithm proposed by SHEN Qun et al．gives analytical attack,which is based on elliptic curve and factoring problems．If the difficulties of elliptic curve or factoring can be solved,SHEN Qun digital signature schemes can be attacked．A new digital signature algorithm was proposed,which is based on elliptic curve and factoring problems．The correctness,security and unforgeability were proved．Another,a new digital signature algorithm with message recovery was proposed,which is based on elliptic curve and factoring problems．The correctness,security and unforgeability were proved.
Nodes Key Agreement Scheme between Clusters in Aeronautical Mobile Ad hoc Network
SUN Ling,TIAN Yuan and HUANG Hou-biao
Computer Science. 2014, 41 (Z6): 369-373. 
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According to the characteristics of the resource constraints and high dynamic of the aeronautical mobile ad hoc network,we proposed a certificateless key agreement scheme applicable to nodes between clusters.The signature scheme was proved to be secure in the random oracle model and the session key was proved to be secure as long as each node still has at least one security secret value.Our scheme avoids pairing computation,exponentiation computation and inverse computation.The computational cost is the lowest in our scheme compared with all the other existing certificateless key agreement schemes.
Fast Scalar Multiplication with Resistance Against SPA Attacks
LI Zhong
Computer Science. 2014, 41 (Z6): 374-376. 
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Scalar multiplication is considered as one of the fundamental and time-consuming operation in elliptic curve cryptosystem(ECC).The performance and security of ECC deeply depend on the efficiency and security of scalar multiplication.A new scalar multiplication algorithm with resistance against simple power analysis(SPA) attacks based on non-adjacent form(NAF) representation was designed.The algorithm processing more than one bit of NAF(k) in each iteration,eliminated the energy consumption difference of each iteration,achieved the goal of resistance against SPA attacks.The analysis results show that the efficiency of the algorithm has a substantial improvement compared with the previous research．At the same time,the algorithm does not depend on any cipher coprocessor,has good versatility.
Method of Compressed Discernibility Matrix of the Attribute Reduction Algorithm Based on Incompletion Decision Table
WANG Ting,XU Zhang-yan,CHEN Yu-wen and YUE Ming
Computer Science. 2014, 41 (Z6): 377-382. 
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Discernibility matrix and binary discernibility matrix method is easy to understand and design,hich has aroused great concern by many scholar.But the two methods produce a large number of repeated and useless elements (if A is the subset of B,B is the useless element of A) on the fly.These repeated and useless elements occupy a lot of space and will affect the efficiency of the algorithm.Attribute reduction based on discernibility matrix methods exist the high cost of storage problem in previous literatures.This paper propose a attribute reduction algorithm based on compressed storage in the thought of combining the binary discernibility matrix with the binary tree (B_Tree) .The algorithm store the binary discernibility matrix attribute sets in the binary tree (B_Tree).The algorithm effectively reduce the time and space efficiency by storage while pruning(pruning is a thought,which delete those repeated and useless attribute sets from binary tree on the same path).Finally the analysis of example proves the feasibility and effectiveness of the new algorithm.
RFID Uncertain Data Cleaning Algorithm Based on Dynamic Tags
WANG Wan-liang,GU Xi-ren and ZHAO Yan-wei
Computer Science. 2014, 41 (Z6): 383-386. 
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SMURF(Statistical sMoothing for Unreliable RFid data) algorithm based on adaptive sliding-window needs to set a threshold manually.The value of has no effect on the smoothing results to the static RFID tags,but it will cause errors when the tags are dynamic.To solve the shortcomings above,the paper proposed DSUMRF(Dynamic tags-based SMURF) algorithm based on dynamic tags.Above all,SMURF algorithm takes major considerations of lost reading and misreading,it is not related to the processing of redundant RFID data.This paper proposed a framework of redundant data cleaning based on DSMURF algorithm.The results of the experiments show that DSMURF performs better than SMURF to the dynamic tags.
