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Table of Content

    01 October 2013, Volume 33 Issue 10
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    Network and communications
    Key technologies and application evolution of Internet of things
    XUE Xiaoping WANG Qian ZHANG Fang
    2013, 33(10):  2701-2706. 
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    The concept and architecture of the Internet of Things (IoT) were introduced. Key characteristics and technologies, which included the ubiquity of the IoT, intelligent identification and sensing technologies, uncertainty of data, representation methods of data, information propagation towards massive data, security and privacy were discussed in detail, and related open issues were presented. Based on the future ubiquitous applications, the research directions of the IoT were put forward.
    Fast handover mechanism based on Delaunay triangulation for FMIPv6
    LI Zhenjun LIU Xing
    2013, 33(10):  2707-2710. 
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    To solve the packet loss problem caused by inaccurate prediction of New Access Router (NAR) in the Fast Handover for mobile IPv6 (FMIPv6), this paper proposed a triangulationbased fast handoff mechanism (TFMIPv6). In TFMIPv6, a triangulation algorithm was used to split the network into virtual triangle topology, and the tunnel was established among adjacent access routers. The candidate target Access Points (AP) were selected to quickly recalculate the new relay addresses for the mobile nodes, and packets were buffered in two potential NARs during handover. The experimental results illustrate that TFMIPv6 protocol achieves lower handoff latency and packet loss rate compared with FMIPv6.
    Indoor localization algorithm based on threshold classification and signal strength weighting
    YANG Xiaoliang YE Ayong LING Yuanjing
    2013, 33(10):  2711-2714. 
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    In order to eliminate the influence caused by fluctuation of Received Signal Strength Indicator (RSSI) and unreliability of individual beacon nodes in complex indoor environment, an indoor localization algorithm based on threshold classification and signal strength weighting was proposed. First, the reference points were classified and corresponding thresholds were determined according to the characteristics of indoor pathloss, then the received signal strength was used as reference weight to locate. The experimental results show that this algorithm can effectively reduce the error caused by RSSI random jitter, weaken the influence of individual beacon nodes which are disturbed, and improve localization accuracy.
    Dynamic opportunistic cooperative strategy with log likelihood ratio switching threshold
    CHENG Yulun YANG Longxiang
    2013, 33(10):  2715-2718. 
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    Error propagation seriously degenerates the selection diversity of decode-and-forward-based opportunistic cooperative system. Addressing this problem, a Log Likelihood Ratio (LLR)-based adaptive switching scheme was proposed, which aimed at exploiting relay channel more efficiently through dynamic cooperation selection according to the LLR comparison with Bit Error Ratio (BER)-based threshold at relay. Moreover, the closed-form expression of the average BER was derived, and the threshold was optimized accordingly. Monte-Carlo simulations validate the analysis, and the results show that the proposed algorithm achieves 1.2dB power gain at BER of 0.001, compared to the conventional scheme.
    Multi-source to single-sink routing algorithm based on data query for wireless sensor network
    LU Xianling WANG Yingying WANG Hongbin XU aoguo
    2013, 33(10):  2719-2722. 
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    A multisource to singlesink routing algorithm based on data query for wireless sensor network was proposed to resolve the problem of huge energy consumption and the redundant links at path reinforcement stage in directed diffusion. Clustering was used to reduce the energy consumption of plane flooding, and the next hop nodes were selected based on the priorities of the neighbor nodes to build the routes from multisource to singlesink and fuse data at the intersection of the routies. The simulation results show that the algorithm can balance the energy consumption, improve the energy efficiency, reduce the number of packets, and prolong the network lifetime.
    Improved backoff mechanism for IEEE 802.15.4 MAC protocol
    QIAO Guanhua MAO Jianlin GUO Ning CHEN Bo DAI Ning ZHANG Chuanlong
    2013, 33(10):  2723-2725. 
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    Concerning the impact on network performance of the mobile nodes and the constantly changing data transmission rate, the authors proposed a new backoff scheme for IEEE802.15.4, which used Probability Judgment based on Network Load and Exponentially Weighted Moving Average (PJNL_EWMA) method. According to a realtime monitoring of current network status by probability judgment of network load, this method dynamically adjusted backoff exponent by EWMA when Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) began. Compared with the IEEE802.15.4 standard protocol and MBS (Memorized Backoff Scheme)+EWMA algorithm, the simulation experiments on NS2 platform show that the PJNL_EWMA algorithm not only improves the throughput of the network, but also reduces the packet loss rate and the collision ratio, significantly improving the network performance.
    Fast networking media access control for random access based mobile wireless sensor networks
    HUANG Liang WANG Fuyue MA Chao YANG Han
    2013, 33(10):  2726-2729. 
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    This paper researched the fast networking Media Access Control (MAC) of mobile sensor networks based on unslotted CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) random access algorithm. This paper analyzed and optimized the networking process by preassigning the channels, simplified the association process using direct transmission instead of indirect transmission, and improved the CSMA/CA mechanism in order to reduce the collision. The simulation and field test results show that the proposed method can reduce the collision and the networking time effectively compared with the IEEE 802.15.4 protocol.
    Algorithm of optimal surface deployment in wireless sensor networks
    LI Yingfang YAN Li YANG Bo
    2013, 33(10):  2730-2733. 
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    Node deployment is a basic problem in sensor networks, which directly relates to the performance of the entire network. Most existing researches on sensor network node deployment are for the case of twodimensional planar and three dimensions space, but very few researches for threedimensional surface deployment scenario. This paper proposed an algorithm of optimal surface deployment in wireless sensor networks. First by mathematical or differential geometry method for threedimensional surface it constructed mathematical model, and then through the centroid of the threedimensional surface Voronoi subdivision partitions, an error function was proposed to evaluate the superiority of deployment method. Finally compared with other surface deployment methods, the performance of the proposed algorithm in this paper is superior.
    P2P traffic identification method based on K-means and twin support vector machine
    GUO Wei WANG Xichuang XIAO Zhenjiu
    2013, 33(10):  2734-2738. 
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    Most of the P2P traffic identification methods have the problem of high time cost. Therefore, it was proposed to use TWin Support Vector Machine (TWSVM) whose time cost was a quarter of the common Support Vector Machine (SVM) to build classifier. Kmeans ensemble was used to create labeled sample set and labeled sample set was combined as the training sample of the TWSVM. At last, the constructed classification model was used to identify P2P traffic. The experimental results show that the method based on Kmeans and TWSVM can significantly decrease time cost of the P2P traffic identification, and has a higher accuracy rate and better stability than the standard SVM.
    Demodulation algorithm design of VHF data broadcast signal
    ZHANG Kunfeng GUO Ying ZHANG Guoxiang ZHAO Yang
    2013, 33(10):  2739-2741. 
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    In order to enhance the performance of the synchronization and demodulation, a Very high frequency (VHF) Data Broadcast (VDB) signal demodulation algorithm based on the solution of differential equation was proposed. This algorithm eliminated the synchronization performance deterioration caused by the frequency offset. And frame synchronization, bit synchronization, frequency offset estimation and correction could be completed within a single set of synchronization symbols. The simulation results show that the method is effective to enhance the VDB signal demodulation performance.
    Calculation method and performance evaluation for network survivability
    ZHAO Pan WEI Zhengxi ZHANG Hong
    2013, 33(10):  2742-2745. 
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    In order to mitigate the network congestion by link failures, a new survivability evaluation method named SASFL 〖BP(〗(Survivability Algorithm based on Shuffled Frog Leaping, )〖BP)〗 was proposed by shuffled frog leaping algorithm and wavelet technology. In this method, the evaluation index of survivability was presented at first, and wavelet transform was used to decompose the arrivel flow in failures state. Then, the optimization wavelet coefficients with shuffled frog leaping was reconstructed to network remained traffic. Finally, simulation was conducted to study the relationship between network survivability and failures link, as well as weight factor with OPNET and Matlab. Compared with the other methods, SASFL algorithm has better adaptability.
