Table of Content

01 May 2013, Volume 33 Issue 05

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Network and communications

Integration system for heterogeneous sensor networks

CHEN Jinkai CAO Jianwei CHEN Qingkui

2013, 33(05):  1191-1193.  DOI: 10.3724/SP.J.1087.2013.01191

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To solve the system integration problem caused by heterogeneous sensor networks, this paper proposed a heterogeneous sensor networks integration system ISHSN (Integration System for Heterogeneous Sensor Network). ISHSN consisted of the gateway of the Internet of Things (IoT) and the access Agent. The gateway converted the data to the same format and converted the command to the customized format according the target sensor network. The access Agent dealt with data collection, link merge and command forward, and balance loading of the access Agents with the scheduling algorithm. The experiment proves that the ISHSN has good scalability and availability in sensor networks data collection and sensor network control.

Two-stage IPv6 route search algorithm based on perfect-Hash table and multibit-trie

Du Fei DONG Zhiguo MIAO Lin TUO YupengYupeng

2013, 33(05):  1194-1202.  DOI: 10.3724/SP.J.1087.2013.01194

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Based on the analysis of the prefix length distribution and prefix level relationships of the routing table, a new IPv6 route search algorithm based on perfect-Hash table and multibit-trie was proposed to improve the efficiency of the IPv6 address search. The prefixes of the addresses divided into intervals were stored in three Hash tables according to the length of 32, 40 and 48, and the rest bits were stored in multibit-tries. IPv6 routing adopted a two-stage search. The first stage was in the perfect-Hash table and the second in the multibit-trie. The experimental results demonstrate that the average search path of the algorithm is 1.0 - 1.7, and it can be applied to the high performance IPv6 route search.

Collaborative Web service composition based on distributed Hash table

CHEN Xi ZENG Huashen WU Tao

2013, 33(05):  1197-1202.  DOI: 10.3724/SP.J.1087.2013.01197

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Centralized CBR (Case-Based Reasoning) is faced with problems such as massive data maintenance cost, high node load and central failure. To tackle these problems, COCO (Distributed Hash Table (DHT) based Collaborative Web Service Composition) was proposed. COCO mappped the workflow and QoS properties of a composite service into a one-dimensional key using Hash function and Space-Filling Curve (SFC). Keys were used for queries of the existing composite services that satisfied user request in a Peer-to-Peer (P2P) fashion in the underlying DHT Overlay. One successful query returned composite services satisfying both functional and non-functional requirements. The experimental results show that COCO has scalable performance on both query delay and query hit rate, indicating COCO's applicability in large-scale network computing environment.

Binary exponential backoff algorithm for slotted ALOHA

FANG Fei MAO Yuming

2013, 33(05):  1203-1207.  DOI: 10.3724/SP.J.1087.2013.01203

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Slot-ALOHA is widely used in wireless communications due to its simplicity. However, because slot-ALOHA is not stable in essence, many algorithms have been used to provide steady throughput. After founding the Markov model for Binary Exponent Backoff (BEB) algorithm, this paper analyzed the adjusting progress. The numerical computation and simulation results demonstrate that BEB algorithm can guarantee the system steady and the theoretic throughput can be derived when the number of modes is within certain range. By comparing throughput of BEB to that of Pseudo-Bayesian Control Algorithm (PBCA), it can derive that the throughput of BEB is less than PBCA when the number of users is either too big or small because of being influenced by the backoff window size.

Node secure localization algorithm in underwater sensor network based on trust mechanism

ZHANG Yao JIN Zhigang LUO Yongmei DU Xiujuan

2013, 33(05):  1208-1211.  DOI: 10.3724/SP.J.1087.2013.01208

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A new security localization algorithm based on trust mechanism was proposed to recognize the malicious beacon nodes timely in UnderWater Sensor Network (UWSN). According to the location information offered by the beacon nodes and combining cluster structure with trust mechanism, this algorithm used Beta distribution to form the initial trust value and the trust update weight could be set as required. In order to reduce the influence of the instability of underwater acoustic channel on the trust evaluation process, meanwhile, recognize the trust cheating of malicious beacon nodes, this algorithm proposed a mechanism named TFM (Trust Filter Mechanism), which calculated and quantized the trust value, and let the cluster head node decide whether each beacon node was credible or not. The results of simulation prove that the proposed algorithm is suitable for UWSNs and it can recognize malicious beacon nodes timely, and the accuracy and security of localization system are greatly improved.

Community-based message transmission scheme in opportunistic social networks

LIU Yahong GAO Yuan QIAO Jinlong TAN Chunhua

2013, 33(05):  1212-1216.  DOI: 10.3724/SP.J.1087.2013.01212

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Since the mainstream forwarding protocol in opportunistic networks does not consider the sociality of node movement, a layering routing algorithm based on copy restriction and human sociality was proposed. This algorithm could dynamically adapt to divide network nodes into different communities according to the nodes intensity of social relation, in which the message copy redundancy was reduced by restricting the number of message copies, and the nodes of high activity were utilized to drive the forwarding and transferring of messages. The simulation results show that it can ensure higher delivery ratio and relatively lower delivery delay, and also reduce the resource consumption of network.

Network protocol reverse parsing technique based on dataflow analysis

DAI Li SHU Hui HUANG Hejie

2013, 33(05):  1217-1221.  DOI: 10.3724/SP.J.1087.2013.01217

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Reverse parsing unknown network protocol is of great significance in many network security applications. Most of the existing protocol reverse parsing methods can not handle the encryption protocol or get the semantic information of the protocol field. To solve this problem, a network protocol parsing technique based on dataflow analysis was proposed. According to the data flow recording tool developed on Pin platform, it could parse the network protocol with the aid of the dependence analysis based data flow tracking technology, as well as obtain the protocol format and semantic information of each protocol field. The experimental results show that the technique can parse out the protocol format correctly, especially for the encryption protocol, and extract the program behavior semantics of each protocol field.

Improved fuzzy auto-regressive model for connection rate prediction

SHEN Chen SUN Yongxiong HUANG Liping LIU Lipeng LI Shuqiu

2013, 33(05):  1222-1229.  DOI: 10.3724/SP.J.1087.2013.01222

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Specific to the need of performance prediction in communication networks, a connection rate prediction method based on fuzzy Auto-Regressive (AR) model was proposed and improved, and the fuzzy AR model based on adaptive fitting degree threshold was studied. The median filtering method was applied to pre-process the data of fuzzy AR model. On this basis, for the uncertain thresholds of some applications, the fitting degree threshold formula was added to the prediction model to make it adaptive. The simulation results show that the predistion method based on fuzzy AR model can be used to predict the connection rate with a higher fitting degree.

Extended joint channel estimation in cooperative multi-cell OFDM systems

CHEN Yixian WANG Yuan

2013, 33(05):  1225-1229.  DOI: 10.3724/SP.J.1087.2013.01225

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Multi-Cell Joint Channel Estimation (MC-JCE) is the practical basis of community collaboration and joint processing technology; however, the MC-JCE needs Power Delay Profile (PDP) knowledge of all channels remains the same and gets known. To solve this problem, based on the cooperative community Orthogonal Frequency Division Multiplexing (OFDM) system framework, this article first explored in the extended multi-cell joint channel estimation (MC-eJCE) algorithm of multi-cell channel PDP differences but known conditions, and then put forward modified multi-cell joint channel estimation (MC-mJCE) algorithm under the condition of this information unknown, at the same time to reduce the computational complexity of algorithm and get minimum Mean Square Error (MSE) of channel estimation. This article used optimal pilot set design of comb pilot to finally derive Cramer-Rao bound of MC-JCE algorithm. The simulation shows the MC-eJCE and MC-mJCE algorithms have good performance of MSE under the conditions of multi-cell channel PDP differences, and Space-Frequency Block Code (SFBC) encoding for joint transmission also has a good performance of Bit Errer Rate (BER) based on the above algorithm for channel estimation.

