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Table of Content

    23 June 2017, Volume 0 Issue 6
    A Japanese-English Hierarchical Phrase-based Translation Model Integrating Tense Features
    MING Fang, XU Jin-an, WANG Nan, CHEN Yu-feng, ZHANG Yu-jie
    2017, 0(6):  1-7.  doi:10.3969/j.issn.1006-2475.2017.06.001
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    In view of the problem that limited contextual information is used in the hierarchical phrase-based (HPB) translation model and the quality of tense translation is not high, this paper proposes a method to integrate tense features into Japanese-English HPB translation. Our method adopts the information of tense as constraints for tense classification model construction, and integrates tense features into HPB translation model, the decoder can get the best-matching rules according to the results of potential tense classification of rules. Firstly, we extract training data from bilingual training corpus to train tense classification models by using maximum entropy. Secondly, we extract tense features from hierarchy phrase rules to classify each kind of rules which include tense information, then we take the tense classification results as a kind of new translation features, and integrate the features into hierarchy phrase-based translation model. The experimental results show that our method can achieve good performance in Japanese-English HPB translation.
    Ships Equipment Fault Diagnosis Method Based on Improved Radical Basis Function Neural Network
    HAN Ke, XIE Qiang, DING Qiu-lin
    2017, 0(6):  8-14+19.  doi:10.3969/j.issn.1006-2475.2017.06.002
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    For the ships equipment fault diagnosis problems with lack of applicability and accuracy during ships sailing, this paper designs a radical basis function neural network method for ships equipment fault diagnosis. An improved artificial bee colony (IABC) algorithm combining opposite learning initialization strategy and auto-adapted search strategy is designed, which builds higher quality initial solution space through opposite learning initialization strategy and adapts its local search length automatically to improve the ability of convergence and local optimization searching. IABC algorithm is used in parameter optimization of radical basis function neural network (RBFNN) for constructing a better performed classifier. The results show that the IABC-RBFNN framework can improve the accuracy and usability of ship fault diagnosis, and satisfy the real-time requirement of ships equipment fault diagnosis.
    Prediction of User’s Moving Location Based on Period-Near Algorithm
    GAO Xia
    2017, 0(6):  15-19.  doi:10.3969/j.issn.1006-2475.2017.06.003
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    Sina Weibo is an electronic medium that allows a large number of users to share personal information with each other including location information, which makes it possible to know users’ movement. Even though users’ movement and mobility patterns have a high degree of freedom and variation, periodicity is a frequently happening phenomenon for users. Finding periodic behaviors is essential for understanding user movements. In this paper, we address the problem as to predict where a user will go. It involves two sub-problems: how to detect users’ historical behavior, and how to use historical behaviors to predict the behavior in the future. Our main assumptions are that users’ behaviors are periodic and a user will stay in one location if he or she stays in this location for a long time. Based on these assumptions, we propose a 4-stage algorithm, Period-Near, to solve the problem. At the first stage, we mine the periodic behaviors of a user, then, find frequent transfers. At the third stage, we aim to know where the user is in the nearest time. At last, we consider the three stages together to predict where the user will go in the next time. Empirical studies on both synthetic and real data sets demonstrate the effectiveness of our method.
    A Method for Determining Expert’s Weight Based on Consistency of Judgment Matrix
    LI Yan-ling1, WU Jian-wei1, ZHU Ye-hang2
    2017, 0(6):  20-24+29.  doi:10.3969/j.issn.1006-2475.2017.06.004
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    The degree of consistency of judgment matrix can reflect the level of consistency of expert thinking, which is an important factor to determine the weight of experts based on judgment matrix. Aiming at the problem that the traditional Euclidean distance method is not concerned with the relative difference between elements, and the measure of similarity degree (or degree of difference) is easy to be affected by the 1-9 scale, the expert weight determination method based on the consistency degree of judgment matrix was studied. The expert weight determination method based on Euclidean distance and grey correlation degree was proposed, and the method of expert weight determination based on relative distance was also proposed. In the former, the relative value of the consistency degree of the expert judgment matrix was calculated by introducing the grey correlation degree; and in the latter, the relative distance method was used to reduce the influence of 1-9 scale. In the example analysis, it is proved that the order of expert weighting obtained by the two proposed methods is reasonable compared with the traditional Euclidean distance method, and the different characteristics of the proposed methods are analyzed, which provides reference for the method selection in practical application in the future.