    Estimation mothod of the figure of merit in Ultra-wideband radio channel
    LI Juan ZHANG Hao CUI Xuerong WU Chunlei
    2013, 33(10):  2746-2749. 
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    UWB (UltraWideBand) technology is considered to be the most suitable for indoor wireless location and IEEE802.15.4a is the first radio ranging and positioning physical layer IEEE standard. In order to let the sender know the quality of the ranging, FoM (Figure of Merit) is added in this protocol, but how to produce FoM is not given. On the basis of analyzing the statistical characteristics of the received signal energy block, a method based on the joint parameters of skewness and the maximum slope was proposed to estimate the FoM in UWB radio channel. The simulation finds that this method can provide reference for accurate ranging and positioning, and can improve the ranging accuracy about 30% in the CM1(Channel Model) channel.
    Environment-aware multiple-path routing algorithm
    LIN Pei HU Jianjun
    2013, 33(10):  2750-2752. 
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    Cognitive network can improve the end-to-end performance of the network, and ensure QoS(Quality of Service) requirements. The existing routing algorithm does not have cognitive ability. To solve this problem, a multi-path routing algorithm of cognitiveload balancing was proposed, which combined the advantages of Q-learning algorithm and ant algorithm, to establish and maintain the route through ant algorithm, and to achieve congestion avoidance and load balancing by Q-learning algorithm. The simulation contrast with OPNET shows that the algorithm is valid and effective at controlling packet loss ratio, delay and bandwidth utilization.
    Microblog fans network evolving model based on user social characteristics and attractiveness of behavior properties
    WANG jing ZHU Ke WANG Binqiang
    2013, 33(10):  2753-2756. 
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    According to the research into how the users social characteristics and behavior properties influence the microblog fans network evolving, a new microblog fans network evolving model based on the attractive factor called SBPAF was proposed. The attractive factor for social characteristics and the attractive factor for behavior properties were defined. The nodes create new edges according to attractive factor preferential attachment principle and the two-step attachment principle. Besides, the dying out of the edges was also considered. The parameter in the model can be adjusted flexibly so that different microblog fans networks can be simulated. Finally, the mathematical analysis and computational experiments verify that SBPAF model is reasonable and available.
    High-order distributed consensus algorithm under directed communication topology
    PENG Huanxin QI Guoqing SHENG Andong
    2013, 33(10):  2757-2761. 
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    In order to improve the convergence rate of distributed consensus algorithms under directed communication topologies, a high-order distributed consensus algorithm was proposed. Under directed topologies, the previous state values of two-hop adjacency nodes were utilized to improve the convergence rate based on single-hop communication. The performance and convergence rate of the high-order distributed consensus algorithm were analyzed under directed networks. The simulation results were provided to verify these analytical results. The results show that an average consensus can be reached under certain conditions, the convergence rate of the high-order algorithm is superior to the other algorithms utilizing the information of two-hop adjacency nodes, but the high-order algorithm can tolerate smaller communication time-delays than the other algorithms utilizing the information of two-hop adjacency nodes.
    Improved blind recognition method for binary cyclic code
    ZHU Lianxiang LI Li
    2013, 33(10):  2762-2764. 
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    The existing blind recoginition methods of cyclic code have poor effects in the high or only Bit Error Ratio (BER) better in low code rate conditions, or the method is only for a subclass of the cyclic codes. In order to solve the blind identification for cyclic code with high BER or high code rate effectively, a method based on code weight distribution and matrix transformation was proposed. First of all the article structured the receiving sequence to matrix according to the estimated code length, and then realized the blind recognition using the improved weight distribution distance formula. The simulation results show that the method can realize the blind recognition for cyclic code with high BER and high code rate, and the results are better.
    Algorithm for modulation recognition based on cumulants in Rayleigh channel
    ZHU Hongbo ZHANG Tianqi WANG Zhichao LI Junwei
    2013, 33(10):  2765-2768. 
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    Concerning the problem of modulation identification in the Rayleigh channel, a new algorithm based on cumulants was proposed. The method was efficient and could easily classify seven kinds of signals of BPSK (Binary Phase Shift Keying), QPSK (Quadrature Phase Shift Keying), 4ASK (4-ary Amplitude Shift Keying), 16QAM (16-ary Quadrature Amplitude Modulation), 32QAM (32-ary Quadrature Amplitude Modulation), 64QAM (64-ary Quadrature Amplitude Modulation) and OFDM (Orthogonal Frequency Division Multiplexing) by using the decision tree classifier and the feature parameters that were extracted from combination of four-order cumulant and six-order cumulant. Through theoretical derivation and analysis, the algorithm is insensitive to Rayleigh fading and AWGN (Additive White Gaussian Noise). The computer simulation results show that the successful rates are over 90% when SNR (Signal-to-Noise Ratio) is higher than 4dB in Rayleigh channel, which demonstrates the feasibility and effectiveness of the proposed algorithm.
    High-sensitive GPS signal acquisition method based on wavelet filtering
    LI Yanmin YI Qingming SHI Min
    2013, 33(10):  2769-2771. 
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    With regard to the low operation efficiency of Global Positioning System (GPS) weak signal high-sensitive acquisition algorithm, a new acquisition method applying wavelet transform and synchronized data blocks accumulation was proposed. The sampled Intermediate Frequency (IF) signal was processed using discrete wavelet transform and Signal-to-Noise Ratio (SNR) was improved by the different characteristics of useful signal and noise during wavelet transform. Meanwhile the quantity of baseband data was decreased. Frequency compensation and synchronized data blocks accumulation method were adopted to reduce the Doppler search range and improve SNR effectively. The simulation results show that compared with traditional high-sensitive acquisition method, the proposed method can obviously reduce the acquisition time and improve the performance of weak signal acquisition.
    Advanced computing
    Virtual machine placement and optimization for data center
    WANG Jiajing ZENG Hui HE Tengjiao ZHANG Na
    2013, 33(10):  2772-2777. 
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    Dynamic consolidation of Virtual Machine (VM) is a promising solution to address the energy inefficiency of data centers. This paper focused on VM placement and its optimization. First, in order to improve the energy efficiency, a CPU utilization-based best fit decreasing algorithm was presented to complete the VM placement. However, due to the variability of workloads experienced by applications, the VM placement should be optimized continuously in an online manner. Therefore, a threshold-based active VM migration mechanism was proposed to solve the dynamic optimization. Extensive simulation results show the proposed algorithms can significantly reduce the energy consumption and the number of VM migrations, while keeping the metrics of Performance Degradation due to Migration (PDM) and Overload Time per Active Server (OTAS) in low level.
    Key technology of cloud simulation for distributed virtual maintenance training system
    ZHU Dongfang SU Qunxing LIU Pengyuan
    2013, 33(10):  2778-2782. 
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    It is tightly coupled between the simulation task and equipment in traditional distributed virtual maintenance training systems, so the system simulation running is inefficient and difficult to expand. In addition, the simulation resource sharing and maintenance cooperation is also a big problem. In order to solve these problems, the infrastructure and realizing framework of cloud simulation were put forward for the application in weapons virtual maintenance training field. The multilayer infrastructure of Run Time Infrastructure (RTI) component was studied. The key techniques were settled, such as federated members excogitation and transport, simulation process monitoring, simulation visualization and distributed storage. The virtual maintenance system was developed based on cloud simulation technologies, which indicated that cloud simulation was feasible and effective.