Spectrogram analysis of frequency-hopping signals based on entropy measure

GUO Jiantao WANG Lin

2013, 33(05):  1230-1236.  DOI: 10.3724/SP.J.1087.2013.01230

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To analyze and estimate the parameters of Frequency-Hopping (FH) signals effectively, an adaptive time-frequency analytical method was proposed according to the characteristics of FH signal spectrogram and Wigner-Ville Didtribution (WVD). The width of window function for spectrogram was selected based on entropy measure so as to obtain optimal spectrogram representation of FH signal. The theoretical analysis and simulation results show that the spectrum analytical method based on entropy measure could give accurate estimation of the hopping cycle of FH signal under the white Gaussian noise environment of greater than 0dB. Compared with Smoothed Pseudo WVD (SPWVD) and its adaptive method, the proposed method can effectively reduce the variance and improve the accuracy of parameter estimation at low Signal-to-Noise Ratio (SNR). While for long observation signal, it owns faster operation speed.

Adaptive variable step-size blind source separation algorithm based on nonlinear principal component analysis

GU Fanglin ZHANG Hang LI Lunhui

2013, 33(05):  1233-1236.  DOI: 10.3724/SP.J.1087.2013.01233

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The design of the step-size is crucial to the convergence rate of the Nonlinear Principle Component Analysis (NPCA) algorithm. However, the commonly used fixed step-size algorithm can hardly satisfy the convergence speed and estimation precision requirements simultaneously. To address this issue, the gradient-based adaptive step-size NPCA algorithm and optimal step-size NPCA algorithm were proposed to speed up the convergence rate and improve tracking ability. In particular, the optimal step-size NPCA algorithm linearly approximated the contrast function and figured out the optimal step-size currently. The optimal step-size NPCA algorithm utilized an adaptive step-size whose value was adjusted in sympathy with the value of the contrast function and free from any manual parameters. The simulation results show that the proposed adaptive step-size NPCA algorithms have faster convergence rate or better tracking ability in comparison with the fixed step-size NPCA algorithm when the estimation precisions are same. The convergence performance of the optimal step-size NPCA algorithm is superior to that of the gradient-based adaptive NPCA algorithm.

Improved weighted multi-modulus blind equalization algorithm based on non-linear function of weighting factor

ZHANG Yanping CUI Weixuan

2013, 33(05):  1237-1240.  DOI: 10.3724/SP.J.1087.2013.01237

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In order to improve the blind equalization performance of the weighted multimode algorithm, an improved weighted multi-modulus blind equalization algorithm based on a non-linear function of weighting factor was proposed in this paper. The new algorithm used a nonlinear relationship between the mean square error and the weighting factor to improve the speed of convergence and improve the adaptive capacity to different signal-to-noise ratio. In the converging process of the algorithm, with the mean square error decreased, the value of the weighting factor increased gradually. It adjusted the modulus value of the algorithm dynamically, and made the error model match with the signal constellation accurately to reduce the steady-state mean square error. The theoretical analysis and simulation results show that the proposed algorithm reduces the steady-state mean square error, and improves the convergence rate.

Estimation algorithm for real-valued direction of arrival based on modified propagator method

HUANG Guangya DENG Xiaofei LIANG Pingyuan

2013, 33(05):  1241-1243.  DOI: 10.3724/SP.J.1087.2013.01241

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The real-valued modified propagator method was proposed to solve the large computational load problem of modified propagator direction of arrival estimation method. This proposed method employed the unitary transformation to rearrange the propagator to be real matrix, which decreased the computational load through the real-valued spectrum peak scanning. And it remained the same estimation performance with modified propagator method. At last, the simulation results confirm that the proposed algorithm can achieve superior estimation precision with lower computational load, compared with modified propagator method, propagator method and multiple signal classification method.

Improved two-stage cooperative spectrum sensing algorithm in cognitive radios

LIU Yang JI Wei

2013, 33(05):  1244-1247.  DOI: 10.3724/SP.J.1087.2013.01244

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Two-stage cooperative spectrum sensing that used both soft combining and hard combining need to send much unnecessary information to fusion center in the second stage. Concerning this problem, this paper proposed an improved algorithm by estimating Signal-to-Noise Ratio (SNR). The improved algorithm selected traditional two-stage scheme to improve the performance of spectrum when SNR was low and selected hard combining scheme to decrease the number of sending data when SNR is high. The simulation results show that the proposed algorithm decreases much unnecessary soft information being sent to fusion center at the cost of a little loss in performance of detection as compared to an existing two-stage cooperative spectrum sensing algorithm.

PROFIBUS-based reading method of smart meter's data

CAO Shiwei ZHU Qing LIU Hongli

2013, 33(05):  1248-1254.  DOI: 10.3724/SP.J.1087.2013.01248

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Communication of most smart meters is based on MODBUS protocol or 645 protocol, which is insufficient for the transmission of large amounts of data from smart meter. A new reading method and its system based on PROFIBUS were proposed. The system included PROFIBUS based master (Programmable Logic Controller, PLC) and slave stations connected by ROFIBUS bus, and the master station consisted of the Network Interface Card (NIC) of Siemens PLC/CP5611, STEP 7 programming software and WINCC monitoring software; the slave station was a smart meter which contained a PROFIBUS module wired with the Micro Control Unit (MCU) in the smart meter. This PROFIBUS-based reading method and its system of smart meter's data is easy to implement, fast in data transmission, and with communication rate of up to 12Mb/s.

Fast rate control algorithm for high efficiency video coding

Wu Min GONG Yanchao YANG Kaifang

2013, 33(05):  1251-1254.  DOI: 10.3724/SP.J.1087.2013.01251

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By analyzing the current rate control algorithm, i.e., JCTVC-H0213 for high efficiency video coding, a new fast and effective method to derive the quantization parameter was proposed, relying on the ratio of the targeted bitrate to the actual coding bitrate of the previous frame. The proposed algorithm was implemented on the HM6.3 platform in the constant bit rate case. The experimental results show that the proposed algorithm outperforms JCTVC-H0213 rate control algorithm. A performance gain in variety of Peak Signal-to-Noise Ratio (PSNR) of more than 2.4 dB can be observed. In conclusion, the proposed algorithm achieves outstanding rate distortion performance with a low complexity, which makes it well suited to real-time scenarios.

Sequential acquisition method based on sequence core transform

TIAN Zhumei JI Jiang REN Guofeng LI Haixia

2013, 33(05):  1255-1259.  DOI: 10.3724/SP.J.1087.2013.01255

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The existing sequential acquisition methods search the correlation peak continuously in receiving signals, thus wasting a great deal of calculation resources to search correlation peak in the received signal containing no target sequence. In another case, with the sequence period increasing, the calculation resources perform exponential growth. As a result, the target sequence can be hardly got. In order to reduce the calculation resources, the paper presented a sequence core transform method to acquire the sequence. The method compressed the entire sequence information into the local sequence core, and by this sequence core, the acquiring process was divided into two steps: sequence detection and sequence acquisition. In this process, the calculation resources were reduced because the sequence acquisition only occured in the second step. Furthermore, by using the down-sampling on received signals, the sequence core transform could decrease the sequence amount needed in the acquiring process. The theoretical analysis and simulation results show that, by losing some acquiring performance, the algorithm can reduce the calculation resources to complete acquisition in one sequence period. And the reduced calculation resources increase with the sequence period.