    User Interest Mining via Multivariate Probit Regression
    SHEN Qiang-hua
    2017, 0(6):  25-29.  doi:10.3969/j.issn.1006-2475.2017.06.005
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    Mining user interest is a fundamental technique in many fields such as recommender system, personalized retrieval and online advertising. The historical actions of a user through the Web or in real word reflect his interests. However, if the user uses the Web at his first time, it is difficult to learn his interests because only few historical actions are known. To deal with this issue, we propose a variant of multivariate Probit model to learn the prior of the user’s interests based on user’s attributes. The attributes may include sign up location, sign up time and some other registration information. The posterior distribution of the model is simulated by a Markov chain Monte Carlo (MCMC) method to estimate the expectation of user’s interest. To evaluate our algorithm, we collect the information of movie stars and their movies as the evaluation dataset. The experiment on this dataset demonstrates that the prior information can effectively improve the performance on cold start users.
    A News Hot Spot Detection Method Based on Semantic Analysis
    CAO Tong
    2017, 0(6):  30-33+39.  doi:10.3969/j.issn.1006-2475.2017.06.006
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    With the development and popularization of the Internet, Internet news reports are the main means for people to get social information. How to get the hot topic of Internet news quickly and accurately is an urgent problem to be solved. This paper uses the theme model of LDA (Latent Dirichlet Allocation) and BTM (Biterm Topic Model), fully considering the different impacts of news headlines and news content on news hot spot detection, to make the semantic analysis of news content and title respectively. By using the BTM model for news headlines and the LDA model for news content, we extract the feature vectors of the topic and combine the two semantic features to form the semantic feature of the whole text. Then, through improved clustering algorithm, the number of documents belonging to each topic is calculated. On this basis, by defining the news heat and using the news heat formula, the news heat is calculated to get the most recent hot news through ordering the news heat values. Through the experiments on the crawling news data, the validity and practicability of the method are verified.
    An Auxiliary Teaching Software About Process Visualization Class C Compiler
    DING Zhi-jun, ZHOU Ze-xia, WEI Zhi-hua
    2017, 0(6):  34-39.  doi:10.3969/j.issn.1006-2475.2017.06.007
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    In the course “Compiler Principle”, there are many knowledge points and very complex concepts, which are too theoretical that the algorithms are difficult to understand, with high complexity and abstraction, not closely linked with the actual. For these problems, we analyze the necessity of the compiler process visualization in the “Compiler Principle” teaching as well as the defects and deficiencies of the existing studies, design and implement the PVC3TAI, which function is more complete, user-friendly, visual process is more detail, specific and can dynamically display the process of compiling operation mechanism. Therefore, combining theory with practice, the better teaching results are achieved.
    Timeliness Requirement Validation of Brake Control System Based on SysML & AADL
    DENG Jia-jia, ZHANG Yu-ping, CHEN Hai-yan
    2017, 0(6):  40-44+49.  doi:10.3969/j.issn.1006-2475.2017.06.008
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    It is a vital process to validate whether the system architecture and properties of its components designed by the developers meet the timeliness requirement while developing an avionics system. In order to validate the time delay of the IMA brake control system, the architecture and working process of the system are both analyzed, based on which, SysML block model and state machine diagrams along with MARTE-marked time attributes are established. Analyzing system models with verification tools is an efficient method to validate system requirements. Hence, we need to transfer the SysML model to AADL model according to the mapping relationship between these two languages. At last, the AADL model is obtained, the system analysis tool COMPASS is applied to verify the time delay of the model to check if it meets the predetermined requirement.
    Loop Skewing Optimization on Global Data Regrouping
    CHEN Hua-jun1,2, WANG Qi3, HONG Chao1,2, FANG Meng1,2
    2017, 0(6):  45-49.  doi:10.3969/j.issn.1006-2475.2017.06.009
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    Loop skewing is a method of loop transformation in program optimization. It changes the form of iteration space and marks the across iterations in loops with the traditional parallel. The loop can be calculated in parallel. But after loop skewing, data which is programed in parallel is discrete. Times of every iteration execution are different. To make full use of SIMD extension, this paper presents loop skewing optimization on global data regrouping. We analyze loop skewing optimization and regroup the data in array for the problem of discrete data. This part improves the data locality and it is simple to do the vector operation. Then we realize the non-full vector operation for the problem of different iteration times. This part makes the tail loop can be executed in vectorization. At last, we choose the wavefront program for testing. After optimization, the program execution speed can be increased by 10.73 times in average.