    Parallelization and optimization of alternating direction implicit CFD solver on GPU
    Liang DENG XU Chuanfu LIU Wei ZHANG Lilun
    2013, 33(10):  2783-2786. 
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    Alternating Direction Implicit (ADI) scheme is a typical discretization scheme for solving partial differential equations. However, there are few researches on the implementations and optimizations of ADI scheme on GPUs for practical Computational Fluid Dynamics (CFD) applications. In this paper, through analysis of the characteristics and calculation processes of ADI solver in a practical CFD application, the authors implemented fine-grained GPU parallelization algorithm for the ADI solver based on grid points and grid lines by a Compute Unified Device Architecture (CUDA) model. Some performance optimization methods were discussed. The experimental results on the TianHe-1A supercomputer show that the proposed GPU-enabled ADI solver can achieve overall speedup of 17.3 compared to single CPU core when simulating a 128×128×128 grid. The speedups for inviscid flux calculation, viscous flux calculation and ADI iteration are 100.1, 40.1 and 10.3 respectively.
    On-line energy-aware scheduling algorithm in multiprocessor system
    ZHANG Binlian XU Hongzhi
    2013, 33(10):  2787-2791. 
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    With the enhancement of computing performance in multiprocessor systems, the management of energy consumption becomes more important, and how to meet real-time constraints and effectively reduce energy consumption in the real-time scheduling is also a key issue. Based on multiprocessor computing systems, concerning randomly arrived task, On-Line Energy-Aware Scheduling Algorithm (OLEAS) was proposed. The algorithm meeting the task deadlines under the premise possibly puts the task scheduler on the least energy consumption producing processor. When a task on all the processors could not meet the deadline requirements, the part of the task between the processors shall be adjusted possibly to meet the deadline requirements. Meanwhile, OLEAS was in a bid to execute the task on a single processor according to the average voltage/frequency, thus reducing the energy consumption. When the new task did not meet the deadline requirements, the former voltage/frequency of unexecuted tasks should be one by one adjusted higher. Compared with the performance of EFF (Earliest Finish First), HVEA (Highest Voltage Energy-Aware), LVEA (Lowest Voltage Energy-Aware), MEG (Minimum Energy Greedy) and ME-MC (Minimum Energy Minimum Completion time) in simulated experiments, the final result shows OLEAS owns obviously comprehensive advantage in the aspect of meeting task deadlines and energy consumption saving.
    Nutch crawling optimization from view of Hadoop
    ZHOU Shilong CHEN Xingshu LUO Yonggang
    2013, 33(10):  2792-2795. 
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    Nutch crawling performance was optimized by tunning Nutch MapReduce job configurations. In order to optimize Nutch performance, firstly Nutch crawling processes were studied from the view of Hadoop. And based on that, the characters of Nutch jobs workflows were analyzed in detail. Then tunned job configurations were generated by profiling Nutch crawling process. The tunned configurations were set before the next job running of the same type. The appropriate profiling interval was selected to consider the balance between cluster environmental error and profiling load, which improved optimization result. The experimental results show that it is indeed more efficient than the original programs by 5% to 14%. The interval value of 5 makes the best optimization result.
    Artificial intelligence
    Deductive method of association rules among compatible datasets based on Apriori
    ZHANG Chunsheng ZHUANG Liyan
    2013, 33(10):  2796-2800. 
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    Data mining algorithm based on Apriori of association rules mines data only for a class of correlated datasets. However, various datasets are very large in the real world, and how to mine data among uncorrelated datasets and how to expand the number of rules are the challenging issues. The study of Apriori algorithm of association rules basically focus on the performance optimization of algorithm and different data forms at present, which does not breakthrough the limit of the uncorrelated datasets. For this, the concepts of correlated datasets, uncorrelated datasets and compatible datasets were given in the paper, furthermore a deductive method of association rules among uncorrelated datasets based on Apriori was given in this paper, and in which deductive rules of the algorithm were given. The correctness of the algorithm was proved by construction method, and the application method was demonstrated by examples. The algorithm can realize rules deduction among correlated rules based on Apriori for uncorrelated datasets, which cannot be realized by common data mining algorithms. The algorithm expands the application field of correlated rules algorithm; meanwhile, it realizes the privacy protection in a certain extent because the rules are mined independently out on the basis of compatible datasets and have not shared original data.
    Large-scale data classification based on hierarchical clustering and re-sampling
    ZHANG Yong FU Panpan ZHANG Yuting
    2013, 33(10):  2801-2803. 
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    Based on hierarchical clustering and re-sampling, this paper presented a Support Vector Machine (SVM) classification method for large-scale data, which combined supervised learning with unsupervised learning. The proposed method first used k-means cluster analytical technology to partition dataset into several subsets. Then, the method clustered class by class for each subset and selected samples in each clustering center neighborhood to form candidate training datasets. Last, the method applied SVM to train and model for candidate training datasets. The experimental results show that the proposed method can substantially reduce SVM learning cost. Meanwhile, the proposed method has better classification accuracy than random re-sampling method, and can attain about the same classification accuracy of the non-sampling method.
    Personal recommendation based on cloud model and user clustering
    LI Kechao LING Xiaoe
    2013, 33(10):  2804-2806. 
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    In order to solve the problem of lack of co-rated users caused by data sparseness and similarity calculation method, the authors, by making use of the advantage of cloud model transformation between qualitative concept and quantitative numerical value, proposed an improved personal recommendation algorithm based on cloud model and users clustering. The users’ preference on the evaluation of item attribute was transformed to preference on digital characteristics represented by integrated cloud model. By using the improved clustering algorithm, the authors clustered the rating data and the standardized original user attribute information, and at the same time, by taking into account the changes of the users’ interests, recommended the neighbor users’ union generated by similarity based on integrated cloud model of items attributes evaluation between users, clustering of users for item rating, and clustering of user attributes these three methods. The theoretical analysis and experimental results show that the proposed improved algorithm can not only solve the problem of lack of co-rated users caused by data sparseness, but also obtain satisfactory mean absolute error and root-mean-square error even when the users are new. Theoretical analysis and experimental results show that the proposed improved algorithm can not only solve the problem of lack of co-rated users caused by sparseness data, but also obtain satisfactory mean absolute error and root-mean-square error even when the users are new.
    Dynamic model combining with time facter for event tracking
    XU Jianmin SUN Xiaolei WU Guifang
    2013, 33(10):  2807-2810. 
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    Concerning the Internet news tracking, the study put forward a dynamic model for event tracking with reference to the time information. The dynamic model introduced the time factor into the traditional vector model to get the time similarity of the same characteristic words between the document and the event,and then applied the time similarity to calculate the similarity of the document and the event.If a document was related to the event,the new characteristic words in the document would be added to the event term set,and the weight and time information of characteristic words in the event term set should be re-adjusted. The experiment was evaluated by Detection Error Tradeoff (DET), and the results show that the dynamic model for event tracking improves the system performance effectively, and its minimum normalized cost of tracking loss is reduced by about 9%.
    Multi-source irrigation information fusion method based on fuzzy rough set and D-S evidence theory
    CHEN Zhifang WANG Jinglei SUN Jingsheng LIU Zhugui SONG Ni GAO Yang
    2013, 33(10):  2811-2814. 
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    Concerning the problem that uncertainty information is difficult to be merged during the decision-making process of multi-source irrigation information, a decision fusion method based on fuzzy rough set and Dempster-Shafer (D-S) evidence theory was proposed. Using the fuzzy rough set theory,the basic probability distribution function was established, the interdependence between irrigation factors and irrigation decision was calculated, and the identification framework of irrigation decision on the multiple fusion irrigation factors was built. Using the improved D-S evidence theory, the multi-source irrigation information was fused at the decision-making level, the expression and synthesis problems of uncertain information were solved. The information of winter wheat such as soil moisture, photosynthetic rate and stomatal conductance in north China was fused in irrigation decision by the application of the methods mentioned above. The results show that the uncertainty of the irrigation decision decreases from 38.0% before fusion to 9.84%. The method can effectively improve the accuracy of irrigation decision and reduce the uncertainty of the irrigation decision.