Study on Similarity Learning with Weighted Sampling
LIU Xin-yue and LIU Guang-zhong
Computer Science. 2014, 41 (Z6): 387-390. 
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A lot of classification algorithms get the similarity between samples according to their distance．Therefore,for this kind of algorithms,the way for getting distance is very important．Studies in existing metric or similarity learning algorithms find that most of the existing methods take use of random samples from training database for learning．This sampling method gives an equal probability for every training samples to be used for metric learning．However,the different location results in different classification difficulty of samples．If those samples who are difficult classified could be used more frequently in learning,while other samples arranged less learning time,the efficiency of learning will be improved．Reducing learning time is significant in Big-Data era.
Data Flow Forecasting Based on Hybrid EHMM Models
DING Yong,ZHU Hui-sheng and CAO Hong-gen
Computer Science. 2014, 41 (Z6): 391-393. 
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Firstly,presented an improved algorithm NONEPI++ for mining non-overlapped frequent episodes on the event sequences.Then created a separate HMM called EHMM for each frequent episode,and computed the mixing coefficient of mix EHMM models by using expectation-maximization procedure.Finally,forecast the data stream by training history data and predict target event．Experiments show that the mixed EHMM models can effectively predict the data stream.
Recommendation Algorithm with User Temporal Preference Fusion
LI Gui,CHEN Sheng-hong,LI Zheng-yu,HAN Zi-yang and SUN Ping
Computer Science. 2014, 41 (Z6): 394-399. 
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Accurately capturing user preferences over time can improve the precision in recommender systems．Simple correlation over time is typically not meaningful,since users change their preferences due to different external events．User behavior can often be determined by individual’s long-term and short-term preferences．In order to capture it,we propose the Session-based Temporal Graph(STG)．Based on the STG model framework,we propose the Path Fusion Algorithm(PFA) to make accurate top-N recommendation.And we evaluate the effectiveness of our method using two real datasets,CiteULike and Delicious．Experimental results show that the proposed algorithm has higher accuracy than most of previous algorithms.
Important User Node Screening and Public Opinion Guiding for Microblogging Social Network
XIE Tian-bao,ZHANG Xiao-wen and WU Kai-bo
Computer Science. 2014, 41 (Z6): 400-405. 
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Firstly,studied the theory of web crawler and open platform Sina microblogging,designed Sina microblogging special reptile,access to research data．Secondly,got indicators of important user nodes through experiments,proposed Bayesian-PageRank algorithm screening important user nodes,and verified through experiment．Finally achieved internet public opinion through the monitoring of important user node,and gave the relevant public opinion guidance strategy.
Novel Anti-noise K-means Algorithm Based on Spatial Distance Difference
MA Shi-yu,LI Yi-cai and LAN Zhang-li
Computer Science. 2014, 41 (Z6): 406-408. 
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Due to the inherent initial clustering center sensitivity of K-means algorithm,it exists problems including result instability and being easy to fall into local optimum．The current improvement schemes can reduce the number of iteration and obtain an approximate global optimal solution when deal with noise-free data sets．But for noisy data sets,it would be easy to fall into local optimum,and the clustering result is lower than traditional K-means algorithm．Based on the algorithm that can find initial clustering centers according to the farthest spatial distance,the paper proposed a novel algorithm to select initial centers based on spatial distance difference．The main idea of the algorithm is calculating the sum distances between non-clustering center and all selected centers,then sort them．Choose the point which is the closer to the given centers as the new selected cluster center．Experimental results show that under the quite condition of iteration,when deal with noise-free data sets,the clustering accuracy of the proposed algorithm is improved about 1%．For noisy data sets,the classified accuracy is above 90%.
Timeout Prediction of the Schedule Method for Big Data of the Intelligence Analysis Based on Hadoop
JIANG Su-rong,LAN Jiang-qiao and YANG Yu-hai
Computer Science. 2014, 41 (Z6): 409-413. 