    Multithreaded Program Testing Based on Controlling Sequence of Thread Schedule
    LI Jing
    2017, 0(6):  50-55.  doi:10.3969/j.issn.1006-2475.2017.06.010
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    As multi-core techniques become pervasive, programming multithreaded programs is becoming popular. However, the problem of correctness of multithreaded program has affected software reliability severely. Moreover, current testing techniques can not satisfy the requirements of multithreaded programs. This paper focuses on the most common type of bugs in multithread programs, which is called data race. We propose a testing approach based on controlling sequence of thread schedule, combining static approach with dynamic approach. The approach can effectively find the data races in multithreaded programs, and identify the harmful data races that are required to be fixed urgently. Experimental results show that our approach improves the probability of triggering data races significantly, from 0.53% to 79.2% averagely. Moreover, the runtime overhead imposed by our approach is on average 80%, and the overhead imposed by related approach is 370%, demonstrating our approach is better.
    Dictionary Learning Algorithm Based on Label Consistent and Locality Constraint
    LI Zheng-ming1,2, YANG Nan-yue1
    2017, 0(6):  56-60.  doi:10.3969/j.issn.1006-2475.2017.06.011
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    In order to improve the classification performance of the learned dictionary, a dictionary learning algorithm based on the label consistent and locality constraint of atoms (LCLCDL) was proposed. The discriminative sparse codes matrix was constructed by using the labels of the atoms and training samples, and then the label consistent model was designed as the discriminative term. It can encourage the training samples of the same class to have similar coding coefficients. The locality constraint model was constructed by using the atoms and the lines of coding coefficient matrix (Profiles), and it can inherit the geometric structure of the training samples. Experiment results show that the LCLCDL algorithm achieves more higher classification performance than five sparse coding and dictionary learning algorithms.
    Large-scale Image Storage and Retrieval Based on Hadoop
    ZHU Shan, AI Li-hua
    2017, 0(6):  61-66+83.  doi:10.3969/j.issn.1006-2475.2017.06.012
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    The exponential growth of images makes the traditional single machine image retrieval face the problem of slow retrieval speed, poor concurrency and low image accuracy when dealing with large-scale images. According to that the image feature files are small files, this paper proposed to properly merge the small files, and then put store them on thedistributed file system HDFS of Hadoop. It achieved rapidly store and read massive image data. In order to adapt to the large-scale image retrieval, this paper proposed to binarize Fisher vector of images and use MapReduce parallel programming model to realize parallel image retrieval based on binary Fisher vector and SIFT. Experiments on INRIA Holidays dataset, Kentucky dataset and Flicker1M dataset show that the method is scalable, can achieve better retrieval accuracy, effectively reduce the retrieval time and improve the retrieval speed. It is a highly efficient large-scale image storage and retrieval method.
    Virtual Human Skinning Animation Algorithm Based on Depth Image Sequences
    XIAO An-nan1, ZHANG Cheng-wei2, DAI Xian-yu2, FEI Ting-ting3, MA Yin-zhong3
    2017, 0(6):  67-71+107.  doi:10.3969/j.issn.1006-2475.2017.06.013
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    Virtual human skinning animation is an important issue in the field of virtual human modeling, which has significant value in the application of film and television production, animation design, and virtual reality, etc. For virtual human skinning animation research, the core of the problem is the skinning parameter calculation, and that skinning calculation is accurate or not determines if the animation is lifelike or not. Common method is the direct calculation method based on the bones and skin, but this method has largely great dependence to posture, and there is no quantitative measure, hard to ensure accuracy. This paper proposed a method that needed skinning parameter optimization and calculation based on depth image sequences. This method was based on the depth image sequence under different posture, designed optimization function about skinning and posture parameters, and took deformation of different postures into comprehensive consideration. Skinning parameters and posture parameters were optimized by the alternate, until the target function reached convergence, and then we output the skinning parameters. The experimental results show that the proposed method has a better animation effect on the vision, and a smaller error on the error comparison when compared with other methods.