    Improved QPSO algorithm based on random evaluation and its parameter control
    WU Tao YAN Yusong CHEN Xi
    2013, 33(10):  2815-2818. 
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    In order to improve the convergence performance of Quantum-behaved Particle Swarm Optimization (QPSO) algorithm, this paper proposed an improved QPSO algorithm which was called RE-QPSO based on the random evaluation strategy. The new algorithm evaluated the innovation of particles by using a random factor and improved the ability of the particles to get rid of the local optima. Fixed value strategy and linear decreasing strategy were proposed for controling the theunique parameter of QPSO algorithm and they were tested on six benchmark functions. According to the test results, some conclusions concerning the selection of the parameter were drawn.
    New stochastic search algorithm for grey nonlinear programming problems
    ZHOU Weiping LIU Bingbing
    2013, 33(10):  2819-2821. 
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    In this paper, the grey constrained nonlinear programming problems were investigated. With the help of mean, this paper firstly transformed the original grey optimization problem into a determinate constrained nonlinear programming problem. Then, based on the estimation of distribution algorithm, a stochastic search method was developed to solve the determinate constrained nonlinear programming problem. The key technique of the proposed method was explained in detail and the steps of the proposed method were described concretely. Finally, the elementary numerical examples show the proposed stochastic search method is feasible and effective.
    Application of ant colony optimization to logistics vehicle dispatching system
    LI Xiujuan YANG Yue JIANG Jinye JIANG Liming
    2013, 33(10):  2822-2826. 
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    The thorough research on ant colony algorithm points out that the ant colony algorithm has superiority in solving large nonlinear optimization problem. Through careful analysis of the deficiencies that genetic algorithm and particle swarm algorithm solve the problem of vehicle dispatching system, based on the advantage of ant colony algorithm and the own characteristics of vehicle dispatching system, the basic ant colony algorithm was improved in the paper, and the algorithm framework was created. Based on the linear programming theory, the article established mathematical model and operation objectives and constraints for vehicle dispatching system, and got the optimal solution of vehicle dispatching system problem with the improved ant colony algorithm. According to the optimal solution and the dispatching criterion real-time scheduling was achieved. The article used Java language to write a simulation program for comparing the improved particle swarm optimization algorithm and ant colony algorithm. Through the comparison, it is found a result that the improved ant colony algorithm is correct and effective to solve the vehicle dispatching optimization problem.
    Parameter correction of simulation model based on data mining
    ZHAO Yiding LI Zhimin WANG Hongli LIU Weiguang CHU Jizheng
    2013, 33(10):  2827-2831. 
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    Concerning the difficulties of parameter estimation for industrial modeling in practice, an innovative approach through data mining to correct parameter of model was proposed. Mining data from a large number of actual data accumulated in production process could be used for correcting parameter through statistical method. The improved method of least square was used for industrial data which contained noise. In view of the characteristics of industrial data, such as incompletion and common distribution, parameter should be segmented and combined to be corrected. For dynamic compensation of statistical model, dynamic parameter can be estimated through data mining of historical dynamic process. Parameter correction and data mining should be interactive with each other. To reduce the scope of massive data mining and improve sufficiency of sample data required for parameter correction, the network model of co-ordination was designed. It is shown in actual cases that this method is efficient and practical. The accuracy of simulation can be greatly improved through this method.
    Information security
    Attribute-based encryption and re-encryption key management in cloud computing
    LUO Wenjun XU Min
    2013, 33(10):  2832-2834. 
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    The security problem of the data stored in the cloud is a challenge for cloud computing. Encryption is the main method to solve the problem of data storage security in cloud computing. The confidentiality issue of the encryption is the key management. The attribute-based encryption and re-encryption scheme in cloud computing was proposed. It combined attribute-based encryption and re-encryption technology. The cloud server could re-encrypt for different users, and re-encrypt for a group of users at a time. Thereby the scheme reduced the number of re-encryption keys. The data owner could generate and send the keys of re-encryption for a group of users and the data requester could use the key corresponding to the attribute set to decrypt the data of several data owners, which reduced the amount of keys’ transmission. The scheme reduced the difficulty of key management and improved the efficiency of the scheme. In the end, the security and efficiency of the scheme were discussed.
    Application and improvement of key agreement protocol in could computation environment
    REN Min
    2013, 33(10):  2835-2837. 
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    By analyzing security requirement of key agreement in cloud computation environment and the defect of security performance for IKEv2, an improved key agreement protocol IKE-C was proposed in order to solve the problem of adaptability of the existing key agreement protocols in cloud computation environment. Puzzle, key material and delaying the transmission of ID were adopted in order to promote the ability of anti-DoS (Denial of Service) attack and overcome the problem that sender identity would be leaked because of man-in-the-middle attack. Performance comparison was conducted in the paper. The simulation result indicates that IKE-C gets shorter convergence time than IKEv2 with the same network scale, and performance superiority is more obvious as clients are increasing.
    Traffic behavior feature based DoS&DDoS attack detection and abnormal flow identification for backbone networks
    ZHOU Yingjie JIAO Chengbo CHEN Huinan MA Li HU Guangmin
    2013, 33(10):  2838-2841. 
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    The existing methods for backbone networks only analyze coarse-grained network traffic characteristic parameters. Thus, they cannot guarantee both the premise of abnormal flow identification and the real-time detection for DoS (Denial of Service) & DDoS (Distributed Denial of Service, DDoS) attacks. Concerning this problem, a DoS&DDoS attack detection and abnormal flow identification method for backbone networks was proposed. First, it analyzed coarse-grained network traffic characteristic parameters to determine the time points that abnormal behaviors occur; then, fine-grained traffic behavior characteristic parameters were analyzed in these time points to find the destination IP addresses that correspond to abnormal behaviors; finally, comprehensive analysis was conducted for extracted traffic that correspond to abnormal behaviors to determine DoS and DDoS attacks. The simulation results show that, the proposed method can effectively detect DoS attacks and DDoS attacks in backbone networks. Meanwhile, it could accurately identify the abnormal traffic, while real-time detection is ensured.
    Design and implementation of real-time network risk control system based on antibody concentration
    GAO Zhiqiang HU Xiaoqing
    2013, 33(10):  2842-2845. 
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    The system adopted artificial immune theory. Through analyzing the detection results of the traditional real-time intrusion detection system Snort, and according to the characteristic that antibody concentration dynamically changes with the network intrusion intensity, the current risk value of network was calculated to reflect all kinds of attacks and overall risk profile. Snort relies on the rule matching to detect data packets. The detection process does not take into account the current network risk, resulting in the problem of high false positives rate. This system set pass threshold and dropped threshold based on different degree of attack danger to reduce the false alarm rate of Snort, and took “pass, alarm, discard packet, etc.” as response measures according to the risk value. The experimental results show that the system can calculate the real-time risk faced by the host and network accurately, reduce the false positive rate and take response measures according to risk value effectively.
    Network anomaly detection method based on principle component analysis and tabu search and decision tree classification
    YE Xiaolong LAN Julong GUO Tong
    2013, 33(10):  2846-2850. 
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    Real network traffic contains mass of features, and the method of anomaly detection based on feature analysis is not suitable for high-dimensional features classification. A method based on Principal Component Analysis and tabu Tabu Search (PCA-TS) decision tree classification for anomaly detection was proposed. The method reduced high-dimensional features and selected optimal feature subset which was suitable for classification through PCA-TS algorithm, then the decision tree of higher detection rate and lower false rate was used for classification and detection based on semi-supervised learning. The experiment shows that the approach has higher detection accuracy and lower false rate compared with traditional anomaly detection method, and the detection performance is less affected by sample size and is suitable for real-time detection of unknown anomalies.