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big data” is a hot research field of information science and technology．Military intelligence data has typical "big data" features．Hadoop is a software framework based on Java for distributed density data processing and analysis．In order to make the intelligence information and data access meet the real-time requirements,improved the scheduling algorithm under the framework of Hadoop．Through a simple classification way,we realized the real-time intelligence data access request scheduling in a laboratory environment.
Research of Spatio-temporal Interpolation Algorithm Based on Time Series
LI Yan and WANG Li-na
Computer Science. 2014, 41 (Z6): 414-416. 
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In order to enhance the degree of the precision of weather forecast,the research carry on the spatial interpolation algorithm．Joined the time series in the spatio-temporal interpolation,it was more accordance with the spatial and temporal characteristics of meteorological elements,and solved the lack of real-time data caused by a variety of force majeure from the source(such as instrument meteorological site failure,transmission line failure,etc.)．Based on the observation data of over 900weather stations in Chongqing of nearly a year,it conducted a comparative study of interpolation methods,and confirmed the feasibility of the algorithm.
Medical Data Similarity Algorithm Analysis Based on Relative-IDF
XIANG Lin-hong,ZHANG Ju,SUN Qi-long and ZHAO Xue-ling
Computer Science. 2014, 41 (Z6): 417-420. 
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Medical data similarity calculation plays an important role in drug information treatment．Traditional text similarity measurement in the field of medicine and can’t get good results．Particularity for the pharmaceutical data text proposed based on Relative-IDF similarity calculation algorithm of medical data．Experimental results show that compared to traditional TF-IDF,edit distance calculation method,based on Relative-IDF medical data similarity measurement in efficiency and accuracy has been greatly improved.
Log Mining Method of Enterprise Information System by Combining Rough Set and Quotient Space
ZHOU Dan-chen
Computer Science. 2014, 41 (Z6): 421-424. 
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To realize the deep mining of diversification in information requirements among different user groups of enterprise information system,a log mining method by combining the theory of rough set and quotient space was put forward through comparison and analysis of the macrocosmic and microcosmic theoretical models of granular computing．Firstly,the users’ characteristic attributes table was established in terms of their use frequencies for different function modules of enterprise information system in a certain period and their working roles．Secondly,the decision tables in two user granular spaces were built by hierarchical division of user groups based on projection division method of quotient space theory．Furthermore,the corresponding user identification rules in two user granular spaces were respectively derived by means of applying knowledge acquisition method of rough set theory．Finally,the consistency and discrepancy of information requirements among different user groups was comprehensively analyzed from different angles．The application case shows the feasibility and effectiveness of the proposed method.
Algorithm of Mining Spatial Co-location Patterns Based on Weighted Euclidean Distance
ZHOU Jian-yun,WANG Li-zhen and YANG Zeng-fang
Computer Science. 2014, 41 (Z6): 425-428. 
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The spatial Co-location pattern mining concerns about occurrence relationship of spatial objects’ instances at the same time in a certain area．Most of the papers studied based on the spatial objects’ instances have the same weight,but in reality it is easy to find that the different instances of the same type of object probably has different size,different importance,or different influence．In this paper,we consider the influence factors of the spatial objects’ instances.A concept of the weighted Euclidean distance was introduced and corresponding mining algorithm was designed,in order to find more valuable spatial co-location rules．
Design of the RBAC-based Access Control Model in the Complex Information Systems
QIANG Zhen-ping,HE Li-bo,CHEN xu and LI Tong
Computer Science. 2014, 41 (Z6): 429-432. 
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To the complexity control problems in a complex information systems which was usually caused by the mana-gement of large numbers roles and the dynamically changing of the user’s responsibilities attributes,in this paper,we based on the full consideration of the relationship between the user’s authorization and the form of the use’s organization,used the organization and group as the main body to assigned the roles,and increasing the resource access permissions scope defined in information system,we proposed an improved RBAC model and designed the realized data relationships．Practical results show that not only can be easily complete the authorization which caused by the responsibilities changing of the organization and groups,and can quickly respond to the change of the property caused by the personnel duty,at the same time can flexibly achieve the resource access permissions.