Network and distributed techno

Graph-based parallel distributed genetic programming model

LU Qiang ZHONG Wei WANG Zhiguang

2013, 33(05):  1260-1266.  DOI: 10.3724/SP.J.1087.2013.01260

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Since Genetic Programming (GP) is of natural parallelism, the parallel and distributed GP model was developed, including master-slave model, island model and grid model. However, the realizing algorithm of these distributed models is complex and they cannot be reused. It is difficult to achieve the scale computation of GP quickly based on different topologies. Due to these shortcomings, the authors presented the graph-based parallel distributed GP model which realizes formal description of the various operations of GP, and could support the distributed parallel computation of GP for different topologies. It is easy to achieve the master-slave model, island model and grid model of GP through experimental test. The new model is stable, efficient and easy to realize.

Formal modeling for structured document in cloud computing

XIONG Jinbo YAO Zhiqiang JIN Biao

2013, 33(05):  1267-1270.  DOI: 10.3724/SP.J.1087.2013.01267

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Structured document plays a vital role in information carrier for information interaction and propagation in cloud computing. However, the existing research works lack structured document model that can describe this information carrier. In order to tackle this issue, the authors formalized the definitions of document element, atomic document element, connection, document fragment, and complex document element based on the in-depth analysis of the special characteristics of structured document in cloud computing. Furthermore, the authors proposed structured document model (referred to as the SDoc) satisfying the special characteristics in cloud computing. Finally, several open issues were indicated for structured document.

Deployment of virtual machines with clustering method based on frame load awareness

WANG Guangbo MA Zitang SUN Lei WU Le

2013, 33(05):  1271-1288.  DOI: 10.3724/SP.J.1087.2013.01271

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Concerning the deployment of virtual machines in the cloud computing, an algorithm on the deployment of virtual machines with clustering method based on frame load awareness was proposed. First of all, the load of each layer in datacenter was computed and the clustering of physical machines in each layer was constructed. In the process of deploying virtual machines, the clustering of virtual machines was first done according to some rules and then the frame with lower load was chosen preferentially. The last step was to match the virtual machines cluster and physical machines cluster in order to deploy the optimal physical machines cluster. The performance of the algorithm was validated with the experiments in CloudSim. The result was compared to that of the greedy algorithm and basic deployment algorithm with the frame load awareness, which shows that the algorithm proposed in this article has evident priority, and improves the utilization rate of network resources.

Construction method of mobile cloud computing system based on mobile Agent

WANG Suzhen DU Zhijuan

2013, 33(05):  1276-1280.  DOI: 10.3724/SP.J.1087.2013.01276

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This paper proposed a mobile cloud computing architecture based on mobile Agent paradigm concerning the problems faced by the mobile cloud computing, such as application migration on network, network latency and non-persistent connection issues caused by execution on the remote device, cross-cloud service problems, and security risks and privacy issues. In this architecture, break-point saving ideas and events replay mechanism were introduced in application migration issues, optimized contract net protocol was used in the synergy between the mobile Agents, and mobile Agent exchange keys for authentication. What's more, this paper described the workflow of this architecture using colored nested Petri nets, and designed a system of mobile e-book sales based on the architecture.

Multi-input-multi-output support vector machine based on principal curve

MAO Wentao ZHAO Shengjie ZHANG Junna

2013, 33(05):  1281-1293.  DOI: 10.3724/SP.J.1087.2013.01281

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To solve the problem that the traditional Multi-Input-Multi-Output (MIMO) Support Vector Machine (SVM) generally ignore the dependency among all outputs, a new MIMO SVM algorithm based on principal curve was proposed in this paper. Following the assumption that the model parameters of all outputs locate on a manifold, this paper firstly constructed a manifold regularization based on the Multi-dimensional Support Vector Regression (M-SVR), where the regularizer was the squared distance from the output parameters to the principal curve through the middle of all parameters' set. Secondly, considering the non-convexity of this regularization, this paper introduced an alternative optimization method to calculate the model parameters and principal curve in turn until convergence. The experiments on simulated data and real-life dynamic load identification data were conducted, and the results show that the proposed algorithm performs better than M-SVR and SVM based separate modeling method in terms of prediction precision and numerical stability.

New gene selection method based on clustering and particle swarm optimization

YANG Shanxiu HAN Fei GUAN Jian

2013, 33(05):  1285-1288.  DOI: 10.3724/SP.J.1087.2013.01285

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Since traditional gene selection methods may select a large number of irrelevant genes, which leads to low sample prediction accuracy, a new hybrid method based on clustering and Particle Swarm Optimization (PSO) was proposed for gene selection of microarray data in this paper. Firstly, genes were partitioned into a certain number of clusters by using clustering algorithm. Then Extreme Learning Machine (ELM) was applied to validate the classification performance of the genes selected from each cluster, which formed an initial gene pool. Finally, the wrapper approach based on PSO and ELM was used to select compact gene subset with high classification accuracy from the initial gene pool. The better classification accuracy on microarray data was provided with the genes selected by the proposed method. The experiments on two public microarray data sets verify that the proposed method can obtain better classification performance with fewer genes than other classical methods.

Reachability analysis of nonlinear hybrid systems based on polyhedron inclusion

ZOU Jin LIN Wang LUO Yong ZENG Zhenbing

2013, 33(05):  1289-1293.  DOI: 10.3724/SP.J.1087.2013.01289

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To study the reachability of a class of nonlinear hybrid systems, this paper presented an verification method based on polyhedron inclusion. Firstly, some notions about hybrid systems and reachability were introduced. The method based on polyhedron inclusion was proposed to compute the linear approximation of polynomial hybrid systems. Quantifier elimination and nonlinear optimization method were applied to obtain the associated linear hybrid systems. Then the over-approximation of reachable set of original polynomial hybrid systems can be computed by using SpaceEx. Furthermore, the safety properties of the systems also can be verified.

Artificial intelligence

Key technology of knowledge reuse in product design based on axiomatic design

YANG Jie CHEN Xuezhao

2013, 33(05):  1294-1312.  DOI: 10.3724/SP.J.1087.2013.01294

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Due to the multi-hierarchy, multi-attribute process of product design, the key technology of knowledge reuse in product design based on axiomatic design was studied. With the axiomatic design framework, the design process was decomposed, and the Z map of the requirement domain, functional domain, structure domain, process domain of the product design was put forward. Then, a case-based knowledge reuse method with overall consideration of inter-domanin and intra-domain design information was presented, which adopted the similarity-based retrieving in knowledge reuse algorithm, and got the best reuse objects. Finally, a case was provided to validate and prove the efficiency and feasibility of the method.

Multi-robot formation based on biological inspired neural network

YANG Xiaofang NI Jianjun

2013, 33(05):  1298-1304.  DOI: 10.3724/SP.J.1087.2013.01298

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Multi-robot formation control is an important issue in the multi-robot cooperation field. It is a hot and difficult problem to achieve multi-robot dynamic formation while making them move toward the same target. Concerning this problem, a new biological inspired neural network based approach for multi-robot formation was proposed in this paper. In the proposed approach, a leader-referenced formation model was used to calculate the virtual target location for each robot in real-time, and a biological neural network was used to realize multi-robot navigation. Finally, some simulation experiments were carried out. The experimental results show that the proposed approach has some good performances, such as the real-time obstacle avoidance, keeping formation and moving toward the same target. Furthermore, multi-robots can change the formation quickly, which proves the real-time and intelligence of the proposed approach.