    Regroup-based semi-distributed botnet anti-strike technology
    ZHU Junhu LI Heshuai WANG Qingxian QIU Han
    2013, 33(10):  2851-2853. 
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    The newly developed botnet defense technologies pose a severe challenge to botnet survivability. In order to improve the survivability of the botnet, from an attackers perspective, this article proposed a new anti-strike mechanism based on regroup, which was suitable for semi-distributed botnet. In the case that semi-distributed botnet suffered a severe blow, which caused topology broken, this mechanism could perceive the state of botnet, detect survival nodes, recover survival node and reassemble them into a new botnet. The experiments verify the effectiveness of the mechanism to effectively enhance the survivability of the semi-distributed botnet.
    Safe and efficient remote attestation protocol based on bilinear pairings signcryption
    HE Long PENG Xinguang
    2013, 33(10):  2854-2857. 
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    In order to deal with the poor security and low efficiency in remote attestation, a module-level safe and efficient property attestation protocol was proposed. In the protocol, the signcryption was used to build the module property signature, which could reduce the time of building property certificate. And the signcryption scheme based on the bilinear pairings over elliptic curves also enhanced the security of property certificate. Finally, a model instance was presented to verify the feasibility of the protocol. The experiments show that the program can quickly generate the module property signature and improves the efficiency of the remote attestation.
    Design and implementation of configuration automatic system for computer core
    LI Xinyou XU Tao LIU Bei
    2013, 33(10):  2858-2860. 
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    The Computer Core Configuration (CCC) becomes one of the important means to improve the security of Internet computers, which has been brought under the spotlight in the field of information security. Based on the concept and the method of core configuration, an automatic way to implement CCC by Agent was described, a system composed of integrated functions such as configuration editing, verifying, dispatching and executing, and compliance monitoring was developed, which was suitable for organization to protect their computers against attack.
    Encryption algorithm for QR code based on Ising model
    ZHOU Qing HUANG Dangzhi
    2013, 33(10):  2861-2864. 
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    There is a potential security risk in the communication process by using QR (Quick Response) code. This paper, therefore, proposed an encryption algorithm. Ising model has a matrix form, in which it is same with QR code, and its process of state change supports parallel operation. An encryption matrix was generated according to the model’s change rule, and then the ciphertext of QR code was produced, using the matrix and combining coding theory of the code. It was proven by the experiments that the algorithm did well in terms of randomness and sensitivity of key. With its simplicity, security and high efficiency, it could be applied to the secure communication for QR code.
    Nonlinear image encryption algorithm based on random fractional Mellin transform
    ZHANG Wenquan ZHANG Ye ZHOU Nanrun
    2013, 33(10):  2865-2867. 
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    A nonlinear image encryption algorithm based on random Fractional Mellin Fransform (FrMT) was proposed to get rid of the potential insecurity problem of the linear encryption system. The random FrMT was constructed by combining log-polar transformation with random Fractional Fourier Fransform (FrFT), and a real-valued symmetrical random matrix was generated by Linear Congruential Generator (LCG) in randomizing process. The real value input image was encrypted by random FrMT which made the encryption be nonlinear, and the output ciphertext of the FrMT was also real-valued, which was convenient for storage and transmission. The encryption algorithm had three keys that were the parameters of LCG. Compared with FrMT, the fractional order key of random FrMT was more sensitive. The numerical simulation results demonstrate that the encryption algorithm is against common attacks, and sensitive to keys with good security.
    Universal steganalysis for RGB images based on color gradient matrix
    QI Ke XIE Dongqing
    2013, 33(10):  2868-2870. 
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    A steganalysis algorithm for RGB images based on color gradient matrix was proposed in this paper. The algorithm was constructed with color gradient matrix of the RGB image, and 16-dimensional statistical features, including gradient asymmetry, gradient energy, gradient mean, gradient variance, gradient entropy and so on. Support Vector Machine (SVM) took the 16-dimensional statistical features to detect hidden message in RGB images. The experimental results indicate that the proposed algorithm realizes the reliable steganalysis of JSteg, F5, OutGuess, Steghide and MB1, which is suitable for universal steganalysis for RGB images.
    Multimedia processing technology
    Non-negative tensor factorization based on feedback sparse constraints
    LIU Yanan XU Zhengzheng LUO Bin
    2013, 33(10):  2871-2873. 
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    In order to fully use the structural information of the data, and compress the image data, the sparse constraints of the subspace (feedback) were applied to the object function of non-negative tensor factorization. Then this algorithm was used to reduce the dimension of the image sets. Finally, image classification was realized. The experimental results on the handwritten digital image database show that the proposed algorithm can effectively improve the accuracy of the image classification.
    Image recognition algorithm based on projection entropy
    SHAO Nan ZHANG Ke
    2013, 33(10):  2874-2877. 
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    A method based on projection entropy for image recognition was introduced in this paper. Since original definition of projection entropy does not make full use of image information and is not scale invariant, a new definition was proposed. The Local Projection Entropy (LPE) of normalized image was used for image recognition. In the process of recognition, firstly, Gaussian Mixture Model (GMM) of training set images’ LPE was obtained by Expectation Maximization (EM) algorithm. Then the Mahalanobis distance of target image’s LPE and GMM was calculated. The category of image was determined according to the distance discriminant law. Computer vision laboratory databases of Columbia university were used in the experiments, and the results show that the proposed algorithm is an effective approach for image recognition and has a proper structure for parallel computing.
    Face recognition with patterns of monogenic oriented magnitudes under difficult lighting condition
    YAN Haiting WANG Ling LI Kunming LIU Jifu
    2013, 33(10):  2878-2881. 
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    In order to improve the performance of face recognition under non-uniform illumination conditions, a face recognition method based on Patterns of Monogenic Oriented Magnitudes (PMOM) was proposed. Firstly, multi-scale monogenic filter was used to get monogenic magnitude maps and orientation maps of a face image. Secondly, a new operator named PMOM was proposed to decompose the monogenic orientation and magnitude into several PMOM maps by accumulating local energy along several orientations, then Local Binary Pattern (LBP) was used to get LBP feature map from each PMOM map. Finally, LBP feature maps were divided into several blocks, and the concatenated histogram calculated over each block was used as the face feature. The experimental results on the CAS-PEAL and the YALE-B face databases show that the proposed approach improves the performance significantly for the image face with illumination variations. Other advantages of our approach include its simplicity and generality. Its parameter setting is simple and does not require any training steps or lighting assumption and can be implemented easily.
    Sign language recognition algorithm based on depth image information
    YANG Quan PENG Jinye
    2013, 33(10):  2882-2885. 
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    In order to realize the accurate recognition of manual alphabets in the sign language video, this paper presented a sign language recognition algorithm based on DI_CamShift (Depth Image CamShift) and SLVW (Sign Language Visual Word). First, it used Kinect to obtain the video and depth image information of sign language gestures. Second, it calculated spindle direction angle and mass center position of the depth images to adjust the search window for gesture tracking. Third, an Ostu algorithm based on depth integral image was applied to gesture segmentation, then the Scale Invariant Feature Transform (SIFT) features was extracted. Finally, it built the SLVW bag of words and used SVM for recognition. The best recognition rate of single manual alphabet can reach 99.67%, and the average recognition rate is 96.47%.
    Partial differential equation model of fingerprint image inpaiting based on orientation field
    HAN Zhike WANG Gui
    2013, 33(10):  2886-2890. 
