Showing papers in "Journal of Computer Applications in 2011"

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

Abstract: The number of users is huge in cloud computing,and the number of tasks and the amount of data are also huge.How to schedule tasks efficiently is an important issue to be resolved in cloud computing environment.A Double-Fitness Genetic Algorithm(DFGA) was brought up for the programming framework of cloud computing.Through this algorithm,the better task scheduling not only shortens total-task-completion time and also has shorter average-completion time.There is a contrast between DFGA and Adaptive Genetic Algorithm(AGA) through simulation experiment,and the result is:the DFGA is better,it is an efficient task scheduling algorithm in cloud computing environment.

Sub-pixel edge detection algorithm based on Gauss fitting

Abstract: Concerning the low accuracy in localization and sensitivity to noise in traditional edge detection algorithms,a sub-pixel edge detection algorithm based on function curve fitting,Gauss fitting of gradient direction sub-pixel edge detection algorithm was proposedThis method firstly chosed a series of points near the edge,then got the grey level of these points,and then tried to get the gradient level of these pointsThen Gauss curves were used to fit the gradient levels of these pointsFinally the axis of the Gauss curves was got by fitting,and the position of axis would be the sub-pixel edge positionThe experimental results show that this algorithm can localize the sub-pixel edge position accuratelyThe comparision with other two algorithms shows that the running time of this algorithm is shorter,and the efficiency is relatively higher

Improved K-means algorithm and its implementation based on density

Abstract: The initial clustering center of the traditional K-means algorithm was generated randomly from the data set,and the clustering result was unstable.An improved K-means algorithm based on density algorithm optimizing initial clustering center was proposed,which selected the furthest mutual distance k points in high-density region as the initial centers.The experimental results demonstrate that the improved K-means algorithm can eliminate the dependence on the initial cluster center,and the clustering result has been greatly improved.

Path planning of unmanned aerial vehicle

Abstract: Path planning is designed to make use of terrain and enemy and other information to plan out the largest survival probability penetration trajectory of Unmanned Aerial Vehicle(UAV).After analyzing the simulation needs of path planning,the path planning of UAV was studied.Firstly,a Voronoi diagram was constructed based on the battle field environment full of threats.The Voronoi diagram yields the optimal routes to travel among a set of threat source points to avoid the threats.Then,Dijkstra algorithm was used to search the optimal route.Finally,the simulation system of path planning was carried out on the platform of Visual Studio.Net 2010 based on MS SQL Server 2008 database and Visual C # 2008 language,and the simulation result was given in graph form,which provided a good basis for further study.

Survey on Chinese text sentiment analysis

Abstract: The sentiment analysis has aroused the interest of many researchers in recent years,since the subjective texts are useful for many applications.Sentiment analysis is to mine and analyze the subjective text,aiming to acquire valuable knowledge and information.This paper surveyed the status of the art of Chinese sentiment analysis.Firstly,the technique was introduced in detail,according to different granularity levels,namely word,sentence,and document;and the research of product review and news review were presented respectively.Then evaluation and corpus for Chinese text sentiment analysis were introduced.The difficulty and trend of Chinese text sentiment analysis were concluded finally.This paper focuses on the major methods and key technologies in this field,making detailed analysis and comparison.

Coverage optimization of wireless sensor networks based on chaos particle swarm algorithm

Abstract: To improve the unreasonable distribution of sensors' random deployment,increase network coverage rate,taking the network coverage rate as the optimized goal,an optimization method of wireless sensor networks coverage based on Chaos Particle Swarm Optimization(CPSO) was proposed in this paperBased on the ergodicity,stochastic property of chaos,the algorithm can avoid the shortage of being easily trapped in a local extremum at the later evolution stageThe simulation results indicate that the addressed algorithm is superior to particle swarm optimization in coverage optimization

Self-adaptive step glowworm swarm optimization algorithm

Abstract: According to the problem that Glowworm Swarm Optimization(GSO) cannot acquire solutions exactly and converge slowly in the later period for solving the multimodal function,an improved GSO algorithm combined with luciferin-factor,which can adaptively adjust step,was proposed.The simulation results show that the improved Self-Adaptive Step Glowworm Swarm Optimization(ASGSO) can search for global optimization more quickly and precisely.

Improved word similarity algorithm based on HowNet

Abstract: The word similarity computation is widely used in text classification,question-answer system,machine-translation and text clustering.Research of this computation is generally based on HowNet,according to the distance and the depth of sememes.Based on above,an improved method of word similarity computation was proposed as follows.Firstly,a new variable coefficient of homonym similarity computing was proposed according to the count of homonym.Secondly,it took part of speech into account and argued that the part of speech of homonym is different in contributions to word similarity and removed the combinations of homonyms with different part of speech.The experimental results show that the result obtained through this newly-improved computation method is better with less complex calculation and higher calculation efficiency.