Similar key posture transformation based on hierarchical Option for humanoid robot

KE Wende PENG Zhiping CHEN Ke XIANG Shunbo

2013, 33(05):  1301-1304.  DOI: 10.3724/SP.J.1087.2013.01301

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Concerning the problem in which the fixed locomotion track captured from human movement can not be used in transformation between key postures for humanoid robot, a method of similar key posture transformation based on hierarchical Option for humanoid robot was proposed. The multi-level dendrogram of key postures was constructed and the difference of key postures was illustrated in respects of similar joint difference, moment total similar difference, period total similar difference. The hierarchical reinforcement Option learning was introduced, in which the sets of key postures and Option actions were constructed. SMDP-Q method tended to be the optimal Option function by the accumulative rewards of key posture difference and the transformations were realized. The experiments show the validity of the method.

Improved artificial fish swarm algorithm based on social learning mechanism

ZHENG Yanbin LIU Jingjing WANG Ning

2013, 33(05):  1305-1329.  DOI: 10.3724/SP.J.1087.2013.01305

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The Artificial Fish Swarm Algorithm (AFSA) has low search speed and it is difficult to obtain accurate value. To solve the problems, an improved algorithm based on social learning mechanism was proposed. In the latter optimization period, the authors used convergence and divergence behaviors to improve the algorithm. The two acts had fast search speed and high optimization accuracy, meanwhile, the divergence behavior enhanced the population diversity and the ability of skipping over the local extremum. To a certain extent, the improved algorithm enhanced the search performance. The experimental results show that the proposed algorithm is feasible and efficacious.

Particle swarm optimization algorithm with fast convergence and adaptive escape

SHI Xiaolu SUN Hui LI Jun ZHU Degang

2013, 33(05):  1308-1312.  DOI: 10.3724/SP.J.1087.2013.01308

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In order to overcome the drawbacks of Particle Swarm Optimization (PSO) that converges slowly at the last stage and easily falls into local minima, this paper proposed a new PSO algorithm with convergence acceleration and adaptive escape (FAPSO) inspired by the Artificial Bee Colony (ABC) algorithm. For each particle, FAPSO conducted two search operations. One was global search and the other was local search. When a particle got stuck, the adaptive escape operator was used to search the particle again. Experiments were conducted on eight classical benchmark functions. The simulation results demonstrate that the proposed approach improves the convergence rate and solution accuracy, when compared with some recently proposed PSO versions, such as CLPSO. Besides, the results of t-test show clear superiority.

Adaptive Chaos Fruit Fly Optimization Algorithm

HAN Junying LIU Chengzhong

2013, 33(05):  1313-1333.  DOI: 10.3724/SP.J.1087.2013.01313

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In order to overcome the problems of low convergence precision and easily relapsing into local extremum in basic Fruit Fly Optimization Algorithm(FOA), by introducing the chaos algorithm into the evolutionary process of basic FOA, an improved FOA called Adaptive Chaos FOA (ACFOA)is proposed. In the condition of local convergence, chaos algorithm is applied to search the global optimum in the outside space of convergent area and to jump out of local extremum and continue to optimize. Experimental results show that the new algorithm has the advantages of better global searching ability, speeder convergence and more precise convergence.

Improved gravitation search algorithm and its application to function optimization

ZHANG Weiping REN Xuefei LI Guoqiang NIU Peifeng

2013, 33(05):  1317-1320.  DOI: 10.3724/SP.J.1087.2013.01317

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Gravitational Search Algorithm (GSA) easily traps into local optimal solutions and its optimization precision is poor when being applied to function optimization problems. An improved GSA (IGSA) was put forward to solve these problems. It significantly improved the exploration and exploitation abilities of GSA, and had good global and local optimization abilities by introducing opposite learning strategy, elite strategy and boundary mutation strategy. The proposed IGSA had been evaluated on six nonlinear benchmark functions. The experimental results show that, compared with standard GSA, the weighted GSA (WGSA) and Artificial Bee Colony (ABC) algorithms, the IGSA has much better optimization performances in solving various nonlinear functions.

Parameters optimization of combined kernel function for support vector machine

GENG Junbao SUN Linkai CHEN Shixue

2013, 33(05):  1321-1356.  DOI: 10.3724/SP.J.1087.2013.01321

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Concerning the lack of an integrated theory system to select the parameters of combined kernel function used in Support Vector Machine (SVM), one method based on ant colony algorithm and circulated cross validation was put forward to get the optimal parameters. The index named as the mean weighting error was used to evaluate the effect of SVM prediction in different parameters. The value of mean weighting error could be calculated by circulated cross validation. To decrease the calculation workload, the ant colony algorithm was used to enhance the optimization effect of combined kernel function for SVM. This method offered in this paper was applied in the prediction of some plan development cost and the result showed that the optimized combined form of the parameters had the least prediction error. The instance indicates that the parameters optimization method in this paper can improve the prediction precision.

Database technology

Research survey on formal description for direction relations

WANG Miao LI Songyang

2013, 33(05):  1324-1329.  DOI: 10.3724/SP.J.1087.2013.01324

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As a fundamental problem in the research field of spatial direction relation, representation and modeling for direction relations has been a hot and difficult issue in the areas of geographic information system, spatial database and artificial intelligence in recent years and a series of research achievements have been obtained. This paper comprehensively surveyed the researches on the formal description models for direction relations between precise objects in 2D space, direction relations between precise objects in 3D space and direction relations between fuzzy objects, analyzed and compared various kinds of models and pointed out the advantages and disadvantages of each model. Finally, it clearly pointed out that modeling for 3D direction relations and fuzzy direction relations was a major concern and especially modeling for fuzzy direction relations in 3D space was a priority in the future research. Besides, several key urgent problems were suggested, which provided reference to further research.

Recommendation research based on general content probabilistic latent semantic analysis model

ZHANG Wei HUANG Wei XIA Limin

2013, 33(05):  1330-1333.  DOI: 10.3724/SP.J.1087.2013.01330

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In the recommendation system, some new items and the accuracy issue cannot be well controlled. Therefore, a new recommendation method based on general content Probabilitistic Latent Semantic Analysis (PLSA) model was proposed. The general content PLSA model contained two latent variables indicating the user groups and item groups, and contained features of items that were trained by asymmetric learning algorithm. The experimental results show that the new method has good quality for recommendation on three different data sets.

Spam short message classifier model based on word terms

ZHANG Yongjun LIU Jinling

2013, 33(05):  1334-1337.  DOI: 10.3724/SP.J.1087.2013.01334

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A classifier model based on word terms was proposed to classify Spam Short Messages (SSM). The concept of word-category weight was introduced for representing a word effect of identifying the category a SSM belongs to and a method was put forward to calculate the word-category weight. Based on the word-category weight, a dimension reduction was carried out to get word items set.The Short message-Category Membership Value (SCMV) was used to illustrate how much a SSM belonged to a category, then a classifying algorithm was implemented by computing SCMV and SCMV density. To improve the accuracy of classification and make the word-category weight more reasonable, an word-weight iterative learning procedure was performed. The experimental results show that the proposed model is superior to other classification methods in terms of classification performance and time complexity.