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    This paper presented a new Partial Differential Equation (PDE) model for fingerprint image restoration, which was an effective method for fingerprint image automatic inpainting. The existing solutions to image inpainting have some drawbacks: satisfactory inpainting results for fingerprint image cannot be provided by common image inpainting models, usually due to the lack of geometric information of the direction field; or because of the introduction of geometric information of the direction field, error results, such as different ridge lines connected to each other, will appear during inpainting process. The main principle of the presented model was to employ the orientation field to act as the constraint of the diffusion directions after comparing and analyzing the existing solutions, and the gray information could be propagated into the inpainting domain along a local fix orientation in the inpainting process, which characterized the orientation of the ridges. The presented model improved normal PDE models for fingerprint image inpainting. The numerical experimental results show that the proposed model is superior to common models at inpainting fingerprint images.
    Image inpainting algorithm based on adaptive template
    ZHAI Donghai XIAO Jie YU Jiang LI Tongliang
    2013, 33(10):  2891-2894. 
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    Currently, template size of texture-based image inpainting algorithm is fixed. Therefore, when the template size is small, the inpainting accuracy improves, but time complexity increases substantially; on the contrary, when the size is large, the time complexity declines, but inpainting error rate increases significantly. Adaptive template size algorithm proposed in this paper can enlarge template size according to the change of expect and variance of grayscale value between current template and its expanded one. Meanwhile, this approach can reduce template size according to the match degree between template and exemplar. After adaptively determining the template size, texture-based image inpainting algorithm was improved and used in experiments. The experimental results show this approach can highly improve the inpainting accuracy with high efficiency.
    Application of PCNN with the improved traversal process in image processing
    XIA Xiaoluan DENG Hongxia LI Haifang
    2013, 33(10):  2895-2898. 
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    Images usually have multiple connected regions of the same color. For the problem that Pulse Coupled Neural Networks (PCNN) cannot abstract these areas separately, a PCNN model with improved traversal process was proposed. By introduceing the depth-first search traversal algorithm, multi-unconnected regions were activated on different layers, so as to achieve a separation. Finally, the new model was improved again for the effect of image noise. The activated scope in each layer was used to detect noisy pixels, and then the mean-shift algorithm was introduced to eliminate the noisy pixels. The separation effect of multi-regions with the same color in the image and the ability to eliminate noise has been verified by experiment.
    Printed circuit board image segmentation by local progressive graph cuts
    DONG Changhao YAN Bin ZENG Lei TONG Li LI Jianxin
    2013, 33(10):  2899-2901. 
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    The Graph Cuts segmentation algorithm is not sufficient to segment Printed Circuit Board (PCB) images with non-uniform gray level and complicated inner structure. A new interactive Local Progressive Graph Cuts (LPGC) segmentation method that modeled local constrained energy into a graph cuts framework was presented in this paper. The local constrained energy was adaptively generated by modeling the users additional information behind the interaction, such as the location of the seed, the class of the seed and the relative position between the seed and previous result. Through a comparison of different PCB image segmentation experiments, the results demonstrate the proposed method has better performance compared with the-state-of-art method such as graph cuts in terms of segmentation accuracy, controllability, and user experience.
    Corner detection algorithm using correlation matrix of Gabor directional derivatives
    ZHU Zhanli CHEN Yuxin
    2013, 33(10):  2902-2906. 
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    To improve the accuracy of the corner detection, a new corner detection algorithm was proposed, and it used the Gabor directional derivatives of each pixel to construct the correlation matrix on edge contour.to detect corner. The algorithm firstly extracted the edge map of an image using the Canny edge detector; secondly, the image was smoothed by the Gabor filters and the correlation matrixes were constructed using Gabor directional derivatives of each edge pixel and its surrounding pixels. If the sum of the normalized eigenvalues was not only above the previously specified threshold but also the local maximum, it would be labeled as a corner. Compared with the traditional contour-based corner detection algorithm, it used the related information of the Gabor directional derivatives of the edge pixel and its surrounding pixels to extract corners, hence achieving better robustness to noise. The experimental results indicate that: The proposed algorithm detects more matched corners and fewer false corners in the noise free and noisy cases and achieves obvious improvement in performance.
    Precise object tracking algorithm for fusion image based on local image matting
    CHEN Yuyu QIAN Xiaoyan
    2013, 33(10):  2907-2910. 
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    A precise object tracking algorithm for fusion image based on local image matting was proposed in this paper to improve the tracking effect. Firstly, the rough region of the moving target could be captured by the minus of the sequence’s first two frames and therefore the rectangle was generated for local matting and the discriminative color set of foreground and background. Then the coarse region and the following tracking results automatically provided sufficient and accurate scribbles for matting, which made matting applicable in a tracking system. Finally accurate boundaries of the target could be obtained from matting results so that the model was successfully updated. For experimental image sequences, the mean error of the proposed algorithm was 0.9 pixels between forecasted center and real center of target, and that of traditional mean-shift was 5.2 pixels. The experimental results show that the proposed algorithm can detect the contour of target accurately, ovviously avoids model drift and promotes precision of tracking.
    Dynamic and real-time errhysis effect simulation in virtual liver surgery
    PENG Shi XIONG Yueshan XU Fan TAN Ke PAN Xinhua
    2013, 33(10):  2911-2913. 
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    In an actual operation, errhysis in the wound happens frequently during surgery cutting. Most previous studies, focus on skin or organ surface more than dynamic blood oozing in the inner wound. Therefore, upon the requirements of authenticity and real-timing, an oozing simulation model combined with force feedback was proposed. The model used Lagrangian approaches in fluid simulation system, and especially simplified the traditional Lagrangian approaches in this specific liver cutting process. The experimental results show that it can meet the demand of authenticity and real-time in dynamic ooze blood simulation.
    Target tracking algorithm based on particle filter and learning with local and global consistency
    WEI Baoguo LI Kejing CAO Cizhuo
    2013, 33(10):  2914-2917. 
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    To solve target tracking with target changes under complex background, an adaptive target tracking method that combined graph-based semi-supervised learning method with the particle filter was proposed. It used LLGC (Learning with Local and Global Consistency) algorithm to establish the cost function, and took current status of the candidate as unlabeled samples, then established diagram using all samples as vertex, taking the optimal solution of the cost function as current status, obtaining the target position in current frame. Besides, it used the tracking result to update the labeled samples in real time, so that the algorithm could adapt to the target deformation, partial occlusion and illumination changes. Analysis and experiment show that the proposed method can handle complicated situations like occlusion or similar background interference very well, and achieves target tracking robustly.
    Video jitter detection algorithm based on forward-backward optical flow point matching motion entropy
    JIANG Aiwen LIU Changhong WANG Mingwen
    2013, 33(10):  2918-2921. 
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    The conflicts between the real-time, efficient intelligent analysis and the inefficient, laborious trouble shooting, which are faced by most of video surveillance systems, can be resolved by Intelligent Video Quality Detection System (IVQDS). As a part of IVQDS, video jitter detection algorithm was focused in this paper. In the proposed method, sparse optical flow features were fused together with interest point matching algorithm; correctly matched point-set which was reliably detected according to the forward-backward error criterion, was used to estimate the global motion parameters, from which motion entropy was computed to measure the motion homogeneity of the video fragment. The experimental results tested on realistic surveillance video records have shown that the proposed algorithm can work under real-time environment against the effects from big movements with high detection performance.
    Video surveillance system-based motion-adaptive de-interlacing algorithm
    NIE miao LI Ying SHI Lizhuo JIANG Jiachen YAN Yachao
    2013, 33(10):  2922-2925. 