New image encryption algorithm based on cellular neural network

Abstract: In this paper,a new image encryption algorithm was presented by employing Cellular Neural Network(CNN)The main objective was to solve the problem of traditional stream cipher's insensitivity to the change of plain textBy using a hyper chaotic system of 6-D CNN as the key source,selecting the secret key based on the results of logical operations of pixel values in the plain image,and introducing simultaneously both position permutation and value transformation,the new algorithm was presentedIt is shown that both NPCR value and the sensitivity to key(0996) can meet the security requirements of image encryptionThe simulation process also indicates that the algorithm is relatively easy to realize with low computation complexity,and ensures,accordingly,the secure transmission of digital images

Retinex color image enhancement based on adaptive bidimensional empirical mode decomposition

Abstract: In this paper,an adaptive color image enhancement method was proposed: Firstly,color image was transformed from RGB to HSV color space and the H component was kept invariable,while the illumination component of brightness image could be estimated through Adaptive Bidimensional Empirical Mode Decomposition(ABEMD);Secondly,reflection component was figured out by the method of center/surround Retinex algorithm,and the illumination and reflection components were controlled through Gamma emendation and Weber's law and processed with weighted average method;Thirdly,the S component was adjusted adaptively based on characteristics of the whole image,and then image was transformed back to RGB color space.The method could be evaluated by subjective effects and objective image quality assessment,and the experiment results show that the proposed algorithm is better in mean value,square variation,entropy and resolution than MSR algorithm and Meylan's algorithm.

Design and implementation of Android phone based access and control in smart space

Abstract: As a new computing mode,the most essential features of ubiquitous computing,embodied in intelligent space,are physical integration and spontaneous interoperationDue to them,Intelligent phone can get personalized serviceA remote access and control system was proposed in this paper,which was based on the Open Service Gateway Initiative(OSGI) intelligent gateway technologyFirstly,the system architecture was introduced,then the realization of each module was analyzed,finally,testing on actual devices was carried outUsing surrounding services,Android mobile phone realizes the universal access and remote control on other devices

Improved SIR model of computer virus propagation in the network

Abstract: By analyzing the deficiency of the existing network virus models,referring to the reality and considering the infectious disease models in biology,an improved Susceptible-Infected-Removed(SIR) computer virus propagation model with pre-immune measures was put forward.The authors considered the varying number of nodes and analyzed its impact on the spread of the virus in the network.In addition,several related dynamic properties were analyzed.The numerical simulation results demonstrate that improving pre-immune rate and controlling the nodes flow in the network can effectively constrain virus prevalence.And this model has inspiration to predict and prevent from computer virus propagation.

Image acquisition and VGA display system based on FPGA

Abstract: Concerning the drawbacks of traditional PCI frame grabber,using Altera's DE2 development platform,image acquisition and VGA display system of programmable logic chip based on Field-Programmable Gate Array(FPGA) were designed.This system used the programmable logic chip FPGA which was in-built into soft-core NiosⅡ as the controller.The FPGA has image sensor,digital memory,video D/A converter and VGA display interface as its accessories.System used System On a Programmable Chip(SOPC) technology to obtain control and coding over FPGA and its accessories and eventually to acquire,process and display the real-time images.The design results prove that,the electronic system based on SOPC technique is flexible and efficient in terms of designing,ported strong,easy to achieve high-speed data acquisition,and it has high compatibility.

Method of weather recognition based on decision-tree-based SVM

Abstract: To improve the quality of video surveillance outdoors and to automatically acquire the weather situations,a method to recognize weather situations in outdoor images is presentedIt extracted such parameters as power spectrum slope,contrast,noise,saturation as features to realize the multi-classification of weather situations with Support Vector Machine(SVM)Then a decision tree was constructed in accordance with the distance between these featuresThe experimental results on WILD image base and our image set of eight hundred samples show that the proposed method can recognize sunny,overcast,foggy weather more than 85%,and recognize rainy weather more than 75%

Application of G(Galam) model in network public opinion evolution

Abstract: The evolution analysis of network public opinion becomes rather complex because of its interaction,diversity and derivability.At first,this paper analyzed the features of the source,content,dissemination and influence of network public opinion,and introduced G(Galam) model which was applied to the study of the evolution of network public opinion.Through experimental analysis,it is concluded that the final polarization direction of the evolution of network public opinion has certain regularity and controllability.Through the intervention in public communication between individuals and the influence on public in public preferences,the direction of the ultimate evolution of network public opinion can be guided.

Improved adaptive median filtering algorithm

Abstract: The size of median filtering window influences the capability of filter and 3×3 filtering window can preserve image details.An adaptive median filtering method was proposed.The extreme value point in 3×3 filter window was taken as candidate noise.If the candidate noise is extreme value in 7×7 window,then it is a sure noise.If the median value of 3×3 filter window is not noise,then the central noise would be replaced with the median value.The steps above were repeated until there was no noise replaced.If there still existed large noise cluster,the noise would be replaced with the mean of the three signals near it.The experimental results show that the method can denoise impulse noise and protect the image details effectively.