Taxi gathering area recognition algorithm based on sample weight

JI Bo YE Yangdong LU Hongxing

2013, 33(05):  1338-1342.  DOI: 10.3724/SP.J.1087.2013.01338

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Dynamic, random and asynchronous taxi objects can be grouped by clustering methods. However, the traditional clustering methods treat all taxi samples equally and set weights of all samples without distinction when evaluating similarity. However, not all of the features are important to the clustering judgment. Therefore, the paper proposed a taxi gathering area recognition SFTA-IB algorithm based on sample weight. The SFTA-IB algorithm introduced sample weight to reveal the contribution level of different samples. Then, the SFTA-IB algorithm considered the taxis as the original variable X, the GPS data as the relevant variable Y. The goal was to find a compressed representation T, which was as informative as possible about Y. The experimental results show that the proposed SFTA_IB algorithm can identify the taxi gathering areas for one specified taxi, supervise the cruise strategy and improve the passenger searching efficiency.

Information security

Dependable data survival scheme based on Chinese remainder theorem weighted threshold secret sharing in unattended WSN

HAN Mingjun XIONG Yan LU Qiwei GONG Xudong LIU Tao

2013, 33(05):  1343-1346.  DOI: 10.3724/SP.J.1087.2013.01343

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Unattended Wireless Sensor Network (UWSN) is usually deployed in a bad or hostile environment. The deployment of static aggregation node (or base station) is difficult, making real-time information aggregation impossible. Hence the node should undertake the mission of self-sustaining the data temporarily. In order to enhance the probability of data survival, this paper proposed a dependable data survival scheme based on Chinese Remainder Theorem (CRT) weighted threshold secret sharing in UWSN. The scheme built a node reputation model in the network, improving the efficiency and effectiveness of key division, distribution and reconstruction. In addition, this paper also discussed the good homomorphism properties of CRT based multi-secret sharing, and the key combination operation scheme, which further ensures the reliable survival of data.

Active defense strategy selection based on non-zero-sum attack-defense game model

CHEN Yongqiang FU Yu WU Xiaoping

2013, 33(05):  1347-1352.  DOI: 10.3724/SP.J.1087.2013.01347

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In order to deal with the problems that defensive measures are lagging behind the attack and that the payoffs of attacker and defender are unequal, an active strategy selection method based on non-zero-sum game was proposed. Firstly, a network security game graph was presented combined with the actual situation of network security and the relationship between the attacker and the defender. Secondly, a network attack-defense game model was proposed based on non-zero-sum game. The attack-defense cost of single security attribute was calculated combined with the host important degree and success rate of defense measures, and according to attack-defense intention, the total attack-defense cost was quantified. Finally, the best strategy for defender was obtained by analyzing the Nash equilibrium of the game model. A representative example was given to illustrate the efficacy and feasibility of the method on attack prediction and active defense strategy selection.

Authentication protocol of mobile RFID based on Hash function

LIU Peng ZHANG Changhong OU Qingyu

2013, 33(05):  1350-1352.  DOI: 10.3724/SP.J.1087.2013.01350

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In order to resolve the security issues of Mobile-Radio Frequency Identification (M-RFID), the author designed a lightweight authentication protocol based on Hash. It can achieve the mutual authentication between tags, readers and servers in the environment of wireless communication. It can prevent a series of security issues such as replay attacks, unauthorized reading, and location tracking. GNY logic was applied to prove that the agreement is sufficient to meet the security needs.

New two-party key agreement protocol in separate networks

LI Haifeng LAN Caihui ZUO Weiping MA Haiyun

2013, 33(05):  1353-1356.  DOI: 10.3724/SP.J.1087.2013.01353

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There is much research about key agreement focus on the secure communication in the same Key Generation Center (KGC), i.e. all the parameters of different participants should be provided by one KGC. To realize the secure communication between two users in different KGCs, adopting elliptic curve cryptography algorithm, a new two-party ID-based key agreement protocol was proposed. This new scheme realized key agreement protocol in separate networks between two participants. Then the improved Blake-Wilson model was used to prove the security of the scheme. After being analyzed, the new protocol was proved to be secure, efficient and of lower computational cost. Therefore, the new scheme will be compatible with low-power and lightweight devices.

Feature selection for network intrusion detection based on quantum evolutionary algorithm

ZHANG Zongfei

2013, 33(05):  1357-1361.  DOI: 10.3724/SP.J.1087.2013.01357

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Concerning the disadvantages of slow detection speed in current network intrusion detection, a new feature selection method of network intrusion detection was put forward. The method applied Quantum Evolutionary Algorithm (QEA) to feature selection of network intrusion detection, extracted an optimal subset used in intrusion detection from the original feature set in network connections, so as to get better detection efficiency. First, QEA was improved in order to make its searching performance better, and the criterion function of feature subset was constructed based on the Fisher ratio of feature attributes. Then, the feature selection algorithm of network intrusion detection was designed according to QEA flow. Last, experiments were carried out using the sample data from KDD99. The experimental results show that the proposed algorithm is effective, and it can not only ensure the classification performance of intrusion detection but also improve the detection efficiency.

New P2P botnet with high survivability based on Kademlia protocol

ZHU Junhu LI Heshuai WANG Qingxian QIU Han

2013, 33(05):  1362-1377.  DOI: 10.3724/SP.J.1087.2013.01362

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At present there are many kinds of technologies which can track, detect and counter botnet effectively, which are serious threats to botnet. In order to improve the survivability of botnets, with the analysis on the existing anti-botnet technology, the paper proposd a new P2P-botnet based on Kademlia protocol from an attacker's prospective. A communication encryption and node authentication mechanism was designed. The theoretical analysis shows that the mechanism can effectively address improper command attack and sybil attack. Eventually, the experimental results verify that this botnet has high survivability.

Authorization query method for RBAC based on partial MAX-SAT solver

SUN Wei LI Yanling LU Jun

2013, 33(05):  1367-1390.  DOI: 10.3724/SP.J.1087.2013.01367

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In order to ensure system security and reflect availability in authorization management, a method for querying authorization was proposed based on solvers for partial maximal satisfiability problem. Static authorization descriptions and dynamic mutually exclusive constraints were translated into hard clauses. The algorithm was adopted to update hard clauses and translate requested permissions into soft clauses. Soft clauses were effectively encoded, and the recursive algorithm was utilized to satisfy all hard clauses and as many soft clauses as possible. The experimental results show that the method can ensure system security, it follows the least privilege principle, and the query efficiency outperforms solvers for maximal satisfiability problem.

Image tamper detection scheme based on chaotic system and fragile watermarking

LIU Min CHEN Zhigang DENG Xiaohong

2013, 33(05):  1371-1373.  DOI: 10.3724/SP.J.1087.2013.01371

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In order to solve the shortage of the method based on fragile watermarking, a new chaotic system and fragile watermarking based image tamper detection algorithm was proposed. Firstly, the method used Arnold cat map k times to scramble the original image, and then chose the Least Significant Bit (LSB) plane of the scrambled image as the embedding position. The actual watermark information was formed by using exclusive-or operation between a random binary sequence produced by Logistic map and the original watermark, and the LSB replacement method was utilized to embed watermark. Finally, the watermarked image was obtained by utilizing Arnold cat map T-k times. The experimental results show that, the introduction of chaotic system to a great extend improves the security of the proposed scheme. In addition, the proposed method achieves superior tamper detection and localization accuracy under different common attacks.