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    This paper proposed a motion-adaptive de-interlacing algorithm with high performance based on the analysis of the advantages and disadvantages of traditional de-interlacing algorithm for video surveillance systems. The algorithm divided the picture into static region and motion region on the basis of the motion state of interpolation points through 4-field motion detection which could detect the spatial-periodic pattern moving. Field insertion algorithm was exploited for interpolation of the static region. A modified edge-adaptive interpolation algorithm was used for the interpolation of the motion region which could increase the function of horizontal edge detection and enhance the level of consistency edge direction estimation. The proposed interpolation algorithm was implemented on DSP for experimental verification. The results show that the algorithm improves Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) and restrains saw-tooth, interline flicker, motion virtual image and other adverse effects and gets bettter visual effects.
    Bus ridership count mothod based on video stabilization and perspective switching
    XIE Lu JIN Zhigang WANG Ying
    2013, 33(10):  2926-2930. 
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    Most of the existing bus ridership count methods dont consider the video jitter caused by bus vibration and the trapezoidal distortion caused by the camera angle. The authors proposed a bus ridership count method based on video stabilization and perspective switching. Firstly, the presented method used video stabilization based on block-matching to reduce the offset between image sequences caused by vibration. Secondly, the method used perspective switching to correct the trapezoidal distortion caused by the camera angle. Lastly, the method used detection and tracking based on the characteristics of head and shoulder for statistics of the number of passengers. The experimental results show that the Peak Signal-to-Noise Ratio (PSNR) value of the stabilization video increases by about 4.5dB than that of the shaky video, and human recognition rate of the perspective switched video increases by about 10% than that of the original video. The method has greatly improved the accuracy of ridership count.
    Image denoising algorithm with variable exponent regularization and L1 fidelity
    GENG Hai HE Xiaowei FAN Junli
    2013, 33(10):  2931-2934. 
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    The L1 norm of gradient is used as the regularization term in the Total Variation (TV) model which can preserve the edges of the image well. However, it has the staircasing effect in the relatively smooth regions. Using the variable exponent function as the regularization term, the modified model can not only preserve the edges of image as well as the TV model but also decrease the staircasing effect obviously. Simultaneously, the L1 norm of 〖WTHX〗u-〖WTHX〗f was regarded as the fidelity term of the model, which can enhance the ability of image denoising.
    3D modeling of complex tunnel sections based on characteristic section
    QI Xiangming CHEN Zhenguo LU Quanhui
    2013, 33(10):  2935-2938. 
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    To resolve the problem of the complex 3D tunnel modeling generated by the changes of the tunnel sections at different rock formations during the project, the 3D tunnel modeling based on the characteristic sections was proposed. Through establishing the characteristic section model library, the 3D modeling of the changed tunnel sections was realized and the efficiency of the modeling of the complex tunnel sections was improved. Following the illustration of the data collection method and an analysis of the characteristic sections with detailed coordinates, the smoothing algorithm (smoothing the tunnel axis at the corner by an arc) of the changed tunnel sections at the corner was proposed. For the ordinary tunnel sections, the triangulation was applied in the 3D modeling; for the complex sections with simple quadrilateral structure, the 3D modeling was realized by using the Bézier surface method and the surface splicing techniques which has been validated through experiments.
    Improved tone modeling by exploiting articulatory features for Mandarin speech recognition
    CHAO Hao YANG Zhanlei LIU Wenju
    2013, 33(10):  2939-2944. 
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    Articulatory features, which represent the articulatory information, can help prosodic features to improve the performance of tone recognition. In this paper, a set of 19 pronunciation categories was given according to the pronunciation characteristics of initials and finals. Besides, 19 articulatory tandem features, which are the posteriors of speech signal belonging to the 19 pronunciation categories, were obtained by hierarchical multilayer perceptron classifiers. Then these articulatory tandem features, as well as prosodic features, were used for tone modeling. Tone recognition experiments of three kinds of tone models indicate that about 5% absolute increase of accuracy can be achieved when using both articulatory features and prosodic features. When the proposed tone model is integrated into LVSCR (Large Vocabulary Continuous Speech Recognition) system, the character error rate is reduced significantly.
    Bird sounds recognition based on energy detection in complex environments
    ZHANG Xiaoxia LI Ying
    2013, 33(10):  2945-2949. 
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    For the purpose of improving the recognition accuracy of bird sounds in various kinds of noisy environments in real world, a new bird sounds recognition approach based on energy detection was proposed. First of all, the useful bird sound signals were detected and selected by the method of energy detection from the bird sounds with noises. Secondly, according to the distribution of Mel scale, the feature of Wavelet Packet decomposition Subband Cepstral Coefficient (WPSCC) was extracted from the useful signals. Finally, the classifier of Support Vector Machine (SVM) was applied to model on the WPSCC and Mel-Frequency Cepstral Coefficient (MFCC) respectively for classification and identification. Meanwhile, the comparisons of recognition performance difference were implemented on 15 kinds of bird sounds at different Signal-to-Noise Ratio (SNR) in different noises, before or after energy detection. The experimental results show that WPSCC has better noise immunity function, and the recognition performance after energy detection can be greatly improved, which means it is more suitable for the bird sounds recognition in complex environments.
    Typical applications
    Inventory model for promotional merchandise with time-dependent partial backlogging rate and inventory-level-dependent demand rate
    HE Wei XU Fuyuan
    2013, 33(10):  2950-2953. 
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    Promoting commodities is an important promotion means for retailers to drive the sales of commodities to improve business sales revenue effectively. In this paper, by considering the effect of the selling price and the time on the waiting behavior of customers in shortage period, a new backlogging rate related to the selling price and the waiting time was constructed. An inventory model based on multiple orders and two-stage stock dependent selling rate and the waiting behavior of customers for promotional merchandise was proposed. The simulation method had been used to analyze the effect of the key parameters on the order policy and the total profits of the distributors. It shows that the price-sensitivity factor and waiting-time sensitivity factor have a significant effect on service level in each cycle; the critical value of stock-dependent demand rate has a great effect on order times. When the selling price changes in a certain range, distributors should adjust the service level of each cycle. When selling price is too high or too low, distributors should adjust both the service level of each cycle and the order times.
    Customer value classification model and application based on analytic network process and K-means clustering
    LUO Biao YAN Weiwei WAN Liang
    2013, 33(10):  2954-2959. 
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    A model was built to evaluate the customer value in terms of current value and potential value. This model used the Analytic Network Process (ANP) for weighting which considered the interrelationship among indexes, then calculated the customer value based on the weight and score of the indexes and then classified the customers by K-means. Taking a tobacco company for example at the end of this paper, qualitative and quantitative method was used to establish a customer value evaluation index system, ANP was used to weight indexes and classify the customers by K-means based on the evaluation result, and the marketing strategy of each customer group was analyzed at last. The proposed model can evaluate and classify the customer value more comprehensively and objectively.
    Profit distribution for information production supply chain based on modified interval-valued fuzzy Shapley value
    LU Zhigang ZHU Wenjin
    2013, 33(10):  2960-2963. 
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    The members of information production supply chain face different risks. The interval-valued fuzzy Shapley value method was proposed to calculate the distribution of profit to realize fairness. Under the condition of income uncertainty, the fuzzy profit values returns were built and a membership function of interval-valued fuzzy Shapley was introduced. A certain allocation decision was presented. Considering the impact of various risk factors on the distribution of profits, the Fuzzy Analytic Hierarchy Process (AHP) method was adopted to revise the risk factors to ensure the stability of the supply chain of information products.
    Passenger route choice behavior on transit network with real-time information at stops
    ZENG Ying LI Jun ZHU Hui
    2013, 33(10):  2964-2968. 