Research and Implementation of U2TP to TTCN-3Automatic Transformation
HOU Xiao yuan,WANG Xian rong,LI Hua and SHEN Wei wei
Computer Science. 2014, 41 (Z6): 433-437. 
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Integrating test information by using U2TP in system modeling stage,on the one hand,enables system deve-lopers to obtain the overall concept of testing in early system modeling stage,on the other hand,can limit the number of test cases from the initial stage．TTCN-3has a perfect,mature test platform,therefore,so we make TTCN-3as the transformation target test language of U2TP．An automatic transformation system that transformed U2TP test model into TTCN-3ATS can reduce the amount of code in the test development at a certain degree．The core part describes the design and realization work of U2TP to TTCN-3automatic transformation．The end of this paper validates the transformation system through a concrete example of U2TP,and makes concrete analysis of the generated TTCN-3ATS.
Detecting the Memory Leak in Java Program by Bi-deduction
ZHANG Guang-mei and LI Jing-xia
Computer Science. 2014, 41 (Z6): 438-441. 
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Lots of dynamitic memories are used in Java program．The unreachable dynamitic memories can be collected by the garbage collector．The reachable but inactive dynamitic memories are free which may lead to memory leak．The bi-deduction method to detect memory leak in Java program is provided．It is based on separation logic．By using separation logic and the rules of Hoare logic,the dynamitic memory’s state can be achieved and the leaked memory can be detected.
Method of Extracting Function Call Relationship in Static Code Analysis of C Language
JIANG Meng-tao and JING Qi
Computer Science. 2014, 41 (Z6): 442-444. 
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Program Static Analysis is a method,of verificating whether code could meet the specification,safety,reliabili-ty,maintainability and other indicators with scanning the program code through lexical analysis,syntax analysis and control flow analysis techno-logy,and without running the code actually．This paper presents the characteristics,technologies,implementations of static code analysis,and then explain the methods of parsing function calls in C language static code analysis.
Method of Parsing Dependencies between the Linux Kernel Compiling Options,Source Files and Functions
JIANG Meng-tao,PAN Peng-fei,SONG Yang and JING Qi
Computer Science. 2014, 41 (Z6): 445-450. 
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Compilation options in Linux Kernel provide the possibilities of functionality customization in operation system,but in traditional method of static code analysis,it is hard to know how a compilation option could affect the source code of Linux kernel．Based on the Linux kernel source,this paper presents a way of analyzing the relationship between compilation options,files and function calls from the top level,and gives the hierarchical model associated with the source code and compile options.
Materialized Views Incremental Algorithm Based on Quicksort and Huffman Tree
ZHANG Yin-ling,WU Tong and DENG Shao-xun
Computer Science. 2014, 41 (Z6): 451-454. 
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Materialized view is an effective way to improve query response,its essential question is how to maintain the data synchronization with the base table．There are many algorithms maintaining materialized view incrementally and each have different time response,so there also appeared a lot of algorithms to improve the efficiency of maintaining materialized views incrementally．This paper proposed a materialized views incremental algorithm based on quicksort and huffman tree,and proved this algorithm can improve the efficiency of maintaining materialized views incrementally.
Semantic Research on Relational Database
LUO Jun and WANG Qiu-ju
Computer Science. 2014, 41 (Z6): 455-458. 
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Database is a structured collection of data．It is a necessary component of all kinds of application．So far,the RDBMS is the most widely used DBMS．The data structure of relational database is simple,storing and accessing data is very efficient．But at the same time it is lack of semantic．And there are restrictions on the application of Knowledge System．Therefore this article introduces the concept of ontology,and implants ontology in relational database．Thus add semantic information and reasoning mechanism for it in order to make RDBMS to be semantic and can apply to Know-ledge System．
Research and Implementation of Dynamic Data-driven Traffic Simulation Framework
LUO Yong-qi,YAN Xue-feng,FENG Xiang-wen and ZHOU Yong
Computer Science. 2014, 41 (Z6): 459-462. 