Research and implementation of four-prime RSA digital signature algorithm

XIAO Zhenjiu HU Chi CHEN Hong

2013, 33(05):  1374-1377.  DOI: 10.3724/SP.J.1087.2013.01374

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In order to improve the operation efficiency of big module RSA (Rivest-Shamir-Adleman) signature algorithm, four prime Chinese Remainder Theorem (CRT)-RSA digital signature was suggested in this paper. The Hash function SHA512 was used to produce message digest, and CRT combining with Montgomery algorithm was applied to optimize large number modular exponentiation. The security analysis and experiment show that the new algorithm can resist some common attacks, and it has some advantages in signature efficiency.

Cryptanalysis and improvement of a certificateless signature scheme

HE Junjie WANG Juan QI Chuanda

2013, 33(05):  1378-1381.  DOI: 10.3724/SP.J.1087.2013.01378

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Security analysis of the certificateless signature scheme proposed by Guo L L, et al. (Guo L L, Lin C L, Zhang S Y. Attack and improvement for certificateless signature scheme. Computer Engineering, 2012, 38(16): 134-137,141) showed that the scheme was insecure against public key replacement attack. An improved scheme which can resist public key replacement attack was proposed. The scheme was proved to be existentially unforgeable against adaptive chosen message and identity attacks in random oracle model, and the security was reduced to computational Diffie-Hellman assumption. Compared with other certificateless signature schemes based on bilinear pairing, the improved scheme has better computational efficiency.

Effective and secure identity-based hybrid signcryption scheme

TONG Ruiyang MENG Qingxian CHEN Ming

2013, 33(05):  1382-1393.  DOI: 10.3724/SP.J.1087.2013.01382

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The existing identity-based hybrid signcryption schemes have either known security flaws or higher computational costs. With the vBNN-IBS signature algorithm, a new identity-based hybrid signcryption scheme was proposed. The new scheme, based on the Discrete Logarithm Problem (DLP) and the Computational Diffie-Hellman (CDH) problem on elliptic curve, did not use bilinear operation. So, the total computational costs of the new scheme were effectively reduced, and had only 7 scalar multiplication operations on elliptic curve, which were much lower than the other silimar schemes. In the random oracle model, the new scheme was verified safe enough to achieve the unforgeability and confidentiality. In addition, the paper also pointed out that the Sun et al's scheme (Sun Y X, Li H. Efficient certificateless hybrid signcryption. Journal of Software, 2011,22(7):1690-1698) did not satisfy the unforgeability.

Concurrent signature scheme constructed by identity-based ring signcryption

LIU Kui LIANG Xiangqian LI Xiaolin

2013, 33(05):  1386-1390.  DOI: 10.3724/SP.J.1087.2013.01386

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The identity-based ring signcryptions have both high efficiency of identity-based cryptosystem and signcryption technology and the ambiguity of ring signature. In the fair exchange protocol based on signcryption proposed by Luo, et al (Luo M, Zou C H, Hu J, 〖WTBX〗et al.〖WTBZ〗Signcryption-based fair exchange protocol. Journal of Communications, 2010, 31(8A): 146-150), the fairness and efficiency are not good enough. The new scheme introduced a more efficient identity-based ring signcryption and dealt with the decryption and the signature-and-identity binding separately. A new fair exchange protocol was proposed based on this new scheme. The analysis shows that this scheme overcomes the fairness defect of the original scheme and has a better efficiency, which makes it a good application in electronic payment and contract signing.

Verifiable multi-secret sharing scheme based on linear one-way function

ZHANG Xiaomin

2013, 33(05):  1391-1393.  DOI: 10.3724/SP.J.1087.2013.01391

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Based on Shamir's threshold secret sharing scheme, the security of the linear one-way function and the difficulty of the discrete logarithm problem, a verifiable multi-secret sharing scheme was proposed．In this scheme, each participant needed just one secret share to share a set of secrets．Before recovering the secrets, participants could verify the correctness of the shadow shares provided by other participants．After recovering all of the secrets, the secret shares of the participants were still kept confidential and the secret shares could be used to share a new set of secrets．At the same time，the proposed scheme had fewer public parameters，and it did not require secure communication channels．

Network and distributed techno

Improved Gaussian mixture model and shadow elimination method

CHEN Lei ZHANG Rongguo HU Jing LIU Kun

2013, 33(05):  1394-1400.  DOI: 10.3724/SP.J.1087.2013.01394

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To reduce the computation of Gauss mixture model effectively and improve the accuracy of shadow elimination in moving object detection, an algorithm which updated the model selectively and eliminated the shadow by the change of brightness was proposed. Firstly, the weight of the Gauss distribution and the rate of those that did not belong to the background were compared before updating the Gauss distribution, if the former was larger, then did not update it, otherwise, updated it; Secondly, the range of brightness change was chosen to be a threshold factor of shadow detection, so that the threshold could be adjusted adaptively according to the change of brightness. Finally, compared this algorithm with the traditional ones through experiments on indoor and outdoor videos, the experimental results show that the time consumption of the algorithm is about one-third of the traditional ones, the accuracy of shadow eliminating is improved and the efficiency of the algorithm is confirmed.

Method of getting arc length segmentation point for B-spline curve based on given accuracy

DING Lijun DAI Shuguang MU Ping'an HOU Wenmei

2013, 33(05):  1398-1400.  DOI: 10.3724/SP.J.1087.2013.01398

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Arc length accurate segmentation for parameters curve such as B-spline curve is an important issue in the detection and processing along a curved path. This article analyzed the relationship of arc length calculation method, calculation error and segmentation accuracy of B-spline curve. The arc length searching interval and arc length dichotomy were specified to meet the accuracy requirements of arc length segmentation point. The experiments show that the method is effective in accurate segmentation of arc length for parametric curve.

Moving object detection based on background image set and sparse analysis

BAO Jinyu WANG Huibin CHEN Zhe SHEN Jie

2013, 33(05):  1401-1410.  DOI: 10.3724/SP.J.1087.2013.01401

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This paper proposed a moving target detection method based on the background image set and sparse representation. The method combined the Robust Principal Component Analysis (RPCA) and the image block analysis method based on sparse representation. The authors got a series of background images from a video sequence by RPCA, and combined these background images as the background image set, treating image block as basic unit, and moving target was extracted from input frame by image block analysis method based on sparse representation. The simulation results indicate that when the background illumination mutates, the proposed method can effectively eliminate the impact of environment noise and reduce the false detection rate of target detection.

Weighted-distance-based asynchronous retrieval for mechanical design images

FANG Naiwei LYU Xueqiang ZHANG Dan WANG Hongwei

2013, 33(05):  1406-1410.  DOI: 10.3724/SP.J.1087.2013.01406

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According to the shape features of mechanical design images, an asynchronous retrieval method based on weighted distance was proposed. The algorithm firstly got preliminary results from the image database by using the circumcircle distance feature, and then calculated the weighted distances between the input image and the preliminary results, by considering both the formal output positions and the Hu invariant moments feature. The experiments show that compared with the traditional methods, the proposed method gets higher precision and recall ratio.

Multi-plane detection algorithm of point clouds based on volume density change rate

CHU Jun WU Tong WANG Lu

2013, 33(05):  1411-1419.  DOI: 10.3724/SP.J.1087.2013.01411

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Most existing methods for detecting plane in point cloud cost long operation time, and the result of detection is susceptible to noise. To address these problems, this paper put forward a kind of multi-plane detection algorithm based on geometric statistical characteristics of the point clouds. The proposed method coarsely segmented point clouds according to the change rate of the volume density firstly, then used the Multi-RANSAC to fit planes, at last the authors proposed a new merge-constraint condition to combine and optimize the initial fitted planes. The experimental results show that the method in this paper is easy to realize, can effectively reduce the influence of cumulative noise to the detection results, improve the plane detection accuracy and also greatly reduce the computing time.