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    Along with the development of intelligent transportation information system, intelligent public transportation system is gradually popularized. Such information system is designed to provide all kinds of real-time information to transit passengers on the conditions of the network, and hence affect passengers’ travel choice behavior and improve passenger travel convenience and flexibility, so as to improve the social benefit and service level of the public transit system. Concerning the particularity of the transit network, with electronic bus stop information of Chengdu as an example, a questionnaire was designed to investigate passengers’ route choice behavior and travel intention. Qualitative and quantitative analysis and random utility theory were adopted，based on Logit model and mixed Logit model, route choice models were established, using characteristic variables of various options and passengers’ personal socio-economic attributes as explanatory variables. The method of Monte Carlo simulation and maximum likelihood were used to estimate parameters. The results indicate that the differences of route choice behavior resulting from individual preferences can be reasonably interpreted by mixed Logit model, which helps us better understand the complexity of transit behavior, so as to guide the application.
    Berth allocation problem with quay crane assignment of container terminals based on rolling-horizon strategy
    XIAO Ling HU Zhihua
    2013, 33(10):  2969-2973. 
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    In order to solve the large-scale integral dynamic scheduling model of continuous berths and quay cranes problem, a method based on rolling-horizon strategy was proposed. A multi-objective optimization model was established under the minimization of total penalty costs of deviation to preferred berthing positions, berthing delays and departure delays. Then the scheduling process was divided into a series of continual scheduling intervals according to the dynamic arrival sequences. Meanwhile, the movement strategy of windows and parameter renew strategy were designed. The input parameters of the model in next window were renewed according to the optimal results of each window. The model for each interval was solved by choosing appropriate rolling window and freezing the quantity of vessels. The holistic optimal solution was obtained by rolling and combining the results of each window. Finally, a case study indicated that the rolling schedule can solve large-scale scheduling problems. The efficiency of the proposed approach relates to the size of rolling window, frozen ship quantity and rolling frequency.
    Algorithm of point cluster similarity based on hierarchical Voronoi diagrams
    KANG Shun LI Jiatian
    2013, 33(10):  2974-2976. 
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    The hierarchical Voronoi diagrams were built through an adaptive clustering method of spatial point clusters. Based on the hierarchical Voronoi diagrams, the topology, density and scope similarities were calculated. The radian and distance similarity were calculated in combination of the standard deviation in mathematical statistics. On the base of every dimensional similarity, the principle of point cluster similarity was decided by the geometrical mean of these parameters. This optimizes the method of the point cluster similarity and the experiment proves its feasibility.
    Molten iron transportation scheduling optimization and simulation of iron and steel enterprises
    YANG Xiaoyan CUI Bingmei
    2013, 33(10):  2977-2980. 
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    Taking railway transportation of molten iron in steel enterprise as an object, the supply and demand relationship between hot metal in blast furnace and steel mills was met by Torpedo Car (TPC) transportation. For factory railway network, according to the distance between the molten iron supply and demand and the network point, as well as the factors such as track switches, signal, using the running flexibility time of TPCs and dynamic programming to optimize the hot metal scheduling method was put forward based on the molten iron transportation route choice and automatic conflict avoiding algorithms. Finally this paper formed an intelligent hot metal scheduling simulation system to assist the staff to realize the optimal allocation of locomotives and TPCs.
    Spatial data visualization based on cluster analysis
    ZHANG Yang WANG Chen
    2013, 33(10):  2981-2983. 
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    Firstly, the paper introduced the researches and basic methods of spatial data visualization technology, and analyzed two common kinds of methods, namely entity-based and region-based. A clustering-based spatial data visualization method was proposed, which firstly made a cluster analysis of spatial data and got the description parameters of the result through the use of spatial clustering algorithms represented by algorithm ASCDT (Adaptive Spatial Clustering algorithm based on Delaunay Triangulation). Secondly, it designed visual objects aimed at the cluster result by combining the basic visualization methods and the characteristics of the parameters. As a result, the mapping relationship was established. Finally, some issues that needed to be further studied and improved were discussed.
    Research on form dynamic configuration technology for industrial-chain coordination SaaS platform
    LYU Rui SUN Linfu LIU Shuya
    2013, 33(10):  2984-2988. 
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    In order to adapt to the dynamic changes of business requirements of collaborative enterprise in the operation course of collaborative platform, a form configuration model for Software as a Service (SaaS) platform was established. The storage and dynamical load of form configuration model were supported by mapping form structure and form elements with XML document. The method of online dynamic allocation operating authority of the form content was presented. Form online dynamic update technology was realized based on form configuration file access interface. The proposed technology was applied to a SaaS platform industrial chain, which shows that the flexibility is improved and the enterprises have more initiative and control over the management of information systems.
    Design and implementation of electronic paper display driver software
    HU Xingbo JIANG Yuan LIANG Hong GUO Yuhua FU Yonghua
    2013, 33(10):  2989-2992. 
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    Electronic Paper Display (EPD) can exhibit good comfortability in reading, but it has a critical drawback - slow refresh, which will be overcome by optimizing the design of the display's driver software. A tri-buffer-based architecture as well as its design methodology for the EPD driver software was proposed in this paper. Also an e-reader integrating the EPD driver in it was implemented to verify the design. Compared with the traditional dual-buffer architecture, the proposed tri-buffer scheme set an additional memory area to keep the EPD data frame. Test results show that the driver software works well in a real device without screen flicker and can help the display to achieve excellent performance.
    Aero-engine parameters estimation using fading Kalman filter algorithm
    HUANG Huixian REN Keming LI Yan ZHUANG Xuan
    2013, 33(10):  2993-2995. 
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    The deviation of the aero-engine on-board adaptive system model could not be completely eliminated, which may result in serious estimation deviation and filtering divergence. A new Kalman estimation algorithm with fading factor was proposed. Adjusting the weight of innovation covariance and increasing the effect on realistic measurement data in state estimation, the accuracy of aero-engine parameters estimation was ensured. Compared with the conventional Kalman filtering, the simulation results shows that the method proposed can restrain filtering divergence and obtain the high accuracy of estimation and the short convergence time. The derivation of the new method is simple, the computation amount is little, and the engineering application value is high.
    Carrier aircrafts operational readiness based on condition-based maintenance
    LI Mansi SHANG Yongshuang ZHANG Yongyu
    2013, 33(10):  2996-2999. 
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    The maintenance system based on Condition-Based Maintenance (CBM) is a complex dynamic system. The interaction between the different elements leads to dynamic changes in the maintenance system. By analyzing the nature of condition-based maintenance, taking the carrier-based aircraft readiness as the research target, using the method of System Dynamics (SD), and the simulation software VENSIM special to analyze the feedback control structure of internal elements in the condition-based carrier aircraft maintenance support system, the SD model based on the condition-based maintenance for operational readiness of the carrier-based aircraft was established. The simulation results operated by the SD model show that the condition-based maintenance method introduced into the carrier aircraft maintenance support system can effectively improve the carrier aircrafts operational readiness.
    Adaptive dynamic surface control for a class of high-order stochastic nonlinear systems
    DENG Tao YAO Hong PAN Yunliang
    2013, 33(10):  3000-3004. 
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    This paper concerned the output tracking problem for a class of high-order stochastic nonlinear systems. Based on the backstepping control by adding a power integrator, an adaptive smooth state-feedback dynamic surface controller was proposed. The derivative of the designed adaption law was continuous by making use of the Sigmoid function. “Explosion of complexity” phenomenon in the adding a power integrator method design was eliminated by introducing a filter at each step of the recursive procedure and employing the dynamic surface control. The stability analysis was carried out by choosing an appropriate conol Lyapunov function. And its results show that the output can be regulated to the small neighborhood of the reference signal in probability. The results of a simulation example demonstrate the effectiveness of the proposed adaptive smooth state-feedback dynamic surface controller.
2025 Vol.45 No.4

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