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The existing pre-established theoretical models in traffic simulation are hardly able to accurately predict the trend of traffic state development,a traffic simulation framework based on dynamic data-driven application system (DDDAS) paradigm is put forward．Firstly,a state space model is proposed to conduct a priori state estimate on the basis of microscopic simulation model；then real-time data is dynamically incorporated in the process of simulation to adjust and evaluate the state space model；what’s more,given the nonlinear and non-Gaussian characteristic of the application field,particle filter is chosen as the means of implementation of data assimilation models and related algorithms by refining the key step and improving related procedures to make enhancement of the ability of state estimation．Finally,micro-simulation system named Movsim is taken to realize the framework．Experimental results indicate our proposed framework poses a high accuracy of prediction and is less vulnerable to the impact of measurement error and environmental noise,thus,it provides stronger stability and reliability．
Design and Implementation of Radio Data Sharing Platform Based on SOA
SHEN Li,HE Jing,LI Ying-hong,FAN Bo-wen and HE Li-bo
Computer Science. 2014, 41 (Z6): 463-465. 
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At present,the radio management information fundamental platform facing data sharing between heteroge-neous systems．This paper deeply analyses the shortage of radio information management basic supportive platform,proposes that establishing the radio data sharing platform is very necessary．By introducing SOA and OSB to the design and implement of the framework of the radio data sharing platform,this paper puts forward a kind of radio data sharing platform framework based on SOA．Then designs and implements the radio data sharing platform based on the framework,this platform realizes the sharing functions between different structure systems safely and efficiently.
Research on Service Contingency Guarantee in CDN-P2P Hybrid Architecture Based Live Streaming
WANG Qun and DAI Xiu-yue
Computer Science. 2014, 41 (Z6): 466-471. 
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Live streaming provides abundant television programs for end users,and has become one of the applications which promptly develop．However,common issues,including long startup delay and unsmooth play,severely restrict the improvement of quality of service in live streaming systems．From the allocation and scheduling of resource,the principle of resource scheduling for live streaming systems is presented,and service contingency guarantee scheme for server resource is proposed,which promote the utilization of network resource and the quality of experience．The experimental results shows service contingency guarantee scheme can significantly shorten the startup delay for live streaming systems and reduce the packet loss.
Cooperative Design System Based on Web Service and Agent Technologies
WANG Kai,LIU Yi,WANG Yao and OU Zheng-liang
Computer Science. 2014, 41 (Z6): 472-473. 
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To shorten the design period of airplane,improve the design quality and reduce the manufacture cost,the computer supported cooperative design has become one of the effective methods．In order to realize the airplane cooperative design in multi-discipline integrated research processes,cooperative design system architecture based on double buses is presented．In which the web service bus was adopted to integrate the software platforms with different frameworks and the agent bus was adopted to integrate the software platforms with the same framework．On the base of the cooperative design system architecture,an aircraft cooperative design system is established by integrating the workflow system and CAD system．
Research of Information Security Assessment for ATC Automation Systems
LAI Xin and HUANG Bang-ju
Computer Science. 2014, 41 (Z6): 474-476. 
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According to relevant national information security standards and basic evaluation requirements,combined with the characteristics of ATC automation system,the main factors affecting the ATC automation system information security are analyzed and the information security evaluation system is proposed．Then based on expert evaluation me-thods and evidence fusion theory quantifiable assessment method is proposed which is easy to be implemented,and the subjectivity of expert opinions will be removed because of evidence fusion algorithm．Finally,according to an example the proposed evaluation method and fuzzy evaluation method were compared.
Research of Offload Parallel Method Based on MIC Platform
SHEN Bo,ZHANG Guang-yong,WU Shao-hua,LU Xiao-wei and ZHANG Qing
Computer Science. 2014, 41 (Z6): 477-480. 