    A Customized PDF Reader Based on Android Platform
    LIU Zhi-wei1, DONG Zheng-hong2, YANG Fan2, LI Meng-wei1
    2017, 0(6):  72-75+90.  doi:10.3969/j.issn.1006-2475.2017.06.014
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    In recent years, the number of mobile terminal grows rapidly, smartphones and tablets computer have brought great convenience to our life and study. In the process of teaching and production practice, a lot of materials such as teaching courseware and training manuals can be placed in the Android terminal for reading, but the functions of some Android terminal PDF readers in the market are too complex or too simple to meet our personalized requirements, so this paper developed a PDF reader using an open source MuPDF analyzer as the kernel. From the aspects of startup view, bookshelf view and reading view, we developed the application software, which has several personal functions e.g. startup password, fixed shelf, navigation drawer and bookmark. There is certain reference value in this paper for the development of open source PDF reader.
    Museum Visiting and Guiding System Based on ZigBee
    ZHONG Xi-wu, XU Chun-yu, HUANG Yi-tao, HUANG Zhen
    2017, 0(6):  76-79+102.  doi:10.3969/j.issn.1006-2475.2017.06.015
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    At present, people can use mobile GPS function to accurately plan travel route outdoors. However, indoor environment is so complex and having multipath phenomenon. So it is difficult for GPS to position in an indoor environment. Combining with the previous studies and based on the principle of fingerprint location algorithm, this paper applies the ZigBee indoor positioning technology in the scene of visitors to visit museum. By using ZigBee wireless local area network, received signal strength indication and fingerprint location algorithm, the system uses the GPRS module to transfer data, the database server to process data, and the Android APP to monitor data. So it could make the visitors’ location information in the museum to be displayed on the APP in a timely manner. At the same time, it could push the information of the exhibit that visitors are visiting according to the location of them in the museum. Test results show that the system operation is good and is in line with the expected requirements basically.
    Water-saving Irrigation Remote Monitoring System Based on Web
    CHEN Cheng
    2017, 0(6):  80-83.  doi:10.3969/j.issn.1006-2475.2017.06.016
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    In order to meet the requirements for automatic control of irrigation, a water-saving irrigation remote monitoring system was studied based on 3G wireless communications technology and Web. The functions of remote monitoring, communication, and automatic control are achieved. In order to achieve the purpose of refreshing partial data and images on the pages, by analyzing the popular Ajax frameworks, jQuery framework is selected for the remote monitoring system. Finally, the Ajax technology is applied to remote monitoring system, to achieve the effect of a partial page refresh, and summarize the advantages and disadvantages of Ajax technology.
    A Community Detection Algorithm of Multiplex Networks with Layer Reduction
    CHEN Li-hu, LIN You-fang, WU Zhi-hao, JING Li-ping
    2017, 0(6):  84-90.  doi:10.3969/j.issn.1006-2475.2017.06.017
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    How to detect community in a multiplex network is a knotty problem. Currently some algorithms represent the multiplex network as a three-way tensor and use non-negative tensor factorization to capture the community structure. However, if there are many edges between communities or when the multiplex network is sparse, the non-negative tensor factorization algorithm won’t work well. To this end, this paper introduced an improved algorithm. The algorithm first merges the layers which have strong correlation to reduce the number of layers of multiplex network for the sake of highlighting the community structure. And then the algorithm uses non-negative tensor factorization to detect community. This paper validates the approach on both synthetic benchmarks and real multiplex networks, and the result shows that the algorithm performs better than the old approach.
    Performance Evaluation Method of Ad Hoc Routing Protocol Based on Wired Network
    HU Ming-ming1, SUN Yan-tao2, REN Shu-ting3
    2017, 0(6):  91-96.  doi:10.3969/j.issn.1006-2475.2017.06.018
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    Software simulation and in-situ test analysis, theoretical analysis and other methods can be used for performance analysis and evaluation of ad hoc routing protocol. Due to the high cost of in-situ test analysis and the complicated experimental environment deployment, at present, the software simulation is the main method for ad hoc routing protocol performance evaluation, however, this method is not convincing for the study of ad hoc networks through practical application scenarios. Comparing the advantage and the disadvantage of the various methods, we propose a new ad hoc routing protocol performance evaluation method based on wired network: Adding various statistics probe into the application layer, network layer, link layer to collect performance data. In addition, we design and implement a visualization data acquisition and analysis platform, which can collect the performance data for graphical display and analysis and evaluation. This method not only makes up the influence of the sensitive factors such as operating system, system hardware, system design and communication environment, but also solves the problems appeared in in-situ test analysis, e.g. the performance data is not easy to be acquired, the cost is huge and the scene construction is complicated. At last, this paper compares the performance of three typical ad hoc network routing protocols by using the proposed performance data acquisition and evaluation method.