Feature-retained image de-noising via sparse representation

MA Lu DENG Chengzhi WANG Shengqian LIU Juanjuan

2013, 33(05):  1416-1419.  DOI: 10.3724/SP.J.1087.2013.01416

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According to the theory of sparse representation, images can be sparse-represented by using an appropriately redundant dictionary. The completeness can enable using very few big coefficients to capture the important information of images, and cause more robust to noise. Regarding image de-noising, considering the human visual characteristics, this paper studied the effective representation of characteristics and edge information of noisy image based on complete dictionary. For more effective feature retaining of images, a method of feature-retaining de-noising via sparse representation was proposed, which made the Structural SIMilarity (SSIM) as fidelity measure of the information. The experimental results indicate that the proposed algorithm has a better efficiency of de-noising, enhances the capacity of retaining feature, and gets a better visual effect of de-noised image.

Non-local means denoising approach based on dictionary learning

CUI Xueying ZHANG Quan GUI Zhiguo

2013, 33(05):  1420-1422.  DOI: 10.3724/SP.J.1087.2013.01420

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Concerning the measurement of the similarity of non-local means, a method based on dictionary learning was presented. First, block matching based local pixel grouping was used to eliminate the interference by dissimilar image blocks. Then, the corrupted similar blocks were denoised by dictionary learning. As a further development of classical sparse representation model, the similar patches were unified for joint sparse representation and learning an efficient and compact dictionary by principal component analysis, so that the similar patches relevency could be well preserved. This similarity between the pixels was measured by the Euclidean distance of denoised image blocks,which can well show the similarity of the similar blocks. The experimental results show the modified algorithm has a superior denoising performance than the original one in terms of both Peak Signal-to-Noise Ratio (PSNR) and subjective visual quality. For some images whose structural similarity is large and with rich detail information, their structures and details are well preserved. The robustness of the presented method is superior to the original one.

One-dimensional objects design and calibration in infrared camera group

LI Bin TAN Guanghua GAO Chunming

2013, 33(05):  1423-1449.  DOI: 10.3724/SP.J.1087.2013.01423

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In order to match coordinates between space and infrared image without color and texture in the calibration process, a design criterion for one-dimensional objects was presented. When one-dimensional objects met a given ratio of those objects, the corresponding coordinates could be acquired by the pixels' distance. The design reliability was theoretically proved.The experiment shows that one-dimensional objects satisfying the design criterion are easy to operate and convenient to match, so infrared camera calibration can obtain very high accuracy.

Method of simulating realistic snow scene

XU Yuanjin ZENG Liang CHEN Shilong

2013, 33(05):  1428-1431.  DOI: 10.3724/SP.J.1087.2013.01428

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The particle system can hardly simulate the natural features effectively and real-time at the same time. Based on the analysis of traditional simulation methods, a real-time rendering algorithm was presented. The algorithm used rectangular elementary to simulate snow particles，added texture mapping based on superposition，normalized snow lifecycle for color blending，and regulated the size of snow particle and snow density according to the size of temperature. In the snow-falling stage, this algorithm introduced Level Of Detail (LOD) technology, imitated the movement effect according to the whereabouts of the snow particles moving force characteristics, took the force comprehensive consideration and simplified to reduce the computational complexity and improve the snow simulation authenticity.In the snow-accumulating stage, this method obtained the exposed surface of the scene model and its height field. And then based on a point coordinates and the point height in the field in a plane, it got the position of snow particles steadily to simulate the height change effect. This new method used the whole surface as ground-object emitter and superimposed the corresponding particle texture to improve authenticity.

Face feature extraction method based on graph

LIU Zhongbao

2013, 33(05):  1432-1455.  DOI: 10.3724/SP.J.1087.2013.01432

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Current feature extraction methods are mainly based on global or local features. In order to fully utilize all the sample information, this paper presented Face Feature Extraction based on Graph (FFEG). At the training stage, the optimal projection was computed by learning the training samples, which guaranteed the samples within classes were close and between classes were far away. At the recognition stage, the test samples were successively mapped onto the optimal projection, and then the nearest neighbor classifier was used for classification and recognition. The experimental results on ORL dataset prove the effectiveness of the proposed method.

Interactive segmentation algorithm optimized by multi-threshold with application in medical images

LAN Hong MIN Lequan

2013, 33(05):  1435-1475.  DOI: 10.3724/SP.J.1087.2013.01435

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Interactive image segmentation methods usually ask users to mark much more initial seeds or more than one interaction when they are used for medical image segmentation with fuzzy boundaries. This paper presented an optimized interactive image segmentation algorithm with multi-threshold technology. Based on GorwCut algorithm put forward by Vladimir, the optimized algorithm introduced image gray histogram with more than one threshold values to generate initial seeds template automatically and then used improved cellular automaton iterative algorithm to realize image segmentation. The algorithm simplified the user interactive operations and improved the segmentation accuracy. In applications, the algorithm was used to test on 100 plaque and liver image segmentations respectively, of which the results show that the optimized algorithm is of good performance.

3D scalp extraction and reconstruction of MRI brain images

MA AAmin YANG Rongqian NING Hai BAI Hongmin LI Lihua WU Xiaoming

2013, 33(05):  1439-1442.  DOI: 10.3724/SP.J.1087.2013.01439

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A new scalp extraction method for Magnetic Resonance Imaging (MRI) brain images in 3D was proposed for the requirements of image guided surgery on fast and accurate positioning in craniotomy. Firstly, anisotropic diffusion filtering was used to reduce noises, and the brain parenchyma image was got by the medical software of BrainSuite3. Afterwards, the brain parenchyma was removed and the threshold of scalp from non-brain-image was calculated. Thirdly, outside surface was extracted by mathematical morphology. Finally, combined with the gray value of scalp, the scalp was reconstructed by Marching Cube (MC) algorithm. The experiments show that this method can extract scalp effectively and the precision reaches sub-pixel's level by connecting threshold, mathematical morphology and MC algorithm.

Feather quill crease recognition based on local Radon transform

YUE Hongwei WANG Renhuang ZHANG Jinghua

2013, 33(05):  1443-1445.  DOI: 10.3724/SP.J.1087.2013.01443

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Concerning the recognition of feather quill crease feature, a new feature extraction method was proposed. In order to solve the scaling and translation sensitivity of Radon transform, an improved Radon transform was used to extract moment invariants of target region and local projection technology was adopted to eliminate interference physiological texture of feather quill. Obtaining invariants matrix by changing the scale factor, Singular Value Decomposition (SVD) was provided here to obtain feature invariant for classification and recognition. The results show that this suggested method has higher robustness and higher recognition rate compared with other algorithms.

Automated debug for common information model defect using natural language processing algorithm

XIANG Wei

2013, 33(05):  1446-1449.  DOI: 10.3724/SP.J.1087.2013.01446

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Common Information Model (CIM) is an open industrial standard, which has been implemented in products of many companies. Meanwhile, there are lots of bugs being reported and fixed. In order to reduce the cost time and effort of finding the root cause, in this paper, a method to debug automatically was proposed based on natural language processing algorithm. It firstly segmented those sentences using maximum entropy model, then used simHash to find the most similar fixed bug based on specifically constructed dictionary, finally used text mining to find the root cause and solution via analyzing the trace provided by customer. The experimental result achieves 87.5% accuracy, which shows its effectiveness.