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With the development of parallel computing,co-processor specializing in parallel computing appeared．Relevant knowledge about application model and offload programming method in the platform of MIC will be introduced,at the same time,different characteristics and environment according to different application model will be discussed．Above all,development strategy based on offload programming method is proposed,which can implement the transplanting and accelerating of MIC parallel program rapidly and effectively.
Research on BP Neural Network Mathematical Model Used for Analyzing Local University Tuition
DONG Ya-nan
Computer Science. 2014, 41 (Z6): 481-483. 
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One mathematical way was introduced in this article to study and analyze the factors that affect the local university tuition．It was brought forth that principal component analysis (PCA) and BP neural network were confirmed to create a mathematical model to analysis the 7data of 31provinces or province-level municipality．The results of PCA indicated that the first 3principal components accumulated contribution rates to 87.39% which showed that the first 3principal can express all the information．It used the first 5data as the input data of BP neural network in order to improve accuracy further,and the provincial tuition as BP network output．After six training sessions,the output error can be reduced to 10－15which basically achieved the full effect of fitting,and also provided a mathematical way to predict further university tuition.
Design and Implementation of ZigBee-WiFi Gateway for Facility Agriculture
ZHONG Wei-bo,LI Zhong-mei,SHI Jie and CHEN Zhong-ming
Computer Science. 2014, 41 (Z6): 484-486. 
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In order to meet the requirements ofdata acquisition,wireless transmission and remote application in facility agricultur,a ZigBee-WiFi wireless gateway based on STM32W108and AX22001was designed to extend the perception and monitoring scope of agricultural facilities and equipment．Channel selection and software channel multiplexing approach are used to reducing interference between ZigBee and WiFi signals based on their spectrum characteristics in this wireless gateway．The experimental results show that this wireless gateway has stable signal,lower data packet loss rate and can interconnect ZigBee and WiFi networks to satisfy the needs of data acquisition and remote application in facilityagriculture.
Automatic Detection System of Fabric Defects Based on Machine Vision
SHAO Xin-yu and HUA Ji-zhao
Computer Science. 2014, 41 (Z6): 487-489. 
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Fabric defect detection plays an important role in automatic visual inspection system detects．For the purpose of detect and localize texture defects．Inspection of fabric products has been done manually by trained staff at present．However,there are still some problems,such as low detection rate,high rate of error checking and high missed rate．In this passage,we put forward the fabric defect defects automatic detection system is a kind of unsupervised defect detection system．Mainly through the gray value of each of the non-overlapping areas of the image,set dynamic threshold segmentation,and using Blob defect feature extraction method．Experimental results show that the method has a good effect on the nonwoven fabric defect detection.
Multi-application Smart Card Platform and Operating System
WU Jun
Computer Science. 2014, 41 (Z6): 490-493. 
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Smart cards provide secure access to private personal information and many other services including cryptographic services and access controls．With the development of microelectronic technology,multi-application smart cards come into being and become the new tendency in the field．In this paper,currently five most popular multi-application smart card platforms and operating systems,which are Java Card,GlobalPlatform,MULTOS,Smartcard.NET and BasicCard,are introduced,and their architecture and security technology are underlined.
Research on Configuration Management Method of Data Center Based on Ontology
LONG Yu-jiang and ZHU Zhou
Computer Science. 2014, 41 (Z6): 494-498. 
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According to the problems that it is difficult to manage and use effectively configuration information at Guizhou Power Grid data center,the ontology technology to realize semantic description of configuration information is introduced,and a quadruple model of configuration management ontology is presented,and configuration items,data properties,as well as object properties and individuals which were to build configuration management ontology were obtained based on existing configuration management database,configuration files and so on．The ontology’s logical structure and OWL description form also were presented．Finally,an application research on configuration management ontology for monitoring system of Guizhou Power Grid data center was presented.
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