    Routing Algorithm of Military Vehicle Network Based on Mobile-model
    FAN Ying-biao1, WEN Fu-peng2
    2017, 0(6):  97-102.  doi:10.3969/j.issn.1006-2475.2017.06.019
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    This paper means to discuss the importance of survivability and robustness of communication link in the integrated joint operation, and analyzes the reason of the network interruption and delay. The typical aggregate-spread mobile model is established based on military vehicle, and then an expected-meeting opportunity routing algorithm based on the operational schedule and channel status is proposed, thus the message delivery and delay are greatly improved.
    Signature from Automorphism Group of Special Linear Group
    PAN Ping, CAO Yang, HE Bin-tao
    2017, 0(6):  103-107.  doi:10.3969/j.issn.1006-2475.2017.06.020
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    Based on the discrete logarithm problem in the automorhoism group of special linear group, this paper proposes a signature scheme over the non-commutative group, and analyzes the difficulty ofthe discrete logarithm problem in the automorhoism group of special linear group. The paper shows that, by selecting proper parameters, the new scheme is much more secure than DSA in the finite field and is as secure as DSA over elliptic curves. The result shows the running efficiency of the new scheme is improved by adopting Leedham-Green algorithm to compute the power of matrices.
    Approach for Detecting Covert Timing Channels Based on One-class SVM
    LIU Yi, LAN Shao-hua
    2017, 0(6):  108-111+121.  doi:10.3969/j.issn.1006-2475.2017.06.021
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    The detection of covert timing channel is the focus and the difficulty of the research on covert channel. Current detections of covert timing channels are more directed against some particular covert timing channels, not all applicable. In this paper, a detection approach based on one-class SVM was introduced. Detection of covert channels is seen as a one-calss calssification problem. The model-building part of the algorithm works trained by the common channel set and generates the classification model. Experimental results show that the detection method can not only ensure a higher detection rate and better versatility, but also effectively detect covert timing channels.
    A Data Hiding Protection Method for Power Grid Based on Content Sensation Cluster
    LIN Fan-long, CHEN Qian, CHEN Liang
    2017, 0(6):  112-115+126.  doi:10.3969/j.issn.1006-2475.2017.06.022
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    Efficient and reliable data hiding protection can effectively prevent the active data disclosure of power network data center. Current data hiding methods suffer from high redundancy and low sparse. A data hiding protection method for power grid based on content sensation cluster is proposed, which constructs support vector machine data extract features framework. Orthogonal regression data clustering parameter are designed to control the data hiding number. Simulations and tests demonstrate the improved performance of new method.
    Using SPSS and Matlab to Study Stability of Rodent Community
    LUO Min1,2, LI Chang-you3, DAI Huan1,2
    2017, 0(6):  116-121.  doi:10.3969/j.issn.1006-2475.2017.06.023
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    The stability of rodent community in a desert area of Northwest China is analyzed. By GM(1,1) statistical analysis mathematical model, SPSS predicts their respective change trends of the numbers of different rodents in different disturbance conditions. Combining Matlab simulation with neural network algorithm, the influence of external disturbance on the diversity of rodent community is analyzed. The integration of the two methods can more reasonably analyze and predict the change trends of animal communities in the area, so as to get the stability of rodent community in this area.
    A Crop Soil Moisture Control Algorithm Based on PIDNN
    GAO Yan, LIU Hong-xia
    2017, 0(6):  122-126.  doi:10.3969/j.issn.1006-2475.2017.06.024
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    Aiming at different requirements of different crops for soil moisture, a soil moisture control algorithm based on PIDNN is proposed. PIDNN and improved PSO algorithm are combined in this algorithm which could meet different needs of soil moisture of crops in a large field. The simulation result shows that this algorithm can effectively meet soil moisture requirements of all kinds of crops. And it also could improve overall control performance of system, shorten adjusting time and has better dynamic performance.