Workflow customization technology for collaborative SaaS platform of industrial chains

CAO Shuai WANG Shuying LIU Shuya

2013, 33(05):  1450-1455.  DOI: 10.3724/SP.J.1087.2013.01450

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A workflow customization model for a collaborative Software-as-a-Service (SaaS) platform of industrial chains was proposed based on the mapping between workflow with operation and the custom relationship between the enterprise groups with workflow. A drive rule and a load and control mode of the workflow model were proposed to provide the dynamic load based on the identities of users. The proposed method was validated by the workflow customization on out application of the after service of automobile parts industrial chains, which showed that it met the needs of workflow customization on the collaborative SaaS platform of industrial chains.

Research and design of hadware and software fusion render layer for embedded browser

TANG Chengjian LEI Hang GUO Wensheng

2013, 33(05):  1456-1458.  DOI: 10.3724/SP.J.1087.2013.01456

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Widely used WebKit of excellent architecture has been ported to many embedded platforms, with excellent cross-platform features. Due to the diversity of hardware for embedded platforms, WebKit open source version does not take full advantage of the characteristics of embedded platforms. Through studying WebKit render architecture, taking full advantage of the embedded hardware feature and the benefit of the software rendering design, a hardware and software fusion render layer was designed. This layer sped up the browser rendering on the embedded platform and improved the user experience. The layer was verified, the time of opening website was reduced by 48% and the speed of rendering of html animation increased by 130% compared to the original WebKit.

Typical applications

Real-time error detection techniques based on FPGA

JU Xiaoming ZHANG Jiehao ZHANG Yizhong

2013, 33(05):  1459-1462.  DOI: 10.3724/SP.J.1087.2013.01459

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Real-time error detections are needed in highly reliable systems. This paper presented three online models with self-checking method for built-in error detection. The error detection model adopted two pipes in the Field Programmable Gate Array (FPGA). By comparing whether the current configuration information and FPGA configuration memory of the original information were consistent, the model can detect errors in real-time, and by comparing their configuration data, it also can locate the error where logic blocks have undergone an Single Event Upset (SEU). The testing result shows that the method proposed in this article has better performance than that of online Built-In Self-Test unit (BIST).

Automatic on-screen-display verification system based on Gabor features and BP neural network

XIANG Rong ZHOU Huijuan

2013, 33(05):  1463-1466.  DOI: 10.3724/SP.J.1087.2013.01463

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To deal with low efficiency and long-time consumption in verifying OSD (On-Screen-Display) of video devices, this paper devised an automatic OSD verification system. The system consisted of three parts. OSD area location was achieved by synthesizing statistical characteristics. Single character was then segmented based on improved Otsu algorithm. Finally, Gabor features and improved BP neural network were used to recognize these characters. The experimental results show that this system costs average 53ms per recognition of one frame with a recognition rate at 92.7%.

Design of mobile phone terminal of weather warning system based on C4.5 decision tree

TANG Huiqiang HANG Lina FAN Haijuan

2013, 33(05):  1467-1481.  DOI: 10.3724/SP.J.1087.2013.01467

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In order to meet the needs of modern society for weather forecast and early warning service, a real-time weather forecast and abnormal weather early warning system was researched and implemented in the Android system. Based on the decision tree algorithm of C4.5 algorithm, the warning classification problem was resolved. By means of extracting the attributes with maximum gain rate as the features of training sample, a decision tree was built. A model of decision tree was got by the pruning weather warning evaluation and analysis and application were made on this model. The experimental results show that this method has advantages in the assessment of classification accuracy, with correct classification rate up to 85.8%.

Anti-interference method based on TDOA residual error in MLAT system

LU Yu WU Honggang XU Zili

2013, 33(05):  1470-1488.  DOI: 10.3724/SP.J.1087.2013.01470

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In view of the fact that Multilateration (MLAT) technique locates the target according to the Time Difference Of Arrival (TDOA) from target to each station and the fact that the precision of clock in each station is crucial to the precision of target locating, an anti-interference method based on the residual error of TDOA was proposed. It estimated the clock precision of each station by the residual error, and archived the goal of the optimal stations selection and the locating precision improvement. The experimental results based on both simulation and practical data illustrate the proposed method can significantly enhance the locating precision, not only feasible but also effective.

Dynamic demodulation of fiber Bragg grating sensing based on LabVIEW

HU Liaolin ZHANG Weichao HUA Dengxin WANG Li DI Huige

2013, 33(05):  1473-1475.  DOI: 10.3724/SP.J.1087.2013.01473

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A dynamic Fiber Bragg Grating(FBG) sensing demodulation system was designed by using tunable optical filter based on LabVIEW. With the use of Visual Instrument (VI) program of LabVIEW software, tunable filter was controlled by a computer through hardware interface to scan the fixed wavelength range. Photoelectric signal was collected by acquisition circuits and sent to the computer to be analyzed, so reflection wavelength and FBG's strain could be obtained. Results of dynamic sensing demodulation experiments were identical with the results from spectrum analyzer, which has verified the correctness and feasibility of the designed scheme.

Track correlation algorithm based on modified Kohonen neural network

FANG Hao WANG Yanhong

2013, 33(05):  1476-1480.  DOI: 10.3724/SP.J.1087.2013.01476

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There are several difficulties must be overcome to develop a track-to-track association algorithm in a distributed multi-sensor situation. For example, it might get errors and omissions related track when there are cross or bifurcation in the target moving patch. Besides, the computation might grow rapidly with the increasing of the number of sensors and target. In order to resolve these problems, a modified Kohonen neural network based correlation algorithm was presented. The algorithm was made up of four main modules, including clustering association, target state estimation, neurons optimization, and state fusion estimation. The suitable thresholds for each layer of the competition element in the neural network were set to avoid the phenomenon of necrotic neurons occurred in the conventional method due to inappropriate choice of initial weights. The learning rules were also designed for the clustering of multi-sensor measurement data in a self-organizing manner. Besides, data clustering association on continuous-time data were used to achieve moving target track correlation. The simulation results demonstrate the efficiency and effectiveness of the proposed algorithm.

Optimization algorithm for I-V curve fitting of solar cell

HU Keman HU Haiyan LIU Guiguo

2013, 33(05):  1481-1484.  DOI: 10.3724/SP.J.1087.2013.01481

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A new optimization algorithm, GA-AFSA, was proposed by integrating Genetic Algorithm (GA) and Artificial Fish Swarm Algorithm (AFSA) to fit for the mathematic model of I-V curve of solar cell. It maintained the global optimization advantages of GA and quick convergence of AFSA while overcoming the defects of GA's slow convergence and AFSA's stepping without a definite purpose. By fitting the five important parameters of I-V curve, namely the photo-generated current of solar cell, quality factor of diode, series resistance, reverse saturation current and shunt resistance, GA-AFSA made a great improvement. Compared with the existing algorithm, the new one has a higher precision and a rapid convergence speed.

Development of MPC8247 embedded Linux system based on device tree

ZHANG Maotian ZHANG Lei GUO Xiao SUN Jun

2013, 33(05):  1485-1488.  DOI: 10.3724/SP.J.1087.2013.01485

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Concerning the MPC8247 target system based on PowerPC, the device tree was discussed and an embedded Linux system was developed, including the transplant and deployment of U-Boot, Linux kernel, Device Tree Blob (DTB) and Ramdisk file system. The actual operation of the system shows that the device tree file is correct, and the system design is rational and efficient.