Pornographic images filtering model based on high-level semantic bag-of-visual-words

Abstract: Current pornographic images filtering algorithms have some shortcomings,such as high false positive rate toward the bikinis images and insufficiency when filtering pornographic images with pornographic actions.The paper proposed a new pornographic image filtering model based on High-level Semantic Bag-of-Visual-Words(BoVW).Firstly,local feature points in sex scene were detected using the Speeded-Up Robust Features(SURF) algorithm and then high-level semantic dictionary was constructed by fusing the context of the visual vocabularies and spatial-related high-level semantic features of pornographic images.The experimental results show that the model has an accuracy up to 87.6% when testing the multi-person pornographic images,which is significantly higher than the existing pornographic images filtering algorithm based on BoVW.

Orientation analysis for Chinese blog text based on semantic comprehension

Abstract: Blog has been accepted by more and more people as a popular information and cultural carrier.Orientation analysis for blog text also has become a hot spot in the field of information mining.The previous researches of text orientation mainly focus on plain text or news comments.A method of orientation analysis for blog text based on semantic comprehension was proposed according to the characteristics of blog text.Firstly,a Chinese basic emotional lexicon dictionary based on the HowNet emotional word set was constructed and the emotional value of Chinese emotional words was calculated on the basis of the similarity of Chinese words.Then,the adverbs and its influence on identification of text orientation in the semantic level were analyzed.Finally,the results were amended by using bloggers' language style factors and then the sentimental classification for blog text was realized.The experimental results show that the proposed method can effectively judge the blog text sentimental preference.

Method for BBS topic tracking based on semantic similarity

Abstract: To study the BBS topic tracking,the paper discovered that most of the traditional methods of topic tracking deal with news reports,and they are not suitable when they are applied to BBS.The paper utilized the characteristics of BBS and presented a topic tracking method for BBS data based on semantic similarity.This method firstly constructed keywords tables of topic and post as their representation models,and then computed the two tables' semantic similarity with the help of HowNet which is served as correlation degree between post and topic.Finally,this method used the correlation degree to realize BBS-oriented topic tracking.This method effectively avoids the disadvantage of Vector Space Model(VSM).The experimental results show that this method can solve the problem of BBS-oriented topic tracking effectively.

Performance of an improved artificial bee colony algorithm

Abstract: An improved algorithm based on Artificial Bee Colony(ABC) algorithm was proposed to solve the problem that traditional ABC algorithm is inclined to fall into local optima.In the first stage,the improved ABC algorithm was derived from the skills of extrapolation in mathematics to update the new location of ABC.In the second stage,in order to overcome the deficiency of high position similarity in later stage of evolution and slow renewal rate and enhance the ability of local search in feasible region,a fine-tuning mechanism was introduced to ABC.Simultaneously,the effect of convergence subjected to different perturbation factors was discussed.Finally,the simulation results in three benchmark functions show that the proposed algorithm has better performance than traditional algorithm in search ability and accuracy.

New approach to retinal image enhancement based on Hessian matrix

Abstract: The retina vessel enhancement of retina angiography image is considered as an essential factor to improve diagnosis.Therefore,this paper proposed a multi-scale vessel enhancement method for retinal image based on Hessian matrix.Besides,the strategy and process of applying this method were provided.This method was tested on DRIVE database and its results were compared with other methods using the same database.The result shows a considerable accuracy as other methods while obtaining better robustness.

Improved algorithm of feather image segmentation based on active contour model

Abstract: Using active contour model to get the bone of feathers is affected by other strong edge,and the computation is too much.According to the characteristics of feathers,a method of describing the object contour using the centerline and width was proposed.Two-dimensional contour described in the model was converted into two independent one-dimensional functions,and according to it,the energy function of the model was modified.The improved algorithm made use of symmetry to avoid the interference of strong edges,reduced the computation scale,and it could achieve fully automatic segmentation.The experimental results show that the improved algorithm is robust to noise;it realizes good feather image segmentation and meets industry needs.

Real-time recommendation method based on browsing preferences mining

Abstract: After analyzing the advantages and disadvantages of various algorithms and the main problems of the current recommended technology,this paper put forward a real-time recommendation method based on user's browsing preferences mining.The algorithm first used Bayesian Network(BN) to estimate user's preferences by analyzing his Web browsing history,and then generated recommendations by calculating the matching degree of user's preferences and the characteristics of goods.The experimental results indicate that this method can provide personal recommendations more accurately and efficiently.

Blind identification algorithm for retouched images based on Bi-Laplacian

Abstract: Image retouching is a technique widespreadly used in image tampering.To implement image retouching blind detection,a blind identification algorithm for image was proposed.The algorithm firstly searched for each block in image,and inserted each block into the KD tree,thus obtaining the same value or the nearest match block.Then it used the hierarchical clustering of the position vector to eliminate the scattered matching.Finally,it applied the 7-tap Laplacian filter to count weight of zero connectivity of suspicious blocks to eliminate false positives,thereby located accurately the tampered area.The experimental results show that this method can efficiently and accurately identify the use of a class of image manipulation techniques for uncompressed images and high quality compressed images.When it is applied to the images of higher compression levels,accurate results are also obtained if the region that has been retouched is sufficiently large.